Design and Modeling for 2D Plate Type MR Damper

A two-dimensional magnetorheological damper is developed for the engineering two-dimensional damping need. The velocity and pressure distribution model of the two-dimensional plate-type damper, and the damping force calculation model are established based on the Navier-Stokes equation. Several structural and physical parameters, including the working gap δ, the length a, and the width a of the middle slide plate, are analyzed theoretically. The damping performance of the two-dimensional plate-type magnetorheological damper was evaluated using a two-dimensional vibration test-bed, with the effect of the excitation current analyzed. The experimental results suggest a significant influence of Coulomb damping force on the damping force of magnetorheological damper when using appropriate magnetorheological fluid. As the excitation current increases, the damping force of magnetorheological damper becomes larger while the system amplitude decreases gradually in both directions, a maximum reduction of 2.5956 times. It's confirmed that the design of the two-dimensional plate-type magnetorheological damper is reasonable

Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal

Objective: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of non-ideal acquisition conditions, and interference with strong background signals mainly from macromolecules. The most popular method, LCModel, adopts complicated non-linear least square to quantify metabolites and addresses these problems by designing empirical priors such as basis-sets, imperfection factors. However, when the signal-to-noise ratio of MRS signal is low, the solution may have large deviation. Methods: Linear Least Squares (LLS) is integrated with deep learning to reduce the complexity of solving this overall quantification. First, a neural network is designed to explicitly predict the imperfection factors and the overall signal from macromolecules. Then, metabolite quantification is solved analytically with the introduced LLS. In our Quantification Network (QNet), LLS takes part in the backpropagation of network training, which allows the feedback of the quantification error into metabolite spectrum estimation. This scheme greatly improves the generalization to metabolite concentrations unseen for training compared to the end-to-end deep learning method. Results: Experiments show that compared with LCModel, the proposed QNet, has smaller quantification errors for simulated data, and presents more stable quantification for 20 healthy in vivo data at a wide range of signal-to-noise ratio. QNet also outperforms other end-to-end deep learning methods. Conclusion: This study provides an intelligent, reliable and robust MRS quantification. Significance: QNet is the first LLS quantification aided by deep learning

CloudBrain-MRS: An Intelligent Cloud Computing Platform for in vivo Magnetic Resonance Spectroscopy Preprocessing, Quantification, and Analysis

Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectra plots and metabolite quantification, the widespread clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: 1) Automatically statistical analysis to find biomarkers for diseases; 2) Consistency verification between the classic and artificial intelligence quantification algorithms; 3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, both healthy and mild cognitive impairment patient data are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing free access and service for two years. Please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html.Comment: 11 pages, 12 figure

Subharmonic Solutions with Prescribed Minimal Periodic for a Class of Second-Order Impulsive Functional Differential Equations

By using critical point theory and variational methods, we investigate the subharmonic solutions with prescribed minimal period for a class of second-order impulsive functional differential equations. The conditions for the existence of subharmonic solutions are established. In the end, we provide an example to illustrate our main results

Quantifying the growth of continental crust through crustal thickness and zircon Hf-O isotopic signatures: A case study from the southern Central Asian Orogenic Belt

Accretionary orogens function as major sites for the generation of continental crust, but the growth model of continental crust remains poorly constrained. The Central Asian Orogenic Belt, as one of the most important Phanerozoic accretionary orogens on Earth, has been the focus of debates regarding the proportion of juvenile crust present. Using published geochemical and zircon Hf-O isotopic data sets for three belts in the Eastern Tianshan terrane of the southern Central Asian Orogenic Belt, we first explore the variations in crustal thickness and isotopic composition in response to tectono-magmatic activity over time. Steady progression to radiogenic zircon Hf isotopic signatures associated with syn-collisional crustal thickening indicates enhanced input of mantle-derived material, which greatly contributes to the growth of the continental crust. Using the surface areas and relative increases in crustal thickness as the proxies for magma volumes, in conjunction with the calculated mantle fraction of the mixing flux, we then are able to determine that a volume of ~14–22% of juvenile crust formed in the southern Central Asian Orogenic Belt during the Phanerozoic. This study highlights the validity of using crustal thickness and zircon isotopic signatures of magmatic rocks to quantify the volume of juvenile crust in complex accretionary orogens. With reference to the crustal growth pattern in other accretionary orogens and the Nd-Hf isotopic record at the global scale, our work reconciles the rapid crustal growth in the accretionary orogens with its episodic generation pattern in the formation of global continental crust.12 month embargo; published: 23 December 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Metropolitan Architecture and Sustainable Habitats in the Indo-Pacific Region to Reinforce the Megacity System Through Urban–Rural Patterns

The Indo-Pacific region needs a comprehensive view of the risks of widening existing inequalities or creating new ones due to the Green and Digital Transitions to improve the quality of life. The goal is to define Regenerative Actions to strengthen existing sustainable habitats and create/support trans-regional and national clusters. Interstitial actors must act as mediators and adapt existing knowledge to new situations. Twin Transitions require new forms of governance and compelling service access issues to identify and reinforce existing sustainable communities. Spatial analysis is needed to generate a strategic vision of territorial shrinkage for Japan. Spatial planning strategies can address population shrinkage by promoting the Desakota phenomenon and fostering the proximity of urban settlements and agriculture. The study aims to explore how Harmony can be integrated into an Operating Culture that encompasses anthropological, social, and economic aspects of cooperation with nature. Nature is critical in shaping the relationship between humans and technology, and culture is the soul that integrates technology and nature. Asian continent significance lies in its technological advancements and its potential to help China overcome its particularism and discover new ways of understanding unity. The Asian and Japanese experience has shown how the community dimension can be effective in an emergency, and how the vulnerability of a community can be transformed into a resource. Realistic contexts are necessary to achieve desired outcomes, and Asian societies must harness and transform these energies into productive innovation

Effect of Hormone Replacement Therapy on Cardiovascular Outcomes: A Meta-Analysis of Randomized Controlled Trials

<div><p>Background</p><p>Hormone replacement therapy (HRT) is widely used to controlling menopausal symptoms and prevent adverse cardiovascular events. However, the benefit and risk of HRT on cardiovascular outcomes remains controversial.</p> <p>Methodology and Principal Findings</p><p>We systematically searched the PubMed, EmBase, and Cochrane Central Register of Controlled Trials databases for obtaining relevant literature. All eligible trials reported on the effects of HRT on cardiovascular outcomes. We did a random effects meta-analysis to obtain summary effect estimates for the clinical outcomes with use of relative risks calculated from the raw data of included trials. Of 1903 identified studies, we included 10 trials reporting data on 38908 postmenopausal women. Overall, we noted that estrogen combined with medroxyprogesterone acetate therapy as compared to placebo had no effect on coronary events (RR, 1.07; 95%CI: 0.91–1.26; P = 0.41), myocardial infarction (RR, 1.09; 95%CI: 0.85–1.41; P = 0.48), stroke (RR, 1.21; 95%CI: 1.00–1.46; P = 0.06), cardiac death (RR, 1.19; 95%CI: 0.91–1.56; P = 0.21), total death (RR, 1.06; 95%CI: 0.81–1.39; P = 0.66), and revascularization (RR, 0.95; 95%CI: 0.83–1.08; P = 0.43). In addition, estrogen therapy alone had no effect on coronary events (RR, 0.93; 95%CI: 0.80–1.08; P = 0.33), myocardial infarction (RR, 0.95; 95%CI: 0.78–1.15; P = 0.57), cardiac death (RR, 0.86; 95%CI: 0.65–1.13; P = 0.27), total mortality (RR, 1.02; 95%CI: 0.89–1.18; P = 0.73), and revascularization (RR, 0.77; 95%CI: 0.45–1.31; P = 0.34), but associated with a 27% increased risk for incident stroke (RR, 1.27; 95%CI: 1.06–1.53; P = 0.01).</p> <p>Conclusion/Significance</p><p>Hormone replacement therapy does not effect on the incidence of coronary events, myocardial infarction, cardiac death, total mortality or revascularization. However, it might contributed an important role on the risk of incident stroke.</p> </div

Subgroup analysis for the effect of hormone replacement therapy on coronary events, and stroke.

<p>Subgroup analysis for the effect of hormone replacement therapy on coronary events, and stroke.</p