Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P \u3c 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies

Geometric measure of quantum discord and the geometry of a class of two-qubit states

We investigate the geometric picture of the level surfaces of quantum entanglement and geometric measure of quantum discord (GMQD) of a class of X-states, respectively. This pictorial approach provides us a direct understanding of the structure of entanglement and GMQD. The dynamic evolution of GMQD under two typical kinds of quantum decoherence channels is also investigated. It is shown that there exists a class of initial states for which the GMQD is not destroyed by decoherence in a finite time interval. Furthermore, we establish a factorization law between the initial and final GMQD, which allows us to infer the evolution of entanglement under the influences of the environment.Comment: 10 pages, 4 figures, comments are welcom

A CBAM‐GAN‐based method for super‐resolution reconstruction of remote sensing image

Abstract As satellite imagery technology advances, remote sensing plays an increasingly prominent role in modern society. Nevertheless, the limitations of existing imaging sensors and complex atmospheric conditions constrain the quality of raw remote sensing data, posing challenges for interpretation and noise reduction. Super‐resolution technology focuses on enhancing low‐quality, low‐resolution remote sensing images. In this study, we introduce a method that utilizes a high‐order degradation model to generate low‐resolution remote sensing images. We employ a Generative Adversarial Network with a Convolutional Block Attention Module (CBAM‐GAN) to enhance these images, reducing noise interference and improving texture and feature display. Our approach outperforms other methods on the UCMerced‐LandUse, WHU‐RS19, and AID datasets. Specifically, it raises SSIM index scores to 0.9443, 0.8928, and 0.8633, respectively, exceeding baselines by 1.31%, 0.19%, and 1.30%. The MOS index also improves to 3.98, 3.96, and 3.83, respectively, representing a 2.31%, 8.20%, and 2.96% gain over the baseline. Our reconstruction produces superior results, demonstrating the effectiveness of our proposed method

A Hybrid Genetic/Powell Algorithm for Wind Measurement in Doppler Lidar

Doppler peaks extraction from massive raw data is a tricky part of coherent Doppler wind Lidar (CDWL) optimization. In this paper, a hybrid genetic/Powell algorithm (HGAP) is proposed to process the power spectrum of the measured signal from CDWL. The HGAP has excellent global exploration capability, which likes traditional genetic algorithms and fast convergence, which like the Powell method. Hence, the HGAP has advantages to find the center frequency of the Doppler peaks from massive raw data, especially to search multiple peaks in complex wind field measurement. Compared with other notable algorithms, the HGAP shows excellent performance in numerical optimization when we use it to solve 27 typical benchmark functions. Then, our algorithm is used to process the raw data in a field experiment of radial wind measurement. The results show that the HGAP can obtain wind speed components quickly and accurately and has value for application in complex wind field analysis

A Hybrid Genetic/Powell Algorithm for Wind Measurement in Doppler Lidar

Doppler peaks extraction from massive raw data is a tricky part of coherent Doppler wind Lidar (CDWL) optimization. In this paper, a hybrid genetic/Powell algorithm (HGAP) is proposed to process the power spectrum of the measured signal from CDWL. The HGAP has excellent global exploration capability, which likes traditional genetic algorithms and fast convergence, which like the Powell method. Hence, the HGAP has advantages to find the center frequency of the Doppler peaks from massive raw data, especially to search multiple peaks in complex wind field measurement. Compared with other notable algorithms, the HGAP shows excellent performance in numerical optimization when we use it to solve 27 typical benchmark functions. Then, our algorithm is used to process the raw data in a field experiment of radial wind measurement. The results show that the HGAP can obtain wind speed components quickly and accurately and has value for application in complex wind field analysis

Controlled Release of BMP‑2 from a Heparin-Conjugated Strontium-Substituted Nanohydroxyapatite/Silk Fibroin Scaffold for Bone Regeneration

The objective of this study was to develop heparin-conjugated strontium-substituted hydroxyapatite/silk fibroin (Sr-nHAp/SF-Hep) scaffold loaded bone morphogenetic proteins-2 (BMP-2) with sustained release to improve bone regeneration. The average pore diameters and porosity of Sr-nHAp/SF scaffolds were respectively approximately 150 μm and 90%. The mechanical properties and thermostability of the Sr-nHAp/SF scaffolds were significantly stronger than those of the SF scaffold. The weight of composite scaffolds is higher than that of the SF scaffold in simulated body fluids. The Sr-nHAp/SF scaffold exhibited excellent biological function of bone marrow mesenchymal stem cell (BMSC) proliferation and adhesion. The expression of related osteogenic genes, including osteocalcin, osteopontion, and alkaline phosphatase activity was elevated by Sr-nHAp/SF-Hep-BMP-2 scaffold, which promoted the differentiation of BMSCs into osteoblasts. <i>In vivo</i> results showed that Sr-nHAp/SF-Hep-BMP-2 scaffolds enhanced bone mineral density and improved new bone regeneration, which was accomplished through microcomputed tomography (micro-CT) and histological and histochemical staining analysis. These results demonstrated Sr-nHAp/SF-Hep-BMP-2 scaffolds with favorable biocompatibility and good mechanical properties have great potential to repair bone defects