32 research outputs found

    Effect of Dexmedetomidine Hydrochloride on Early Cognitive Function in Postoperative Elderly Patients

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    Purpose: to explore the effect of dexmedetomidine hydrochloride on early cognitive function in postoperative elderly patients. Methods: during December 2015 to November 2016, 80 elderly patients who received surgical treatment in our hospital were selected as research object. Result: patients were randomly divided into two groups (control group and research group). On the basis of routine anesthetic induction, patients in research group took dexmedetomidine, in comparison, patients in control group took an equal dose of sodium chloride solution. The goal was to evaluate the anesthetic effect of those two methods. One hour before surgery, there was no significant difference in the MMSE score between the two groups (P>0.05). In research group, the MMSE scores at postoperative 1d and 3d were (23.8 ± 2.4) and (27.1 ± 2.0) respectively. In control group, the MMSE scores at postoperative 1d and 3d were (20.5 ± 3.2) and (24.6 ± 3.4) respectively. The difference was statistically significant (P<0.05). There was no significant difference in anesthesia time, awake time and extubation time between those two groups (P>0.05). Conclusion: using dexmedetomidine in elderly patients after surgery can protect early cognitive function and improve the prognosis

    Transmitter Design for Uplink MIMO Systems With Antenna Correlation

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    CS-SAR Imaging Method Based on Inverse Omega-K Algorithm

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    Compressed Sensing (CS) has been proved to be effective in Synthetic Aperture Radar (SAR) imaging. Previous CS-SAR imaging algorithms are very time consuming, especially for producing high-resolution images. In this study, we propose a new CS-SAR imaging method based on the well-known omega-K algorithm, which is precise and convenient to use in SAR imaging. First, we derive an inverse omega-K algorithm to directly obtain echoes without any convolution between the transmitted signal and scene. Then, we formulate the SAR imaging problem into a sparse regularization problem and solve it using an iterative thresholding algorithm. With our derived inverse omega-K algorithm, we can save significant amounts of computation time and computer memory usage. Simulation results show that the proposed method can effectively recover SAR images with much less data than that required by the Nyquist rate

    Protective effects of lycopene on oxidative stress, proliferation and autophagy in iron supplementation rats

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    Lycopene is common in diet and known for its antioxidant activities. However, the impact of lycopene on iron metabolism is poorly investigated. In this study, we hypothesize that lycopene can prevent iron-mediated oxidative stress, proliferation and autophagy in liver and use a rat model of nutritional iron supplementation to confirm its intervention in these defence mechanisms. We found that iron supplementation induced cell proliferation predominantly in non parenchymal cells compared with hepatocytes, but not apoptosis. In addition, iron was accumulated within the hepatic lysosomes where it triggered autophagy as evidenced by the formation of autophagic vesicles detected by LC3-B staining. Iron supplementation also induced morphologic alterations of the mitochondrial membranes probably due to increased lipid peroxidation as indicated by elevated iron and malondialdehyde concentrations in serum and tissues. Lycopene reduced iron-catalyzed lipid peroxidation by decreasing the malondialdehyde level in the liver and colon and enhancing the total superoxide dismutase activities in serum and tissues. The result suggest that lycopene prevents iron-induced oxidative stress, proliferation and autophagy at both biochemical and histological levels due to its potent free radical scavenging and antioxidant properties

    Estimating and Assessing Monthly Water Level Changes of Reservoirs and Lakes in Jiangsu Province Using Sentinel-3 Radar Altimetry Data

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    Generating accurate monthly estimations of water level fluctuations in reservoirs and lakes is crucial for supporting effective water resource management and protection. The dual-satellite configuration of Sentinel-3 makes it possible to monitor water level changes with great coverage and short time intervals. However, the potential of Sentinel-3’s Synthetic Aperture Radar Altimetry (SRAL) data to enable operational monitoring of water levels across Jiangsu Province on a monthly basis has not yet been fully explored. This study demonstrated and validated the use of Sentinel-3’s SRAL to generate accurate monthly water level estimations needed to inform water management strategies. The monthly water levels of lakes and reservoirs from 2017 to 2021 were produced using Sentinel-3 level-2 land products. Results showed that, compared with in situ data across eight studied lakes, all lakes presented R (Pearson correlation coefficient) values greater than 0.5 and Root Mean Square Error (RMSE) values less than 1 m. Notably, water level estimates for Tai Lake, Gaoyou Lake, and Luoma Lake were particularly accurate, with R above 0.9 and RMSE below 0.5 m. Furthermore, the monthly water level estimates derived from the Sentinel-3 data showed consistent seasonal trends over the multi-year study period. The annual water level of all lakes did not change significantly, except for Shijiu Lake, of which the difference between the highest and lowest water level was up to about 5 m. Our findings confirmed the water level observation ability of Sentinel-3. The accuracy of water level monitoring could be influenced by internal water level differences, terrain features, as well as the area and shape of the lake. Larger lakes with more altimetry sampling points tended to yield higher accuracy estimates of water level fluctuations. These results demonstrate that the frequent, wide-area coverage offered by this satellite platform provides valuable hydrological information, especially across remote regions lacking in situ data. Sentinel-3 has immense potential to support improved water security in data-scarce regions

    Comparative transcriptional profiling of <i>Gracilariopsis lemaneiformis</i> in response to salicylic acid- and methyl jasmonate-mediated heat resistance

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    <div><p>Culturing the economically important macroalga <i>Gracilariopsis lemaneiformis</i> (Rhodophyta) is limited due to the high temperatures in the summertime on the southern Chinese coast. Previous studies have demonstrated that two phytohormones, salicylic acid (SA) and methyl jasmonate (MJ), can alleviate the adverse effects of high-temperature stress on <i>Gp</i>. <i>lemaneiformis</i>. To elucidate the molecular mechanisms underlying SA- and MJ-mediated heat tolerance, we performed comprehensive analyses of transcriptome-wide gene expression profiles using RNA sequencing (RNA-seq) technology. A total of 14,644 unigenes were assembled, and 10,501 unigenes (71.71%) were annotated to the reference databases. In the SA, MJ and SA/MJ treatment groups, 519, 830, and 974 differentially expressed unigenes were detected, respectively. Unigenes related to photosynthesis and glycometabolism were enriched by SA, while unigenes associated with glycometabolism, protein synthesis, heat shock and signal transduction were increased by MJ. A crosstalk analysis revealed that 216 genes were synergistically regulated, while 18 genes were antagonistically regulated by SA and MJ. The results indicated that the two phytohormones could mitigate the adverse effects of heat on multiple pathways, and they predominantly acted synergistically to resist heat stress. These results will provide new insights into how SA and MJ modulate the molecular mechanisms that counteract heat stress in algae.</p></div

    1-b Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers

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    In this paper, we propose a low-cost data acquisition approach for model extraction of digital predistortion (DPD) of RF power amplifiers. The proposed approach utilizes only 1-bit resolution analog-to-digital converters (ADCs) in the observation path to digitize the error signal between the input and output signals. The DPD coefficients are then estimated based on the direct learning architecture using the measured signs of the error signal. The proposed solution is proved to be feasible in theory and the experimental results show that the proposed algorithm achieves equivalent performance as that using the conventional method. Replacing high resolution ADCs with 1- bit comparators in the feedback path can dramatically reduce the power consumption and cost of the DPD system. The 1-bit solution also makes DPD become practically implementable in future broadband systems since it is relatively straightforward to achieve an ultra-high sampling speed in data conversion by using only simple comparators.Science Foundation IrelandNatural Science Foundation of Chin
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