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Advancements in remote sensing technology and very-large-scale integrated circuit (VLSI) have significantly augmented the real-time processing capabilities of spaceborne synthetic aperture radar (SAR), thereby enhancing terrestrial observational capacities. However, the inefficiency of voluminous data storage and transfer inherent in conventional methods has emerged as a technical hindrance, curtailing real-time processing within SAR imaging systems. To address the constraints of a limited storage bandwidth and inefficient data transfer, this study introduces a three-dimensional cross-mapping approach premised on the equal subdivision of sub-matrices utilizing dual-channel DDR3. This method considerably augments storage access bandwidth and achieves equilibrium in two-dimensional data access. Concurrently, an on-chip data transfer approach predicated on a superscalar pipeline buffer is proposed, mitigating pipeline resource wastage, augmenting spatial parallelism, and enhancing data transfer efficiency. Building upon these concepts, a hardware architecture is designed for the efficient storage and transfer of SAR imaging system data, based on the superscalar pipeline. Ultimately, a data storage and transfer engine featuring register addressing access, configurable granularity, and state monitoring functionalities is realized. A comprehensive imaging processing experiment is conducted via a "CPU + FPGA" heterogeneous SAR imaging system. The empirical results reveal that the storage access bandwidth of the proposed superscalar pipeline-based SAR imaging system's data efficient storage and transfer engine can attain up to 16.6 GB/s in the range direction and 20.0 GB/s in the azimuth direction. These findings underscore that the storage exchange engine boasts superior storage access bandwidth and heightened data storage transfer efficiency. This considerable enhancement in the processing performance of the entire "CPU + FPGA" heterogeneous SAR imaging system renders it suitable for application within spaceborne SAR real-time processing systems. [ABSTRACT FROM AUTHOR]

Plant-based dietary patterns may reduce the risk of dyslipidemia. However, not all plant-based foods are beneficial, and limited data exist for the Chinese population. We investigated the association between different plant-based dietary indices and the risk of dyslipidemia in a Chinese middle-aged and elderly population. The study participants (n = 4096) consisted of adults between 35 and 74 years of age from Xinjiang, China. Dietary consumption of the study participants was evaluated using a semi-quantitative food-frequency questionnaire (FFQ). Three different plant-based dietary indices were calculated using data from dietary surveys, including overall plant-based diet index (PDI), healthy plant-based diet index (hPDI), and unhealthy plant-based diet index (uPDI). Based on these indices, we created an adjusted plant-based diet index (aPDI) based on the Xinjiang population actual dietary behavior and health effects of food. We measured the levels of total cholesterol, triglyceride, LDL-C, and HDL-C in the blood of the study participants. We used multivariable logistic regression and restricted cubic spline to analyze the relationship between plant-based diets and dyslipidemia. The findings showed that 36.6% of the participants had dyslipidemia. Higher PDI adherence was related to lower odds of dyslipidemia (Q3 vs. Q1, OR: 0.780, 95% CI: 0.641–0.949; Q4 vs. Q1, OR: 0.799, 95% CI: 0.659–0.970). High aPDI was related to lower odds of dyslipidemia (Q4 vs. Q1, OR: 0.770, 95% CI: 0.628–0.945; Q5 vs. Q1, OR: 0.748, 95% CI: 0.607–0.921). High scores for PDI, hPDI, and aPDI were all related to a reduced risk of low HDL-C (OR: 0.638, 95% CI: 0.491–0.823; OR: 0.661, 95% CI: 0.502–0.870; OR: 0.580, 95% CI: 0.443–0.758). Conversely, a high uPDI score was associated with an increased risk of low HDL-C (OR: 1.349, 95% CI: 1.046–1.740). There was no non-linear relationship between PDI, hPDI, uPDI, and aPDI and the risk of different types of dyslipidemia. Plant-based dietary indices are related to specific types of dyslipidemia risk. Appropriately increasing the consumption of plant-based foods while improving the quality of plant-based dietary patterns is critical for the prevention of dyslipidemia, especially low HDL-C, in the population. [ABSTRACT FROM AUTHOR]

With the development of wireless Internet and the popularity of location sensors in mobile phones, the coupling degree between social networks and location sensor information is increasing. Many studies in the Location-Based Social Network (LBSN) domain have begun to use social media and location sensing information to implement personalized Points-of-interests (POI) recommendations. However, this approach may fall short when a user moves to a new district or city where they have little or no activity history and social network friend information. Thus, a need to reconsider how we model the factors influencing a user's preferences in new geographical regions in order to make personalized and relevant recommendation. A POI in LBSNs is semantically enriched with annotations such as place categories, tags, tips or user reviews which implies knowledge about the nature of the place as well as a visiting person's interests. This provides us with opportunities to better understand the patterns in users' interests and activities by exploiting the annotations which will continue to be useful even when a user moves to unfamiliar places. In this research, we proposed a location-aware POI recommendation system that models user preferences mainly based on user reviews, which shows the nature of activities that a user finds interesting. Using this information from users' location history, we predict user ratings by harnessing the information present in review text as well as consider social influence from similar user set formed based on matching category preferences and similar reviews. We use real data sets partitioned by city provided by Yelp, to compare the accuracy of our proposed method against some baseline POI recommendation algorithms. Experimental results show that our algorithm achieves a better accuracy. [ABSTRACT FROM AUTHOR]

The present study reports the reversing effects of extracts from P. americana on multidrug resistance of BEL-7402/5-FU cells, as well as a preliminary investigation on their mechanism of action. A methylthiazolyl tetrazolium (MTT) method was applied to determine the multidrug resistance of BEL-7402/5-FU, while an intracellular drug accumulation assay was used to evaluate the effects of a column chromatography extract (PACC) and defatted extract (PADF) from P. americana on reversing multi-drug resistance. BEL-7402/5-FU reflected high resistance to 5-FU; PACC and PADF could promote drug accumulation in BEL-7402/5-FU cells, among which PADF was more effective than PACC. Moreover, results from the immunocytochemical method showed that PACC and PADF could downregulate the expression of drug resistance-associated proteins (P-gp, MRP, LRP); PACC and PADF had no effects on the expression of multidrug resistance-associated enzymes (GST-π), but PACC could increase the expression of multidrug resistance-associated enzymes (PKC). Results of real-time fluorescence quantitative PCR revealed that PACC and PADF were able to markedly inhibit the expression of multidrug resistance-associated genes (MDR1, LRP and MRP1); PACC presented a significant impact on the gene expression of multidrug resistance-associated enzymes, which increased the gene expression of GST-π and PKC. However, PADF had little impact on the expression of multidrug resistance-associated enzymes. These results demonstrated that PACC and PADF extracted from P. americana could effectively reverse MDR in BEL-7402/5-FU cells, whose mechanism was to inhibit the expression of P-gp, MRP, and LRP, and that PADF was more effective in the reversal of MDR than did PACC. In addition, some of extracts from P. americana altered (sometimes increasing) the expression of multidrug resistance-associated enzymes.