Study of Ni Metallization in Macroporous Si Using Wet Chemistry for Radio Frequency Cross-Talk Isolation in Mixed Signal Integrated Circuits.

A highly conductive moat or Faraday cage of through-the-wafer thickness in Si substrate was proposed to be effective in shielding electromagnetic interference thereby reducing radio frequency (RF) cross-talk in high performance mixed signal integrated circuits. Such a structure was realized by metallization of selected ultra-high-aspect-ratio macroporous regions that were electrochemically etched in p- Si substrates. The metallization process was conducted by means of wet chemistry in an alkaline aqueous solution containing Ni2+ without reducing agent. It is found that at elevated temperature during immersion, Ni2+ was rapidly reduced and deposited into macroporous Si and a conformal metallization of the macropore sidewalls was obtained in a way that the entire porous Si framework was converted to Ni. A conductive moat was as a result incorporated into p- Si substrate. The experimentally measured reduction of crosstalk in this structure is 5~18 dB at frequencies up to 35 GHz

High-performance and Scalable Software-based NVMe Virtualization Mechanism with I/O Queues Passthrough

NVMe(Non-Volatile Memory Express) is an industry standard for solid-state drives (SSDs) that has been widely adopted in data centers. NVMe virtualization is crucial in cloud computing as it allows for virtualized NVMe devices to be used by virtual machines (VMs), thereby improving the utilization of storage resources. However, traditional software-based solutions have flexibility benefits but often come at the cost of performance degradation or high CPU overhead. On the other hand, hardware-assisted solutions offer high performance and low CPU usage, but their adoption is often limited by the need for special hardware support or the requirement for new hardware development. In this paper, we propose LightIOV, a novel software-based NVMe virtualization mechanism that achieves high performance and scalability without consuming valuable CPU resources and without requiring special hardware support. LightIOV can support thousands of VMs on each server. The key idea behind LightIOV is NVMe hardware I/O queues passthrough, which enables VMs to directly access I/O queues of NVMe devices, thus eliminating virtualization overhead and providing near-native performance. Results from our experiments show that LightIOV can provide comparable performance to VFIO, with an IOPS of 97.6%-100.2% of VFIO. Furthermore, in high-density VMs environments, LightIOV achieves 31.4% lower latency than SPDK-Vhost when running 200 VMs, and an improvement of 27.1% in OPS performance in real-world applications

Estimation of ground-level PM2.5 concentration using MODIS AOD and corrected regression model over Beijing, China.

To establish a new model for estimating ground-level PM2.5 concentration over Beijing, China, the relationship between aerosol optical depth (AOD) and ground-level PM2.5 concentration was derived and analysed firstly. Boundary layer height (BLH) and relative humidity (RH) were shown to be two major factors influencing the relationship between AOD and ground-level PM2.5 concentration. Thus, they are used to correct MODIS AOD to enhance the correlation between MODIS AOD and PM2.5. When using corrected MODIS AOD for modelling, the correlation between MODIS AOD and PM2.5 was improved significantly. Then, normalized difference vegetation index (NDVI), surface temperature (ST) and surface wind speed (SPD) were introduced as auxiliary variables to further improve the performance of the corrected regression model. The seasonal and annual average distribution of PM2.5 concentration over Beijing from 2014 to 2016 were mapped for intuitively analysing. Those can be regarded as important references for monitoring the ground-level PM2.5 concentration distribution. It is obviously that the PM2.5 concentration distribution over Beijing revealed the trend of "southeast high and northwest low", and showed a significant decrease in annual average PM2.5 concentration from 2014 to 2016

Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang

Planting with non-film mulching is the fundamental means to eliminate the pollution of residual film in cotton fields. However, this planting approach should have regional adaptability. Therefore, the calibrated WOFOST model and an early mature cultivar CRI619 (Gossypium hirsutum Linn) were employed to simulate the cotton growth, and regions were then evaluated for planting in Xinjiang. A field experiment was conducted in 2019–2020 at the experimental irrigation station of Alar City, and the data were used to calibrate and validate the WOFOST model. The field validation results showed that the errors of the WOFOST simulation for emergence, flowering, and maturity were +1 day, +2 days, and +1 day, respectively, with good simulation accuracy of phenological development time. The simulated WLV, WST, WSO, and TAGP agreed well with measured values, with R2 = 0.96, 0.97, 0.99, and 0.99, respectively. The RMSE values of simulated versus measured WLV, WST, WSO, and TAGP were 175, 210, 199, and 251 kg ha−1, and showed high accuracy. The simulated soil moisture (SM) agreed with the measured value, with R2 = 0.87. The calibration model also showed high SM simulation accuracy, with RMSE = 0.022 (cm3 cm−3). Under all treatments, the simulated TAGP and yield agreed well with the measured results, with R2 of 0.76 and 0.70, respectively. RMSE of simulated TAGP and yield was 465 and 200 kg ha−1, and showed high accuracy. The percentage RMSE values (ratio of RMSE to the average measured value, NRMSE) of ETa and WUE were 9.8% and 11.7%, indicating extremely high precision (NRMSE < 10%) and high precision (10% < NRMSE ≤ 20%), respectively. The simulated results for phenology length at the regional scales showed that the effective accumulation temperature in counties such as Yingjisha and Luntai was not enough for the phenological maturity of the studied cotton cultivar. The southern area of Xinjiang had a generally higher yield than the northern area but required more irrigation. This research can provide a method for evaluating the adaptability of filmless cultivation techniques for cotton in different counties

Progressive Difference Amplification Network With Edge Sensitivity for Remote Sensing Image Change Detection

Capturing finer and discriminative difference features (DFs) is key to obtaining a high-quality change detection (CD) map. However, there is still significant scope for further study on fine-grained detection, especially concerning terms of improving structural integrity and reducing internal holes or sticking in DF. To this end, we propose a progressive difference amplification network (PDANet) with edge sensitivity to detect changed areas in optical remote sensing images (RSIs), where the key point is to amplify DF and reinforce edge detail to improve CD accuracy. The edge sensitivity (ES) encoder is designed to capture the long-distance dependency, which compensates for the limited receptive fields of the convolutional neural network with fixed kernels. Meanwhile, we introduce the prior edge in the network training stage, which collaborates with the ESE to improve the structural integrity of the changed areas. On the other hand, the difference amplification decoder is proposed to enhance the representation of the changed areas, and it is achieved by integrating multiscale DF and reconstructing the original single RSI using DF as full-stage guidance. Finally, the CD map and edge map are predicted based on the reconstructed feature and the maximum scale DF. Extensive experiments on one instance dataset and three CD benchmark datasets demonstrate that PDANet outperforms the state-of-the-art CD competitors both qualitatively and quantitatively

Dietary sodium/potassium intake and cognitive impairment in older patients with hypertension: Data from NHANES 2011–2014

Abstract This study aimed to assess the relationship between dietary sodium/potassium intake and cognition in elderly individuals with hypertension. We designed a cross‐sectional study based on the 2011–2014 National Health and Nutrition Examination Survey (NHANES) 2011–2014. A multivariable‐logistic regression analysis was performed to analyze the relationship between sodium/potassium intake and cognitive impairment. Restricted cubic spline (RCS) based on regression analysis to assess the nonlinear dose‐response relationship between dietary sodium intake and cognitive performance. Out of the 2276 participants included in this study, 1670 patients had hypertension. Compared with the lowest quartile of dietary sodium intake, the lowest weighted odds ratio of cognitive impairment in DSST was observed in Q4 (OR = 0.45, 0.29–0.70), and a similar trend was observed in AFT (OR = 0.34, 0.18–0.65). After adjusting the covariates, the lowest weighted multivariable‐adjusted OR of cognitive impairment in DSST were also observed in Q4 (OR = 0.47, 0.26‐0.84) compared with the lowest quartile of dietary sodium intake. The RCS results showed that dietary sodium intake was U‐shaped and associated with the risk of cognitive impairment in the DSST (Pnon–linearity = 0.0067). In addition, no significant association was observed between dietary potassium intake and different dimensions of cognitive performance. In conclusion, excessively high and low low dietary sodium were associated with impairment of specific processing speed, sustained attention, and working memory for elderly patients with hypertension in the United States. However, no association was observed between dietary potassium intake and cognition

Study of Ni Metallization in Macroporous Si Using Wet Chemistry for Radio Frequency Cross-Talk Isolation in Mixed Signal Integrated Circuits.

A highly conductive moat or Faraday cage of through-the-wafer thickness in Si substrate was proposed to be effective in shielding electromagnetic interference thereby reducing radio frequency (RF) cross-talk in high performance mixed signal integrated circuits. Such a structure was realized by metallization of selected ultra-high-aspect-ratio macroporous regions that were electrochemically etched in p- Si substrates. The metallization process was conducted by means of wet chemistry in an alkaline aqueous solution containing Ni2+ without reducing agent. It is found that at elevated temperature during immersion, Ni2+ was rapidly reduced and deposited into macroporous Si and a conformal metallization of the macropore sidewalls was obtained in a way that the entire porous Si framework was converted to Ni. A conductive moat was as a result incorporated into p- Si substrate. The experimentally measured reduction of crosstalk in this structure is 5~18 dB at frequencies up to 35 GHz