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In view of the current debate about the relationship between lipids and deep venous thrombosis (DVT) in clinical studies, a two-sample Mendelian randomization (MR) study was conducted to clarify the effects of five circulating lipids (apolipoprotein A1, apolipoprotein B, low-density lipoprotein, high-density lipoprotein and triglycerides) on DVT from the perspective of genetic inheritance. Five lipids (exposure) were analysed by MR with DVT (outcome) from two different data sources. For the analysis, we used inverse variance weighting and a weighted mode, weighted median, simple mode and MR–Egger regression to analyse the effect of circulating lipids on DVT. In addition, we used the MR–Egger intercept test, Cochran’s Q test and “leave-one-out” sensitivity analysis to evaluate horizontal multiplicity, heterogeneity and stability, respectively, in the analysis. In the analysis, the two-sample Mendelian randomization analysis of five common circulating lipids and DVT showed that common circulating lipids had no causal effect on DVT, which is somewhat inconsistent with the findings of many published observational studies. Based on our results, our two-sample MR analysis failed to detect a statistically significant causal relationship between five common circulating lipids and DVT.

Background:Current knowledge of the nature and treatment of knee osteoarthritis (KOA) have shown that an effective prevention strategy and treatment to identify and avoid risk factors in the early stage of KOA are required. Therefore, we hope to be able to determine some modifiable risk factors for KOA through MR analysis from a genetically informed perspective to achieve early prevention to reduce the prevalence of KOA in the population. Methods: In our research, we used a series of quality control steps to identify eligible instrumental SNPs that were strongly related to exposure. We used numerous dependable analytical methods (Inverse-variance weighting, MR-PRESSO method, weighted median, MR–Egger regression, and MR. RAPS method) that consist of two MR extrapolation hypotheses to make our conclusions more robust and credible. The MR–Egger intercept test, Cochran’s Q test, and “leave-one-out” sensitivity analysis were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on KOA. Outlier variants identified by the MR-PRESSO outlier test were removed step-by-step to reduce heterogeneity and the effect of horizontal pleiotropy. Results: Through Two- sample MR analysis, we found that there was a causal relationship between obesity and KOA, and obesity was positively correlated with the incidence of KOA (IVW: beta (95% CI), 0.144 (0.089, 0.199); OR (95% CI) 1.155 (1.093, 1.221); p =3.09e-7). The genetic predisposition to smoking was associated with a decreased risk of KOA (IVW: beta (95% CI), 0.178 (0.045, 0.311); OR (95% CI), 1.195 (1.046, 1.365); p =0.008). Based on the IVW model, there was a causal relationship between alcohol consumption and KOA (IVW: beta (95% CI), 0.347 (0.003, 0.692); OR (95% CI) 1.416 (1.003, 1.998); p =0.047). Conclusion: Our two-sample MR analysis confirmed that some controllable risk factors (smoking, drinking and obesity) can lead to KOA from a genetic point of view, which provides an important clue for the prevention and treatment of KOA.

Graphene has attracted a lot of attention in gas sensing applications for its high surface area ratio and unique chemical or physical gas adsorption ability. Being an important research method, theoretical calculations play a key role in both illustrating the gas sensing mechanism of graphene and improving the gas sensing performance of graphene-based sensors. This review discusses the application of adsorption isotherm theory and first-principles studies to graphene gas sensors. Different isotherm theories are presented, including Langmuir, Freundlich, BET, and Temkin isotherm models, and it is illustrated how to investigate the adsorption information from them. The first-principles analysis of graphene-based gas sensors is presented. In general, doping with transition metals and nonmetals can improve the sensitivity of graphene to gases. This review shows the significance of using theoretical calculations to design novel and efficient gas sensors. The theoretical results obtained so far can be of great help in designing novel and efficient graphene-based gas sensors.

The linearity of synaptic plasticity of single-walled carbon nanotube field-effect transistor (SWCNT FET) was improved by CdSe quantum dots decoration. The linearity of synaptic plasticity in SWCNT FET with decorating QDs was further improved by reducing the P-type doping level from the atmosphere. The synaptic behavior of SWCNT FET is found to be dominated by the charging and discharging processes of interface traps and surface traps, which are predominantly composed of H2O/O2 redox couples. The improved synaptic behavior is mainly due to the reduction of the interface trap charging process after QDs decoration. The inherent correlation between the device synaptic behavior and the electron capture process of the traps are investigated through charging-based trap characterization. This study provides an effective scheme for improving linearity and designing new-type SWCNT synaptic devices.

This paper introduces a kind of timing adaptive corrected circuit, which quantifies the phase between data generating clock and sampling clock, compares the current phase with the target phase that meets the timing requirement, adjusts the delay of one clock based on the comparison results, and changes the current phase, forms a negative feedback loop. This technique allows the sampling timing to be always met and also compensates for sampling timing changes caused by changes in the external environment, thus achieving data transfer and synchronization at high speed. In the post-simulation the inputs are two 5GHz clocks with 0° initial phase, after the loop is stabilized, the phase between the two output clocks is locked to 90° to meet the target phase.

This paper describes a 16-bit 5GSPS high-speed DAC with segmented R2R load, using a 65nm CMOS process, and consists of a SERDES receiver, a high-speed thermometer decoder, a high-speed MUX, a high-speed data latch, a DAC core, and so on. Through the R2R load to ensure that the current density of each pair of switch is the same. The same drive unit is used for the switch input stage, which ensures that the switch changes at the same time. Switching simultaneously can improve the dynamic performance of the high speed DAC. In this paper measured performance of greater than 65 dBc SFDR is achieved at 500 MHz output signal.

Silicided-Polysilicon fuses are programmable nonvolatile memory elements which are widely used on wafer. In this paper a simple and efficient fuse-trimming circuit is presented. The circuit is based on match-design concept, which can be easily implemented, and there are no needs of high blowing voltage or precise control of the voltage-pulse parameters such as width or fall-time. It has high efficiency in fuse-trimming, and is insensitive to the resistance of the post-trimming fuse. The robustness of the circuit has been discussed. Application of the circuit in a high performance 14-Bit DAC based on the 0.25um CMOS process technology also has been demonstrated.

This paper describes a high linearity and high resolution semi-digital delay-locked loop (DLL) architecture using a multiphase generator and a phase rotator to get infinite phase capture range, in the meanwhile using current interpolation to obtain high linearity and high resolution. The multiphase generator generates quadrature clocks for the phase rotator instead of a delay line. Thus the phase capture range will change with the changing of input clock rate. An infinite phase capture range can be achieved. The current interpolation is used to eliminate the drawbacks of quadrature phase mixing. The results of simulation show that this semidigital DLL architecture exhibits 7 picosecond resolution and high linearity at 1.25GHz.