A study on the high power microwave effects of PIN diode limiter based on deep learning algorithm.

PIN diodes, due to their simple structure and variable resistance characteristics under high-frequency high-power excitation, are often used in radar front-end as limiters to filter high power microwaves (HPM) to prevent its power from entering the internal circuit and causing damage. This paper carries out theoretical derivation and research on the HPM effects of PIN diodes, and then uses an optimized neural network algorithm to replace traditional physical modeling to calculate and predict two types of HPM limiting indicators of PIN diode limiters. We proposes a neural network model for each of the following two prediction scenarios: in the scenario of time-junction temperature curves under different HPM irradiation, the weighted mean squared error (MSE) between the predicted values from the test dataset and the simulated values is below 0.004. While in predicting PIN limiter's power limitation threshold, insertion loss, and maximum isolation under different HPM irradiation, the MSE of the test set prediction values and simulation values are all less than 0.03. The method proposed in this research, which applies an optimized neural network algorithm to replace traditional physical modeling algorithms for studying the high-power microwave effects of PIN diode limiters, significantly improves the computational and simulation speed, reduces the calculation cost, and provides a new method for studying the high-power microwave effects of PIN diode limiters.

Prediction of electrical properties of GAAFET based on integrated learning model.

As device feature sizes continue to decrease and fin field effect transistors reach their physical limits, gate all around field effect transistors (GAAFETs) have emerged with larger gate control areas and stackable characteristics for better suppression of second-order effects such as short-channel effects due to their gate encircling characteristics. Traditional methods for studying the electrical characteristics of devices are mostly based on the technology computer-aided design. Still, it is not conducive to developing new devices due to its time-consuming and inefficient drawbacks. Deep learning (DL) and machine learning (ML) have been well-used in recent years in many fields. In this paper, we propose an integrated learning model that integrates the advantages of DL and ML to solve many problems in traditional methods. This integrated learning model predicts the direct current characteristics, capacitance characteristics, and electrical parameters of GAAFET better than those predicted by DL or ML methods alone, with a linear regression factor (R2) greater than 0.99 and very small root mean square error. The proposed integrated learning model achieves fast and accurate prediction of GAAFET electrical characteristics, which provides a new idea for device and circuit simulation and characteristics prediction in microelectronics.

Correction: Systemic Delivery of MicroRNA-101 Potently Inhibits Hepatocellular Carcinoma In Vivo by Repressing Multiple Targets.

[This corrects the article DOI: 10.1371/journal.pgen.1004873.].

A high performance trench gate tunneling field effect transistor based on quasi-broken gap energy band alignment heterojunction.

In this letter, a tunneling field effect transistor based on quasi-broken gap energy band alignment (QB-TFET) is proposed and investigated by simulation method. To offering high on-state current, InGaAs/GaAsSb heterojunction with quasi-broken gap energy band alignment is applied to QB-TFET to improve the band-to-band tunneling rate. Trench gate structure and InGaAs pocket layer are applied to further increase the tunneling efficiency. To suppress the leakage current caused by the off-state tunneling path from source to drain, an intrinsic InGaAs spacer is inserted between n+ InGaAs drain and p+ GaAsSb source. In order to further improve the control ability of gate voltage on channel, TiO2is used as the gate dielectric of the proposed QB-TFET. Moreover, the effect ofxandyfraction of InxGa1-xAs and GaAsySb1-yon quasi-broken gap tunneling junction are studied in this work. The electrical characteristic change of QB-TFET with differentxandyfraction is analyzed. The proposed QB-TFET is compared with other works and shows an obvious advantage on performance. As a result, a large on-state current (Ion) of 921µAµm-1can be obtained. Moreover, steep average subthreshold swing (SSavg) of 4.9 mV/dec can be achieved whenIon = 1µAµm-1.

Prediction of electrical properties of FDSOI devices based on deep learning.

Fully depleted Silicon on insulator technology (FDSOI) is proposed to solve the various non-ideal effects when the process size of integrated circuits is reduced to 45 nm. The research of traditional FDSOI devices is mostly based on simulation software, which requires a lot of calculation and takes a long time. In this paper, a deep learning (DL) based electrical characteristic prediction method for FDSOI devices is proposed. DL algorithm is used to train the simulation data and establish the relationship between the physical parameters and electrical characteristics of the device. The network structure used in the experiment has high prediction accuracy. The mean square error of electrical parameters and transfer characteristic curve is only 4.34 × 10-4and 2.44 × 10-3respectively. This method can quickly and accurately predict the electrical characteristics of FDSOI devices without microelectronic expertise. In addition, this method can be extended to study the effects of various physical variables on device performance, which provides a new research method for the field of microelectronics.

Single event effects prediction of MOSFET device using deep learning.

Single event effect (SEE) is an important problem in the reliability research of integrated circuits. The study of SEE of traditional MOSFET devices is mainly based on simulation software, which is characterized by slow simulation speed, large computation and time-consuming. In this paper, a SEE research method based on deep learning is proposed. The method relies on 28 nm MOSFET. The complete drain transient current pulse, transient current peak value and total collected charge can be obtained in a short time by inputting relevant parameters that affect the SEE. The accuracy of the network for predicting transient current peak and total collected charge is 96.95% and 97.53% respectively, and the mean goodness of fit of the network for predicting the drain transient current pulse curve is 0.985. Compared with TCAD Sentaurus software, the simulation speed is increased by 5.89 × 103and 1.50 × 103times respectively. This method has good prediction effect and provides a new possibility for the study of SEE.

MR-based synthetic CT image for intensity-modulated proton treatment planning of nasopharyngeal carcinoma patients.

PURPOSE: To develop an advanced deep convolutional neural network (DCNN) architecture to generate synthetic CT (SCT) images from MR images for intensity-modulated proton therapy (IMPT) treatment planning of nasopharyngeal cancer (NPC) patients. METHODS: T1-weighted MR images and paired CT (PCT) images were obtained from 206 NPC patients. For each patient, deformable image registration was performed between MR and PCT images to create an MR-CT image pair. Thirty pairs were randomly chosen as the independent test set and the remaining 176 pairs (14 for validation and 162 for training) were used to build two conditional generative adversarial networks (GANs): 1) GAN3D: using a 3D U-net enhanced with residual connections and attentional mechanism as the generator and 2) GAN2D: using a 2D U-net as the generator. For each test patient, SCT images were generated using the generators with the MR images as input and were compared with respect to the corresponding PCT image. A clinical IMPT plan was created and optimized on the PCT image. The dose was recalculated on the SCT images and compared with the one calculated on the PCT image. RESULTS: The mean absolute errors (MAEs) between the PCT and SCT, within the body, were (64.89 ± 5.31) HU and (64.31 ± 4.61) HU for the GAN2D and GAN3D. Within the high-density bone (HU > 600), the GAN3D achieved a smaller MAE compared with the GAN2D (p < 0.001). Within the body, the absolute point dose deviation was reduced from (0.58 ± 1.61) Gy for the GAN2D to (0.47 ± 0.94) Gy for the GAN3D. The (3 mm/3%) gamma passing rates were above 97.32% for all SCT images. CONCLUSIONS: The SCT images generated using GANs achieved clinical acceptable dosimetric accuracy for IMPT of NPC patients. Using advanced DCNN architecture design, such as residual connections and attention mechanism, SCT image quality was further improved and resulted in a small dosimetric improvement.

Synthesis and Spectral Characteristics Investigation of the 2D-2D vdWs Heterostructure Materials.

Due to the attractive optical and electrical properties, van der Waals (vdWs) heterostructures constructed from the different two-dimensional materials have received widespread attention. Here, MoS2/h-BN, MoS2/graphene, WS2/h-BN, and WS2/graphene vdWs heterostructures are successfully prepared by the CVD and wet transfer methods. The distribution, Raman and photoluminescence (PL) spectra of the above prepared heterostructure samples can be respectively observed and tested by optical microscopy and Raman spectrometry, which can be used to study their growth mechanisms and optical properties. Meanwhile, the uniformity and composition distribution of heterostructure films can also be analyzed by the Raman and PL spectra. The internal mechanism of Raman and PL spectral changes can be explained by comparing and analyzing the PL and Raman spectra of the junction and non-junction regions between 2D-2D vdWs heterostructure materials, and the effect of laser power on the optical properties of heterostructure materials can also be analyzed. These heterostructure materials exhibit novel and unique optical characteristics at the stacking or junction, which can provide a reliable experimental basis for the preparation of suitable TMDs heterostructure materials with excellent performance.

Effects of subchronic exposure of mercuric chloride on intestinal histology and microbiota in the cecum of chicken.

This study aimed to investigate the influences of mercuric chloride (HgCl2, 250 ppm, drink water) on the growth performance, cecal morphology and microbiota of chickens (n = 60) after 30, 60, and 90 days of exposure. A control group of sixty chickens received water free of HgCl2. Our results suggested that mercury exposure reduced the body weight and changed the cecal morphology of chickens after the 90-day treatment. Furthermore, sequence analysis of 16 S rRNA gene revealed that the diversity and composition of cecal microbiota in chickens differed between the control and exposure group. At the phylum level, Proteobacteria and Tenericutes phyla both significantly increased in mercury exposure groups on day 30 while only Tenericutes phyla significantly increased on day 60. At the genus level, we observed that the change in microbial populations are most dramatic on day 30. Besides, compared with the control group, the genus Prevotellaceae_UCG-001 significantly increased in exposure group on day 30 but showed no significant difference on day 60, whereas there was a significant decrease on day 90. PICRUSt analysis revealed potential metabolic changes, such as Bacterial invasion of epithelial cells and Metabolism of xenobiotics, associated with mercury exposure in chickens. Taken together, the data show that subchronic exposure to mercury not only affected the growth and development but also caused the dysbiosis of gut microbiota, which may further induced metabolic disorders in chickens.

The Large-Scale Preparation and Optical Properties of MoS2/WS2 Vertical Hetero-Junction.

A variety of hetero-junctions can be constructed to form the basic structural units in the different optoelectronic devices, such as the photo-detectors, solar cells, sensors and light-emitting diodes. In our research, the large-area high-quality MoS2/WS2 vertical hetero-junction are prepared by the two-step atmospheric pressure chemical vapor deposition (APCVD) methods and the dry transfer method, and the corresponding optimal reaction conditions of MoS2/WS2 vertical hetero-junction are obtained. The morphology, composition and optical properties of MoS2/WS2 vertical hetero-junction are systematically characterized by the optical microscopy, Raman spectroscopy, photoluminescence spectroscopy, atomic force microscopy and the field emission scanning electron microscopy. Compared to the mechanical transfer method, the MoS2/WS2 vertical hetero-junction sample obtained by the APCVD and dry transfer methods have lower impurity content, cleaner interfaces and tighter interlayer coupling. Besides, the strong interlayer coupling and effective interlayer charge transfer of MoS2/WS2 vertical hetero-junction are also further studied. The photoluminescence intensity of MoS2/WS2 vertical hetero-junction is significantly reduced compared to the single MoS2 or WS2 material. In general, this research can help to achieve the large-scale preparation of various Van der Waals hetero-junctions, which can lay the foundation for the new application of optoelectronic devices.

Chemotherapeutic drugs stimulate the release and recycling of extracellular vesicles to assist cancer cells in developing an urgent chemoresistance.

BACKGROUND: Chemotherapy is a widely used treatment for cancer. However, the development of acquired multidrug resistance (MDR) is a serious issue. Emerging evidence has shown that the extracellular vesicles (EVs) mediate MDR, but the underlying mechanism remains unclear, especially the effects of chemotherapeutic agents on this process. METHODS: Extracellular vesicles isolation was performed by differential centrifugation. The recipient cells that acquired ATP-binding cassette sub-family B member 1 (ABCB1) proteins were sorted out from co-cultures according to a stringent multi-parameter gating strategy by fluorescence-activated cell sorting (FACS). The transfer rate of ABCB1 was measured by flow cytometry. The xenograft tumor models in mice were established to evaluate the transfer of ABCB1 in vivo. Gene expression was detected by real-time PCR and Western blotting. RESULTS: Herein, we show that a transient exposure to chemotherapeutic agents can strikingly increase Rab8B-mediated release of extracellular vesicles (EVs) containing ABCB1 from drug-resistant cells, and accelerate these EVs to circulate back onto plasma membrane of sensitive tumor cells via the down-regulation of Rab5. Therefore, intercellular ABCB1 transfer is significantly enhanced; sensitive recipient cells acquire a rapid but unsustainable resistance to evade the cytotoxicity of chemotherapeutic agents. More fascinatingly, in the xenograft tumor models, chemotherapeutical drugs also locally or distantly increase the transfer of ABCB1 molecules. Furthermore, some Non-small-cell lung carcinoma (NSCLC) patients who are undergoing primary chemotherapy have a rapid increase of ABCB1 protein in their monocytes, and this is obviously associated with poor chemotherapeutic efficacy. CONCLUSIONS: Chemotherapeutic agents stimulate the secretion and recycling of ABCB1-enriched EVs through the dysregulation of Rab8B and Rab5, leading to a significant increase of ABCB1 intercellular transfer, thus assisting sensitive cancer cells to develop an urgent resistant phenotype. Our findings provide a new molecular mechanism of how chemotherapeutic drugs assist sensitive cancer cells in acquiring an urgent resistance.

Systemic delivery of microRNA-101 potently inhibits hepatocellular carcinoma in vivo by repressing multiple targets.

Targeted therapy based on adjustment of microRNA (miRNA)s activity takes great promise due to the ability of these small RNAs to modulate cellular behavior. However, the efficacy of miR-101 replacement therapy to hepatocellular carcinoma (HCC) remains unclear. In the current study, we first observed that plasma levels of miR-101 were significantly lower in distant metastatic HCC patients than in HCCs without distant metastasis, and down-regulation of plasma miR-101 predicted a worse disease-free survival (DFS, P<0.05). In an animal model of HCC, we demonstrated that systemic delivery of lentivirus-mediated miR-101 abrogated HCC growth in the liver, intrahepatic metastasis and distant metastasis to the lung and to the mediastinum, resulting in a dramatic suppression of HCC development and metastasis in mice without toxicity and extending life expectancy. Furthermore, enforced overexpression of miR-101 in HCC cells not only decreased EZH2, COX2 and STMN1, but also directly down-regulated a novel target ROCK2, inhibited Rho/Rac GTPase activation, and blocked HCC cells epithelial-mesenchymal transition (EMT) and angiogenesis, inducing a strong abrogation of HCC tumorigenesis and aggressiveness both in vitro and in vivo. These results provide proof-of-concept support for systemic delivery of lentivirus-mediated miR-101 as a powerful anti-HCC therapeutic modality by repressing multiple molecular targets.

A feasibility study of intrafractional tumor motion estimation based on 4D-CBCT using diaphragm as surrogate.

PURPOSE: To investigate the intrafractional stability of the motion relationship between the diaphragm and tumor, as well as the feasibility of using diaphragm motion to estimate lung tumor motion. METHODS: Eighty-five paired (pre and posttreatment) daily 4D-CBCT images were obtained from 20 lung cancer patients who underwent SBRT. Bony registration was performed between the pre- and post-CBCT images to exclude patient body movement. The end-exhalation phase image of the pre-CBCT image was selected as the reference image. Tumor positions were obtained for each phase image using contour-based translational alignments. Diaphragm positions were obtained by translational alignment of its apex position. A linear intrafraction model was constructed using regression analysis performed between the diaphragm and tumor positions manifested on the pretreatment 4D-CBCT images. By applying this model to posttreatment 4D-CBCT images, the tumor positions were estimated from posttreatment 4D-CBCT diaphragm positions and compared with measured values. A receiver operating characteristic (ROC) test was performed to determine a suitable indicator for predicting the estimate accuracy of the linear model. RESULTS: Using the linear model, per-phase position, mean position, and excursion estimation errors were 1.12 ± 0.99 mm, 0.97 ± 0.88 mm, and 0.79 ± 0.67 mm, respectively. Intrafractional per-phase tumor position estimation error, mean position error, and excursion error were within 3 mm 95%, 96%, and 99% of the time, respectively. The residual sum of squares (RSS) determined from pretreatment images achieved the largest prediction power for the tumor position estimation error (discrepancy < 3 mm) with an Area Under ROC Curve (AUC) of 0.92 (P < 0.05). CONCLUSION: Utilizing the relationship between diaphragm and tumor positions on the pretreatment 4D-CBCT image, intrafractional tumor positions were estimated from intrafractional diaphragm positions. The estimation accuracy can be predicted using the RSS obtained from the pretreatment 4D-CBCT image.

CD133+ liver cancer stem cells resist interferon-gamma-induced autophagy.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most fatal malignancies worldwide, and CD133 is a popular cancer stem cell (CSC) marker for HCC. CD133(+) CSCs have been reported to resist conventional chemo- and radiotherapy, but little is known about their response to immune surveillance. Interferon-gamma (IFN-γ) is one of key cytokines that the immune system produce to eradicate cancer cells, so we investigated the function of IFN-γ on CD133+ HCC CSCs in this study. METHODS: The response of CD133(+) cells to IFN-γ was performed with functional assays (cell proliferation assay and tumor formation in nude mice), flow cytometry, immunofluorescence staining and RNA interference. RESULTS: We found that IFN-γ inhibited the proliferation of cell lines with low percentage of CD133(+) cells (wild-type human cells, BEL7402, QGY7701) but it did not affect the proliferation of cell lines with high percentage of CD133(+) cells (wild-type human cells, Huh7, PLC8024) in vivo and in vitro (nude mice). Flow cytometry analysis demonstrated that the percentage of CD133+ cells increased after IFN-γ treatment of low CD133(+) cell lines. Furthermore, IFN-γ induced the autophagy of low CD133(+) cell lines to decrease proliferation. CONCLUSION: CD133(+) HCC CSCs resisted IFN-γ-induced autophagy, which might also be a mechanism through which CSCs resist immune eradication.

MR image-based synthetic CT for IMRT prostate treatment planning and CBCT image-guided localization.

The purpose of this study was to propose and evaluate a method of creating a synthetic CT (S-CT) from MRI simulation for dose calculation and daily CBCT localization. A pair of MR and CT images was obtained in the same day from each of 10 prostate patients. The pair of MR and CT images was preregistered using the deformable image registration (DIR). Using the corresponding displacement vector field (atlas-DVF), the CT image was deformed to the MR image to create an atlas MR-CT pair. Regions of interest (ROI) on the atlas MR-CT pair were delineated and used to create atlas-ROI masks. 'Leave-one-out' test (one pair of MR and CT was used as subject-MR and subject-CT for evaluation, and the remaining 9 pairs were in the atlas library) was performed. For a subject-MR, autosegmentation and DVFs were generated using DIR between the subject-MR and the 9 atlas-MRs. An S-CT was then generated using the corresponding 9 paired atlas-CTs, the 9 atlas-DVFs and the corresponding atlas-ROI masks. The total 10 S-CTs were evaluated using the Hounsfield unit (HU), the calculated dose distribution, and the auto bony registration to daily CBCT images with respect to the 10 subject-CTs. HU differences (mean ± STD) were (2.4 ± 25.23), (1.18 ± 39.49), (32.46 ± 81.9), (0.23 ± 40.13), and (3.74 ± 144.76) for prostate, bladder, rectal wall, soft tissue outside all ROIs, and bone, respectively. The discrepancy of dose-volume param-eters calculated using the S-CT for treatment planning was small (≤ 0.22% with 95% confidence). Gamma pass rate (2% & 2 mm) was higher than 99.86% inside PTV and 98.45% inside normal structures. Using the 10 S-CTs as the reference CT for daily CBCT localization achieved the similar results compared to using the subject-CT. The translational vector differences were within 1.08 mm (0.37 ± 0.23 mm), and the rotational differences were within 1.1° in all three directions. S-CT created from a simulation MR image using the proposed approach with the preconstructed atlas library can replace the planning CT for dose calculation and daily CBCT image guidance.

MiR-449a suppresses the epithelial-mesenchymal transition and metastasis of hepatocellular carcinoma by multiple targets.

BACKGROUND: Increasing evidence indicates that Epithelial-mesenchymal transition (EMT) can be regulated by microRNAs (miRNAs). MiR-449a is a liver abundant miRNA. However, the role of miR-449a in the metastasis of hepatocellular carcinoma (HCC) remains largely unknown. METHODS: The expression levels of miR-449a were first examined in HCC cell lines and tumour tissues by real-time PCR. The in vitro and in vivo functional effect and underlying molecular mechanisms of miR-449a were examined further. RESULTS: In the present study, we found that miR-449a was significantly decreased in HCC cells and tissues, especially in those with the portal vein tumor thrombus. In HCC cell lines, stable overexpression of miR-449a was sufficient to inhibit cell motility in vitro, and pulmonary metastasis in vivo. In addition, ectopic overexpression of miR-449a in HCC cells promoted the expression of epithelial markers and reduced the levels of mesenchymal markers. Further studies revealed that the reintroduction of miR-449a attenuated the downstream signaling of Met, and consequently reduced the accumulation of Snail in cell nucleus by targeting the 3'-untranslated regions (3'-UTR) of FOS and Met. CONCLUSIONS: Our data highlight an important role of miR-449a in the molecular etiology of HCC, and implicate the potential application of miR-449a in cancer therapy.

Transducin ß-like 1 X-linked receptor 1 suppresses cisplatin sensitivity in nasopharyngeal carcinoma via activation of NF-κB pathway.

BACKGROUND: Transducin ß-like 1 X-linked receptor 1 (TBL1XR1) is an important transcriptional cofactor involved in the regulation of many signaling pathways, and is associated with carcinogenesis and tumor progression. However, the precise role of TBL1XR1 in these processes is not well understood. METHODS: We detected the expression of TBL1XR1 protein and mRNA in nasopharyngeal carcinoma (NPC) cell lines and biopsies by western blotting, real-time PCR and immunohistochemical staining (IHC). Overexpression of TBL1XR1 in NPC enhanced chemoresistance to cisplatin using two NPC cell lines in vitro and in vivo. RESULTS: TBL1XR1 was upregulated in NPC cell lines and clinical samples. The expression of TBL1XR1 was correlated with several clinicopathological factors including clinical stage, T classification, N classification and patient survival. Univariate and multivariate analysis revealed that TBL1XR1 was an independent prognostic factor for patient survival. In vitro and in vivo studies demonstrated that TBL1XR1 high expression induced resistance to cisplatin-induced apoptosis in NPC cells. Furthermore, we found that TBL1XR1 activated the NF-κB pathway and promoted transcription of genes downstream of NF-κB, especially anti-apoptotic genes. CONCLUSIONS: Upregulation of TBL1XR1 induces NPC cells resistance to cisplatin by activating the NF-κB pathway, and correlates with poor overall survival of NPC patients. TBL1XR1 has a pivotal role in NPC and could be a valuable prognostic factor as well as a novel biomarker for tailoring appropriate therapeutic regimes.

microRNA-146 up-regulation predicts the prognosis of non-small cell lung cancer by miRNA in situ hybridization.

Non-small cell lung cancer (NSCLC) accounts for approximately 70% of all lung cancer-related deaths worldwide. Prognostic markers are essential for the early detection of lung cancer in patients. In this study, we first identified microRNA146 (miR-146) expression in cancer cell lines using miRNA in situ hybridization (MISH) and confirmed the accuracy of MISH using q-RT-PCR. In addition, two different systems, BCIP/NBT and ELF, were used to detect the signal for a comparative analysis of the specificity of MISH. Compared to the BCIP/NBT system, the ELF detection system was more effective for MISH. Furthermore we detected the expression of miR-146 in NSCLC tissues (43 cases) and normal tissues (32 cases). Based on our results, we can conclude that miR-146 is more highly expressed in cancer tissue than normal tissue (t-test, P<0.05) and that miR-146 can predict the prognosis of NSCLC by MISH. Our findings preliminary demonstrate that MISH can be applied as a molecular diagnostic tool to determine the expression and localization of miRNAs in cancer tissues and that miR-146, determined by MISH, predicts the prognosis of NSCLC patients.

A novel angiotensin I-converting enzyme inhibitory peptide from walnut (Juglans sigillata) protein hydrolysates and its evaluation in Ang II-induced HUVECs and hypertensive rats.

This study aims to seek angiotensin-I-converting enzyme inhibitory (ACEi) peptides from walnut using different enzymatic hydrolysis, and further to validate the potent ACEi peptides identified and screened via peptidomics and in silico analysis against hypertension in spontaneously hypertensive rats (SHRs). Results showed that walnut protein hydrolysate (WPH) prepared by combination of alcalase and simulated gastrointestinal digestion exhibited high ACEi activity. WPH was separated via Sephadex-G25, and four peptides were identified, screened and verified based on their PeptideRanker score, structural characteristic and ACE inhibition. Interestingly, FDWLR showed the highest ACEi activity with IC50 value of 8.02 µg/mL, which might be related to its close affinity with ACE observed in molecular docking. Subsequently, high absorption and non-toxicity of FDWLR was predicted via in silico absorption, distribution, metabolism, excretion and toxicity. Furthermore, FDWLR exhibited positively vasoregulation in Ang II-induced human umbilical vein endothelial cells, and great blood pressure lowering effect in SHRs.

Research on the Coupling Effect of NBTI and TID for FDSOI pMOSFETs.

The coupling effect of negative bias temperature instability (NBTI) and total ionizing dose (TID) was investigated by simulation based on the fully depleted silicon on insulator (FDSOI) PMOS. After simulating the situation of irradiation after NBT stress, it was found that the NBTI effect weakens the threshold degradation of FDSOI PMOS under irradiation. Afterward, NBT stress was decomposed into high gate voltage stress and high-temperature stress, which was applied to the device simultaneously with irradiation. The devices under high gate voltage exhibited more severe threshold voltage degradation after irradiation compared to those under low gate voltage. Devices at high temperatures also exhibit more severe threshold degradation after irradiation compared to devices under low temperatures. Finally, the simultaneous effect of high gate voltage, high temperature, and irradiation on the device was investigated, which fully demonstrated the impact of the NBT stress on the TID effect, resulting in far more severe threshold voltage degradation.