mmWave Spatial-Temporal Single Harmonic Switching Transmitter Arrays for High back-off Beamforming Efficiency

This paper presents a spatial-temporal single harmonic switching (STHS) transmitter array architecture with enhanced efficiency in the power back-off (PBO) region. STHS is an electromagnetic and circuit co-designed and jointly optimized transmitter array that realizes beamforming and back-off power generation at the same time. The temporal dimension is originally added in STHS to achieve back-off efficiency enhancement, which can be combined with conventional power back-off enhancement methods such as Doherty amplifiers and envelope tracking. The design is validated through a simulation of a two-stage power amplifier in 65-nm CMOS at 77 GHz, which achieves a peak drain efficiency (DE) of 24.2%, a 22% DE at 3-dB PBO, 16% DE at 6-dB PBO, and 10.2% at 9-dB PBO. The efficiency exhibits a 57% improvement at 3-dB PBO, 100% improvement at 6-dB PBO, and 190% improvement at 9-dB PBO compared with class A/B amplifier

Identification and validation of SERPINE1 as a prognostic and immunological biomarker in pan-cancer and in ccRCC

Background:SERPINE1, a serine protease inhibitor involved in the regulation of the plasminogen activation system, was recently identified as a cancer-related gene. However, its clinical significance and potential mechanisms in pan-cancer remain obscure.Methods: In pan-cancer multi-omics data from public datasets, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and online web tools were used to analyze the expression of SERPINE1 in different cancers and its correlation with prognosis, genetic alteration, DNA promoter methylation, biological processes, immunoregulator expression levels, immune cell infiltration into tumor, tumor mutation burden (TMB), microsatellite instability (MSI), immunotherapy response and drug sensitivity. Further, two single-cell databases, Tumor Immune Single-cell Hub 2 (TISCH2) and CancerSEA, were used to explore the expression and potential roles of SERPINE1 at a single-cell level. The aberrant expression of SERPINE1 was further verified in clear cell renal cell carcinoma (ccRCC) through qRT-PCR of clinical patient samples, validation in independent cohorts using The Gene Expression Omnibus (GEO) database, and proteomic validation using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database.Results: The expression of SERPINE1 was dysregulated in cancers and enriched in endothelial cells and fibroblasts. Copy number amplification and low DNA promoter methylation could be partly responsible for high SERPINE1 expression. High SERPINE1 expression was associated with poor prognosis in 21 cancers. The results of gene set enrichment analysis (GSEA) indicated SERPINE1 involvement in the immune response and tumor malignancy. SERPINE1 expression was also associated with the expression of several immunoregulators and immune cell infiltration and could play an immunosuppression role. Besides, SERPINE1 was found to be related with TMB, MSI, immunotherapy response and sensitivity to several drugs in cancers. Finally, the high expression of SERPINE1 in ccRCC was verified using qRT-PCR performed on patient samples, six independent GEO cohorts, and proteomic data from the CPTAC database.Conclusion: The findings of the present study revealed that SERPINE1 exhibits aberrant expression in various types of cancers and is associated with cancer immunity and tumor malignancy, providing novel insights for individualized cancer treatment

Challenges and directions: an analysis of Genetic Analysis Workshop 17 data by collapsing rare variants within family data

Recent studies suggest that the traditional case-control study design does not have sufficient power to discover rare risk variants. Two different methods—collapsing and family data—are suggested as alternatives for discovering these rare variants. Compared with common variants, rare variants have unique characteristics. In this paper, we assess the distribution of rare variants in family data. We notice that a large number of rare variants exist only in one or two families and that the association result is largely shaped by those families. Therefore we explore the possibility of integrating both the collapsing method and the family data method. This combinational approach offers a potential power boost for certain causal genes, including VEGFA, VEGFC, SIRT1, SREBF1, PIK3R3, VLDLR, PLAT, and FLT4, and thus deserves further investigation

The data-intensive scientific revolution occurring where two-dimensional materials meet machine learning

Machine learning (ML) has experienced rapid development in recent years and been widely applied to assist studies in various research areas. Two-dimensional (2D) materials, due to their unique chemical and physical properties, have been receiving increasing attention since the isolation of graphene. The combination of ML and 2D materials science has significantly accelerated the development of new functional 2D materials, and a timely review may inspire further ML-assisted 2D materials development. In this review, we provide a horizontal and vertical summary of the recent advances at the intersection of the fields of ML and 2D materials, discussing ML-assisted 2D materials preparation (design, discovery, and synthesis of 2D materials), atomistic structure analysis (structure identification and formation mechanism), and properties prediction (electronic properties, thermodynamic properties, mechanical properties, and other properties) and revealing their connections. Finally, we highlight current research challenges and provide insight into future research opportunities.This work was supported by the ANU Futures Scheme (Q4601024), the Australian Research Council (DP190100295, LE190100014), the National Natural Science Foundation of China (No. 51706114 and 51302166), Functional Materials Interfaces Genome (FIG) project, and Doctoral Fund of Ministry of Education of China (20133108120021)

Increasing Supply Chain Visibility by Incentivizing Stakeholders to Use Blockchain

With increasing customer expectations for fast and cheap deliveries and competition to capture market share, retail organizations are increasingly compelled to make their supply chains as efficient as possible. A major driver of inefficiency in supply chains is the lack of visibility of the goods, information, and financial flows. This lack of visibility leads to decreased customer service levels and increased disputes in the supply chain. To tackle this problem, companies are investing in supply chain visibility tools such as blockchain technology. But there is no clear understanding of the impact of this new technology on supply chains. Our research models the transportation network of our corporate partner, Walmart, through system dynamics methodology and quantifies the impact that blockchain technology would have on the transportation service level and the number of shipment-related disputes. Our results suggest that when stakeholders in a supply chain introduce blockchain-enabled visibility technologies, there is a significant increase in the percentage of deliveries that are on-time and in full (OTIF), and a reduction in dispute management costs. At the same time, there are several disincentives and challenges, such as high setup cost and lack of understanding of the technology, that Walmart needs to consider to increase blockchain adoption among its stakeholders

Intersystem Bias in GPS, GLONASS, Galileo, BDS-3, and BDS-2 Integrated SPP: Characteristics and Performance Enhancement as a Priori Constraints

Global navigation satellite systems (GNSSs) have been booming in recent years, and the space segment of all four of the GNSSs, including BDS (BDS-3/BDS-2), Galileo, GPS, and GLONASS, has almost been fully deployed at present. The single point positioning (SPP) technology, which is widely used in satellite navigation and low-accuracy positioning, can benefit from the multi-GNSS integration, but the additional intersystem bias (ISB) parameters should be introduced to ensure the compatibility among different GNSSs. In this study, the ISB estimates derived from four-system integrated SPP are carefully characterized, and the performance enhancement attributed to a priori ISB constraints by prediction for position solutions under open sky and constrained visibility environments is rigorously evaluated. The results indicate that the ISB between BDS-3 and BDS-2 cannot be ignored. The daily ISBs show step changes when encountering the replacement of receiver types, while it is not the case for the receiver firmware versions. The daily ISBs are roughly consistent for the stations equipped with the same type of receivers. The short-term stability of epochwise ISBs for GLONASS, Galileo, BDS-2, and BDS-3 with respect to GPS can be 2.335, 1.262, 1.741, and 1.532 ns, respectively, whereas the corresponding long-term stability for daily ISBs can be 1.258, 1.288, 2.713, and 2.566 ns, respectively. The single-day prediction accuracy of daily ISBs for GLONASS, Galileo, BDS-2, and BDS-3 with respect to GPS can be 1.055, 0.640, 1.242, and 0.849 ns, respectively. The improvements on positioning accuracy after introducing a priori ISB constraints can be over 20% at an elevation mask of 40° and 50° with a time span of ISB prediction of a day. As to the availability, it is only 64.0% for traditional four-system SPP under a cutoff elevation of 50°, while the corresponding availability is increased to approximately 90.0% after considering a priori ISB constraints. For completeness, the characteristics of ISBs estimated with the low-cost u-blox M8T receiver and the Xiaomi Mi8 smartphone as well as the contribution of a priori ISB constraints to the multisystem SPP solutions with these devices are also investigated

Global metabolomics study on the pathogenesis of pediatric medulloblastoma via UPLC- Q/E-MS/MS.

Medulloblastoma is one of the most frequent malignant brain tumors in infancy and childhood. Early diagnosis and treatment are quite crucial for the prognosis. However, the pathogenesis of medulloblastoma is still not completely clarified. High-resolution mass spectrometry has enabled a comprehensive investigation on the mechanism of disease from the perspective of metabolism. Herein, we compared the difference of metabolic profiles of serum between medulloblastoma (n = 33) and healthy control (HC, n = 16) by using UPLC-Q/E-MS/MS. Principal component analysis and orthogonal projections to latent structures discriminant analysis (OPLS-DA) intuitively revealed the significantly distinct metabolic profiles between medulloblastoma and HC (p 0.98). Functional analysis discovered that there are four pathways notably perturbed for medulloblastoma. These pathways are related with the dysfunction of arachidonic acid metabolism, steroid hormone biosynthesis, and folate-related metabolism. The target intervention on these pathways may reduce the mortality of medulloblastoma

Assessment of IRNSS-Only Data Processing: Availability, Single-Frequency SPP and Short-Baseline RTK

The Indian Regional Navigation Satellite System (IRNSS) currently can provide independent positioning services with eight in-orbit satellites. This study provides a comprehensive assessment of IRNSS-only data processing, including the availability of satellite constellation, the performance of single-frequency single point positioning (SPP), and the performance of single-frequency short-baseline real-time kinematic (RTK) positioning. Regarding the availability of IRNSS-only case in its primary service areas, the average number of visible satellites is 6–8, and the average Position Dilution of Precision (PDOP) value falls between 3.3 and 6.2, under a service rate of nearly 100.0%. The datasets from 14 stations located in the IRNSS service areas spanning a week are used for position determination. The results show that under the IRNSS single-system case, the positioning accuracy of the SPP is 6.031, 6.015, and 9.668 m in the east, north, and up directions, respectively, and the mean positioning bias of short-baseline RTK is 5.4, −21.1, and −0.2 mm with a standard deviation (STD) error of 7.8, 19.2, and 29.0 mm in the three directions, respectively. For comparative analysis, the results of the GPS single-system and GPS/IRNSS dual-system combination cases are also presented. The positioning performance of IRNSS is inferior to that of GPS, and the performance improvement of GPS/IRNSS dual-system integrated solutions over GPS single-system solutions is not significant. Furthermore, based on the GPS/IRNSS dual-system solutions, the inter-system bias estimates from SPP, the code observation residuals from SPP, and the carrier phase observation residuals from short-baseline RTK are characterized

Assessment of IRNSS-Only Data Processing: Availability, Single-Frequency SPP and Short-Baseline RTK

The Indian Regional Navigation Satellite System (IRNSS) currently can provide independent positioning services with eight in-orbit satellites. This study provides a comprehensive assessment of IRNSS-only data processing, including the availability of satellite constellation, the performance of single-frequency single point positioning (SPP), and the performance of single-frequency short-baseline real-time kinematic (RTK) positioning. Regarding the availability of IRNSS-only case in its primary service areas, the average number of visible satellites is 6–8, and the average Position Dilution of Precision (PDOP) value falls between 3.3 and 6.2, under a service rate of nearly 100.0%. The datasets from 14 stations located in the IRNSS service areas spanning a week are used for position determination. The results show that under the IRNSS single-system case, the positioning accuracy of the SPP is 6.031, 6.015, and 9.668 m in the east, north, and up directions, respectively, and the mean positioning bias of short-baseline RTK is 5.4, −21.1, and −0.2 mm with a standard deviation (STD) error of 7.8, 19.2, and 29.0 mm in the three directions, respectively. For comparative analysis, the results of the GPS single-system and GPS/IRNSS dual-system combination cases are also presented. The positioning performance of IRNSS is inferior to that of GPS, and the performance improvement of GPS/IRNSS dual-system integrated solutions over GPS single-system solutions is not significant. Furthermore, based on the GPS/IRNSS dual-system solutions, the inter-system bias estimates from SPP, the code observation residuals from SPP, and the carrier phase observation residuals from short-baseline RTK are characterized

Research Progress of the Role of EMT in EGFR-TKIs Resistance of Non-small Cell Lung Cancer

Lung cancer is the one of the malignant tumor of the highest morbidity and mortality over the world, and non-small cell lung cancer (NSCLC) makes up about 80%. Nowadays, molecular targeted therapy has been the first-line treatment for NSCLC. Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are increasingly used in the clinical treatment, but the EGFR-TKIs acquired resistance becomes the bottleneck of continuation of EGFR-TKIs therapy. Epithelial-mesenchymal transition (EMT) is a biological phenomenon in which epithelial cells are transformed into mesenchymal cells. EMT promoted metastasis, invasion of lung cancer and conferred characteristic of stem cell on cancer cells. Meanwhile, EMT is one of an important cause of EGFR-TKIs resistance in NSCLC. The recent studies have found that resistant cells restored the sensitivity to EGFR-TKIs by reversing EMT which suggested that the target of EMT may contribute to inhibit or even reverse the resistance of EGFR-TKIs. Here we make a review about research progress of EMT in EGFR-TKIs resistance in NSCLC