Research on potential disruptive technology identification based on technology network.

Three evident and meaningful characteristics of disruptive technology are the zeroing effect that causes sustaining technology useless for its remarkable and unprecedented progress, reshaping the landscape of technology and economy, and leading the future mainstream of technology system, all of which have profound impacts and positive influences. The identification of disruptive technology is a universally difficult task. Therefore, this paper aims to enhance the technical relevance of potential disruptive technology identification results and improve the granularity and effectiveness of potential disruptive technology identification topics. According to the life cycle theory, dividing the time stage, then constructing and analyzing the dynamic of technology networks to identify potential disruptive technology. Thereby, using the Latent Dirichlet Allocation (LDA) topic model further to clarify the topic content of potential disruptive technologies. This paper takes the large civil unmanned aerial vehicles (UAVs) as an example to prove the feasibility and effectiveness of the model. The results show that the potential disruptive technology in this field is the data acquisition, main equipment, and ground platform intelligence.

Asymmetric vortex beam emission from a metasurface-integrated microring with broken conjugate symmetry.

Vortex beams that carry orbital angular moment (OAM) have recently attracted a great amount of research interest, and metasurfaces and planar microcavities have emerged as two prominent, but mostly separated, methods for Si chip-based vortex beam emission. In this work, we demonstrate in numerical simulation for the first time the hybridization of these two existing methods in a Si chip-based passive emitter (i.e., a light coupler). A unique feature of this device is its broken conjugate symmetry, which originates from introducing a metasurface phase gradient along a microring. The broken conjugate symmetry creates a new phenomenon that we refer to as asymmetric vortex beam emission. It allows two opposite input directions to generate two independent sets of OAM values, a capability that has never been reported before in Si chip-based passive emitters. In addition, we have also developed here a new analytical method to extract the OAM spectrum from a vector vortex beam. This analytical method will prove to be useful for vector vortex beam analysis, as mode purity analysis has rarely been reported in literature due to the complexity of the full-vector nature of such beams. This study provides new approaches for both the design and the analysis of integrated vortex beam emission, which could be utilized in many applications such as free-space optical communications and microfluidic particle manipulation.

Identifying TME signatures for cervical cancer prognosis based on GEO and TCGA databases.

The mortality rate from cervical cancer (CESC), a malignant tumor that affects women, has increased significantly globally in recent years. The discovery of biomarkers points to a direction for the diagnosis of cervical cancer with the advancement of bioinformatics technology. The goal of this study was to look for potential biomarkers for the diagnosis and prognosis of CESC using the GEO and TCGA databases. Because of the high dimension and small sample size of the omic data, or the use of biomarkers generated from a single omic data, the diagnosis of cervical cancer may be inaccurate and unreliable. The purpose of this study was to search the GEO and TCGA databases for potential biomarkers for the diagnosis and prognosis of CESC. We begin by downloading CESC (GSE30760) DNA methylation data from GEO, then perform differential analysis on the downloaded methylation data and screen out the differential genes. Then, using estimation algorithms, we score immune cells and stromal cells in the tumor microenvironment and perform survival analysis on the gene expression profile data and the most recent clinical data of CESC from TCGA. Then, using the 'limma' package and Venn plot in R language to perform differential analysis of genes and screen out overlapping genes, these overlapping genes were then subjected to GO and KEGG functional enrichment analysis. The differential genes screened by the GEO methylation data and the differential genes screened by the TCGA gene expression data were intersected to screen out the common differential genes. A protein-protein interaction (PPI) network of gene expression data was then created in order to discover important genes. The PPI network's key genes were crossed with previously identified common differential genes to further validate them. The Kaplan-Meier curve was then used to determine the prognostic importance of the key genes. Survival analysis has shown that CD3E and CD80 are important for the identification of cervical cancer and can be considered as potential biomarkers for cervical cancer.

Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data.

The early symptoms of lung adenocarcinoma patients are inapparent, and the clinical diagnosis of lung adenocarcinoma is primarily through X-ray examination and pathological section examination, whereas the discovery of biomarkers points out another direction for the diagnosis of lung adenocarcinoma with the development of bioinformatics technology. However, it is not accurate and trustworthy to diagnose lung adenocarcinoma due to omics data with high-dimension and low-sample size (HDLSS) features or biomarkers produced by utilizing only single omics data. To address the above problems, the feature selection methods of biological analysis are used to reduce the dimension of gene expression data (GSE19188) and DNA methylation data (GSE139032, GSE49996). In addition, the Cartesian product method is used to expand the sample set and integrate gene expression data and DNA methylation data. The classification is built by using a deep neural network and is evaluated on K-fold cross validation. Moreover, gene ontology analysis and literature retrieving are used to analyze the biological relevance of selected genes, TCGA database is used for survival analysis of these potential genes through Kaplan-Meier estimates to discover the detailed molecular mechanism of lung adenocarcinoma. Survival analysis shows that COL5A2 and SERPINB5 are significant for identifying lung adenocarcinoma and are considered biomarkers of lung adenocarcinoma.

Coherent generation of arbitrary first-order Poincaré sphere beams on an Si chip.

Generalized vector vortex light beams possess spatially variant polarization states, and higher-order Poincaré spheres represent a powerful analytical tool for analyzing these intriguing and complicated optical fields. For the generation of these vortex beams, a range of different methods have been explored, with an increasing emphasis placed on compact, integrated devices. Here, we demonstrate via numerical simulation, for the first time, an on-chip light emitter that allows for the controllable generation of all points on a first-order Poincaré sphere (FOPS). The FOPS beam generator consists of a waveguide-coupled, nanostructured Si microring resonator that converts two guided, coherent light waves into freely propagating output light. By matching their whispering gallery modes with the nanostructures, the fundamental TE (transverse electric) and TM (transverse magnetic) input modes produce radial and azimuthal polarizations, respectively. These two linear polarizations can form a pair of eigenstates for the FOPS. Consequently, tuning the phase contrast and the intensity ratio of these two coherent inputs allows for the generation of an arbitrary point on the FOPS. This result indicates a new way for on-chip vector vortex beam generation, which may be applied for integrated optical tweezers and high-capacity optical communications.

On-chip optical pulse train generation through the optomechanical oscillation.

This paper proposes a novel on-chip optical pulse train generator (OPTG) based on optomechanical oscillation (OMO). The OPTG consists of an optical cavity and mechanical resonator, in which OMO periodically modulates the optical cavity field and consequently generates optical pulse trains. The dimensionless method are introduced to simulate the OMO-based OPTG with reduced analysis complexity. We investigate the optomechanical coupling and the dynamic back-action processes, by which we found a dead zone that forbids the OMO, and derived the optimal laser detuning and the minimum threshold power. We analysed the OMO-based OPTG in terms of the pulse shape distortion, extinction ratio (ER) and duty-cycle (DC). Increasing input power, mechanical and optical Q-factors will increase ER, reduce DC and produce sharper and shorter optical pulses. We also discuss the design guidance of OMO-based OPTG and explore its application in distributed fibre optical sensor (DFOS).