No abstract

No abstract

No abstract

The emerging ferroelectric nematic (N F ) liquid crystal is a novel 3D-ordered liquid exhibiting macroscopic electric polarization. The combination of the ultrahigh dielectric constant, strong nonlinear optical signal, and high sensitivity to the electric field makes N F materials promising for the development of advanced liquid crystal electroopic devices. Previously, all studies focused on the rod-shaped small molecules with limited length (l) range and dipole moment (μ) values. Here, through the precision synthesis, we extend the aromatic rod-shaped mesogen to oligomer/polymer (repeat unit up to 12 with monodisperse molecular-weight dispersion) and increase the μ value over 30 Debye (D). The N F phase has a widespread existence far beyond our expectation and could be observed in all the oligomer/polymer length range. Notably, the N F phase experiences a nontrivial evolution pathway with the traditional apolar nematic phase completely suppressed, i.e., the N F phase nucleates directly from the isotropic liquid phase. The discovery of thte ferroelectric packing of oligomer/polymer rods not only offers the concept of extending the N F state to oligomers/polymers but also provides some previously overlooked insights in oxybenzoate-based liquid crystal polymer materials.

No abstract

Background: Renal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in urogenital system, and the clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma. Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IRlncRs analysis based on abundant ccRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field. Methods: Based on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immunerelated genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines. Results: A total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRl-ncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient.

Summary This paper studies sign consensus, a collective behavior of multiagent systems, when both cooperative and antagonistic interactions coexist among agents. By sign consensus, it means that the states of all agents will eventually achieve the same sign but may with different magnitudes. Compared with some recent works on sign‐consensus problems, where only fixed graphs are considered and the graph adjacency matrix needs to be eventually positive, this paper allows the graph to be switching over time. Control laws are proposed and analyzed with respect to three classes of switching graphs. Examples illustrate the efficacy of the control algorithms.

A class of linear time-varying systems can be characterized by dispersive signal transformations, such as nonlinear shifts in the phase of the propagating signal, causing different frequencies to be shifted in time by different amounts. In this paper, we propose a discrete time-frequency model to decompose the dispersive system output into discrete dispersive frequency shifts and generalized time shifts, weighted by a smoothed and sampled version of the dispersive spreading function. The discretization formulation is obtained from the discrete narrowband system model through a unitary warping relation between the narrowband and dispersive spreading functions. This warping relation depends on the nonlinear phase transformations induced by the dispersive system. In order to demonstrate the effectiveness of the proposed discrete characterization, we investigate acoustic transmission over shallow water environments that suffers from severe degradations as a result of modal frequency dispersions and multipath fading. Using numerical results, we demonstrate that the discrete dispersive model can lead to a joint multipath-dispersion diversity that we achieve by properly designing the transmitted waveform and the reception scheme to match the dispersive environment characteristics.