Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz

Integrated sensing and communications (ISAC) is a potential technology of 6G, aiming to enable end-to-end information processing ability and native perception capability for future communication systems. As an important part of the ISAC application scenarios, ISAC aided vehicle-to-everything (V2X) can improve the traffic efficiency and safety through intercommunication and synchronous perception. It is necessary to carry out measurement, characterization, and modeling for vehicular ISAC channels as the basic theoretical support for system design. In this paper, dynamic vehicular ISAC channel measurements at 28 GHz are carried out and provide data for the characterization of non-stationarity characteristics. Based on the actual measurements, this paper analyzes the time-varying PDPs, RMSDS and non-stationarity characteristics of front, lower front, left and right perception directions in a complicated V2X scenarios. The research in this paper can enrich the investigation of vehicular ISAC channels and enable the analysis and design of vehicular ISAC systems

Nonlinear analysis of gravitational wave signals based on recurrence quantification analysis

Recurrence plot and recurrence quantification analysis are used to analyze different features of gravitational wave signals. Firstly, the appropriate delay time and embedding dimension are respectively estimated by methods of the C_C method. One dimension time series of gravitational wave is extended to high dimension phase space by employing phase space reconstruction for studying the movement characteristic of neighboring points in time series. Then the recurrence plots of different gravitational wave signals are implemented intuitively and qualitatively analyzing different features of gravitational wave signals. Different nonlinear characteristic parameters are calculated by recurrence quantification analysis (RQA) methods, such as recurrence rate, recurrence entropy, determinism rate and stratification, based on which the features of different gravitational wave signals can be well analyzed quantitatively

Nonlinear analysis of gravitational wave signals based on recurrence quantification analysis

Recurrence plot and recurrence quantification analysis are used to analyze different features of gravitational wave signals. Firstly, the appropriate delay time and embedding dimension are respectively estimated by methods of the C_C method. One dimension time series of gravitational wave is extended to high dimension phase space by employing phase space reconstruction for studying the movement characteristic of neighboring points in time series. Then the recurrence plots of different gravitational wave signals are implemented intuitively and qualitatively analyzing different features of gravitational wave signals. Different nonlinear characteristic parameters are calculated by recurrence quantification analysis (RQA) methods, such as recurrence rate, recurrence entropy, determinism rate and stratification, based on which the features of different gravitational wave signals can be well analyzed quantitatively

Transcriptome-wide identification of optimal reference genes for expression analysis of Pyropia yezoensis responses to abiotic stress

Abstract Background Pyropia yezoensis, a marine red alga, is an ideal research model for studying the mechanisms of abiotic stress tolerance in intertidal seaweed. Real-time quantitative polymerase chain reaction (RT-qPCR) is the most commonly used method to analyze gene expression levels. To accurately quantify gene expression, selection and validation of stable reference genes is required. Results We used transcriptome profiling data from different abiotic stress treatments to identify six genes with relatively stable expression levels: MAP, ATPase, CGS1, PPK, DPE2, and FHP. These six genes and three conventional reference genes, UBC, EF1-α, and eif4A, were chosen as candidates for optimal reference gene selection. Five common statistical approaches (geNorm, ΔCt method, NormFinder, BestKeeper, and ReFinder) were used to identify the stability of each reference gene. Our results show that: MAP, UBC, and FHP are stably expressed in all analyzed conditions; CGS1 and UBC are stably expressed under conditions of dehydration stress; and MAP, UBC, and CGS1 are stably expressed under conditions of temperature stress. Conclusion We have identified appropriate reference genes for RT-qPCR in P. yezoensis under different abiotic stress conditions which will facilitate studies of gene expression under these conditions

Additional file 6: of Transcriptome-wide identification of optimal reference genes for expression analysis of Pyropia yezoensis responses to abiotic stress

Table S1. Pairwise variation (Vn/n + 1) analysis of 9 candidate. (XLSX 10 kb

Additional file 1: of Transcriptome-wide identification of optimal reference genes for expression analysis of Pyropia yezoensis responses to abiotic stress

Figure S1. Stability distribution of transcripts using PaGeFinder (PDF 8 kb

Additional file 3: of Transcriptome-wide identification of optimal reference genes for expression analysis of Pyropia yezoensis responses to abiotic stress

Figure S3. Cycle threshold (Ct) values of nine candidate reference genes across dehydration samples (A) and temperature samples (B). (PDF 194 kb

Additional file 4: of Transcriptome-wide identification of optimal reference genes for expression analysis of Pyropia yezoensis responses to abiotic stress

Figure S4. Expression stability values(M) of nine candidate reference genes calculated geNorm under dehydration (A), temperature (B) and all conditions (C) respectively. (PDF 99 kb

Additional file 2: of Transcriptome-wide identification of optimal reference genes for expression analysis of Pyropia yezoensis responses to abiotic stress

Figure S2. Melting curves and agarose gel electrophoresis of PCR products of nine candidate genes. (JPEG 1688 kb

5G for Railways: the Next Generation Railway Dedicated Communications

To overcome increasing traffic, provide various new services, further ensure safety and security, significantly improve travel comfort, a new communication system for railways is required. Since 2019, public networks have been evolving to the fifth generation communication (5G) worldwide, whereas the main communication system of railway is still based on the second generation communication (2G). It is thus necessary for railways to replace the current 2G-based technology with the next generation railway dedicated communication system with improved capacity and capability, and the 5G for railways (5G-R) technology is a promising solution for further intelligent railways. This article gives a review of the current developments of the next generation railway communications, followed by a discussion of the typical services that the 5G-R can provide to intelligent railways. Then, main application scenarios of 5G-R are summarized and system configurations are compared. Some key technologies of 5G-R such as network architecture, massive MIMO, millimeter-wave, multiple access scheme, ultra-reliable low latency communication, and advanced video processing are presented and analyzed. Finally, some challenges of 5G-R are highlighted