Lumped Time-Delay Compensation Scheme for Coding Synchronization in the Nonlinear Spectral Quantization-Based All-Optical Analog-to-Digital Conversion

this paper, we propose a novel lumped time-delay compensation scheme for the all-optical analog-to-digital conversion based on soliton self-frequency shift and optical interconnection techniques. By inserting a segment of negative dispersion fiber between the quantization and the coding module, the time delay of different quantized pulses can be accurately compensated with a simple structure compared to the multiple time-delay lines. The simulation results show that the coding pulses can be well synchronized using a span of fiber, with the flattened negative dispersion within the wavelength range of 1558-1620 nm. In addition, the problems of pulse broadening and time error are discussed, and it is shown that no damage happens to the coding correctness within the sampling rate of 30 GSa/s

Bayesian model-data synthesis with an application to global Glacio-Isostatic Adjustment

We introduce a framework for updating large scale geospatial processes using a model-data synthesis method based on Bayesian hierarchical modelling. Two major challenges come from updating large-scale Gaussian process and modelling non-stationarity. To address the first, we adopt the SPDE approach that uses a sparse Gaussian Markov random fields (GMRF) approximation to reduce the computational cost and implement the Bayesian inference by using the INLA method. For non-stationary global processes, we propose two general models that accommodate commonly-seen geospatial problems. Finally, we show an example of updating an estimate of global glacial isostatic adjustment (GIA) using GPS measurements

Can we resolve the basin-scale sea-level trend budget from GRACE ocean mass?

Understanding sea level changes at a regional scale is important for improving local sea level projections and coastal management planning. Sea level budget (SLB) estimates derived from the sum of observation of each component close for the global mean. The sum of steric and Gravity Recovery and Climate Experiment (GRACE) ocean mass contributions to sea level calculated from measurements does not match the spatial patterns of sea surface height trends from satellite altimetry at 1° grid resolution over the period 2005–2015. We investigate potential drivers of this mismatch aggregating to subbasin regions and find that the steric plus GRACE ocean mass observations do not represent the small-scale features seen in the satellite altimetry. In addition, there are discrepancies with large variance apparent at the global and hemispheric scale. Thus, the SLB closure on the global scale to some extent represents a cancelation of errors. The SLB is also sensitive to the glacial isostatic adjustment correction for GRACE and to altimery orbital altitude. Discrepancies in the SLB are largest for the Indian-South Pacific Ocean region. Taking the spread of plausible sea level trends, the SLB closes at the ocean-basin scale ( ) but with large spread of magnitude, one third or more of the trend signal. Using the most up-to-date observation products, our ocean-region SLB does not close everywhere, and consideration of systematic uncertainties diminishes what information can be gained from the SLB about sea level processes, quantifying contributions, and validating Earth observation systems

Extremely Large-Scale MIMO: Fundamentals, Challenges, Solutions, and Future Directions

Extremely large-scale multiple-input-multiple-output (XL-MIMO) is a promising technology to empower the next-generation communications. However, XL-MIMO, which is still in its early stage of research, has been designed with a variety of hardware and performance analysis schemes. To illustrate the differences and similarities among these schemes, we comprehensively review existing XL-MIMO hardware designs and characteristics in this article. Then, we thoroughly discuss the research status of XL-MIMO from "channel modeling", "performance analysis", and "signal processing". Several existing challenges are introduced and respective solutions are provided. We then propose two case studies for the hybrid propagation channel modeling and the effective degrees of freedom (EDoF) computations for practical scenarios. Using our proposed solutions, we perform numerical results to investigate the EDoF performance for the scenarios with unparallel XL-MIMO surfaces and multiple user equipment, respectively. Finally, we discuss several future research directions.Comment: 8 pages, 6 figures, to appear in IEEE Wireless Communication

The Role of Necroptosis in Cardiovascular Disease

A newly discovered mechanism of cell death, programmed necrosis (necroptosis), combines features of both necrosis and apoptosis. Necroptosis is tightly modulated by a series of characteristic signaling pathways. Activating necroptosis by ligands of death receptors requires the kinase activity of receptor-interacting protein 1 (RIP1), which mediates the activation of receptor-interacting protein 3 (RIP3) and mixed lineage kinase domain-like (MLKL) two critical downstream mediators of necroptosis. Recently, different cytokines have been found participating in this mechanism of cell death. Necroptosis has been proposed as an important component to the pathophysiology of heart disease such as vascular atherosclerosis, ischemia-reperfusion injury, myocardial infarction and cardiac remodeling. Targeting necroptosis signaling pathways may provide therapeutic benefit in the treatment of cardiovascular diseases

Surface density-of-states on semi-infinite topological photonic and acoustic crystals

Iterative Green's function, based on cyclic reduction of block tridiagonal matrices, has been the ideal algorithm, through tight-binding models, to compute the surface density-of-states of semi-infinite topological electronic materials. In this paper, we apply this method to photonic and acoustic crystals, using finite-element discretizations and a generalized eigenvalue formulation, to calculate the local density-of-states on a single surface of semi-infinite lattices. The three-dimensional (3D) examples of gapless helicoidal surface states in Weyl and Dirac crystals are shown and the computational cost, convergence and accuracy are analyzed.Comment: 7 pages, 4 figure

A new global GPS dataset for testing and improving modelled GIA uplift rates

We have produced a global dataset of ~4000 GPS vertical velocities that can be used as observational estimates of glacial isostatic adjustment (GIA) uplift rates. GIA is the response of the solid Earth to past ice loading, primarily, since the Last Glacial Maximum, about 20 K yrs BP. Modelling GIA is challenging because of large uncertainties in ice loading history and also the viscosity of the upper and lower mantle. GPS data contain the signature of GIA in their uplift rates but these also contain other sources of vertical land motion (VLM) such as tectonics, human and natural influences on water storage that can mask the underlying GIA signal. A novel fully-automatic strategy was developed to post-process the GPS time series and to correct for non-GIA artefacts. Before estimating vertical velocities and uncertainties, we detected outliers and jumps and corrected for atmospheric mass loading displacements. We corrected the resulting velocities for the elastic response of the solid Earth to global changes in ice sheets, glaciers, and ocean loading, as well as for changes in the Earth's rotational pole relative to the 20th century average. We then applied a spatial median filter to remove sites where local effects were dominant to leave approximately 4000 GPS sites. The resulting novel global GPS dataset shows a clean GIA signal at all post-processed stations and is suitable to investigate the behaviour of global GIA forward models. The results are transformed from a frame with its origin in the centre of mass of the total Earth's system (CM) into a frame with its origin in the centre of mass of the solid Earth (CE) before comparison with 13 global GIA forward model solutions, with best fits with Pur-6-VM5 and ICE-6G predictions. The largest discrepancies for all models were identified for Antarctica and Greenland, which may be due to either uncertain mantle rheology, ice loading history/magnitude and/or GPS errors