Hyperspectral Image Denoising With Group Sparse and Low-Rank Tensor Decomposition

Hyperspectral image (HSI) is usually corrupted by various types of noise, including Gaussian noise, impulse noise, stripes, deadlines, and so on. Recently, sparse and low-rank matrix decomposition (SLRMD) has demonstrated to be an effective tool in HSI denoising. However, the matrix-based SLRMD technique cannot fully take the advantage of spatial and spectral information in a 3-D HSI data. In this paper, a novel group sparse and low-rank tensor decomposition (GSLRTD) method is proposed to remove different kinds of noise in HSI, while still well preserving spectral and spatial characteristics. Since a clean 3-D HSI data can be regarded as a 3-D tensor, the proposed GSLRTD method formulates a HSI recovery problem into a sparse and low-rank tensor decomposition framework. Specifically, the HSI is first divided into a set of overlapping 3-D tensor cubes, which are then clustered into groups by K-means algorithm. Then, each group contains similar tensor cubes, which can be constructed as a new tensor by unfolding these similar tensors into a set of matrices and stacking them. Finally, the SLRTD model is introduced to generate noisefree estimation for each group tensor. By aggregating all reconstructed group tensors, we can reconstruct a denoised HSI. Experiments on both simulated and real HSI data sets demonstrate the effectiveness of the proposed method.This paper was supported in part by the National Natural Science Foundation of China under Grant 61301255, Grant 61771192, and Grant 61471167, in part by the National Natural Science Fund of China for Distinguished Young Scholars under Grant 61325007, in part by the National Natural Science Fund of China for International Cooperation and Exchanges under Grant 61520106001, and in part by the Science and Technology Plan Project Fund of Hunan Province under Grant 2015WK3001 and Grant 2017RS3024.Peer Reviewe

Quasiparticle characteristics of the weakly ferromagnetic Hund's metal MnSi

Hund's metals are multi-orbital systems with $3d$ or $4d$ electrons exhibiting both itinerant character and local moments, and they feature Kondo-like screenings of local orbital and spin moments, with suppressed coherence temperature driven by Hund's coupling $J_H$. They often exhibit magnetic order at low temperature, but how the interaction between the Kondo-like screening and long-range magnetic order is manifested in the quasiparticle spectrum remains an open question. Here we present spectroscopic signature of such interaction in a Hund's metal candidate MnSi exhibiting weak ferromagnetism. Our photoemission measurements reveal renormalized quasiparticle bands near the Fermi level with strong momentum dependence: the ferromagnetism manifests through possibly exchange-split bands (Q1) below $T_C$ , while the spin/orbital screenings lead to gradual development of quasiparticles (Q2) upon cooling. Our results demonstrate how the characteristic spin/orbital coherence in a Hund's metal could coexist and compete with the magnetic order to form a weak itinerant ferromagnet, via quasiparticle bands that are well separated in momentum space and exhibit distinct temperature dependence. Our results imply that the competition between the spin/orbital screening and the magnetic order in a Hund's metal bears intriguing similarity to the Kondo lattice systems.Comment: accepted by PR

Coherent control of a high-orbital hole in a semiconductor quantum dot

Coherently driven semiconductor quantum dots are one of the most promising platforms for non-classical light sources and quantum logic gates which form the foundation of photonic quantum technologies. However, to date, coherent manipulation of single charge carriers in quantum dots is limited mainly to their lowest orbital states. Ultrafast coherent control of high-orbital states is obstructed by the demand for tunable terahertz pulses. To break this constraint, we demonstrate an all-optical method to control high-orbital states of a hole via stimulated Auger process. The coherent nature of the Auger process is proved by Rabi oscillation and Ramsey interference. Harnessing this coherence further enables the investigation of single-hole relaxation mechanism. A hole relaxation time of 161 ps is observed and attributed to the phonon bottleneck effect. Our work opens new possibilities for understanding the fundamental properties of high-orbital states in quantum emitters and developing new types of orbital-based quantum photonic devices.Comment: Manuscript with 14 pages and 6 figures plus supplementary Information comprising 15 pages and 14 figure

RNA modifications in cancer immune therapy: regulators of immune cells and immune checkpoints

RNA modifications are epigenetic changes that alter the structure and function of RNA molecules, playing a crucial role in the onset, progression, and treatment of cancer. Immune checkpoint inhibitor (ICI) therapies, particularly PD-1 blockade and anti-CTLA-4 treatments, have changed the treatment landscape of virous cancers, showing great potential in the treatment of different cancer patients, but sensitivity to these therapies is limited to certain individuals. This review offers a comprehensive survey of the functions and therapeutic implications of the four principal RNA modifications, particularly highlighting the significance of m6A in the realms of immune cells in tumor and immunotherapy. This review starts by providing a foundational summary of the roles RNA modifications assume within the immune cell community, focusing on T cells, NK cells, macrophages, and dendritic cells. We then discuss how RNA modifications influence the intricate regulatory mechanisms governing immune checkpoint expression, modulation of ICI efficacy, and prediction of ICI treatment outcomes, and review drug therapies targeting genes regulated by RNA modifications. Finally, we explore the role of RNA modifications in gene editing, cancer vaccines, and adoptive T cell therapies, offering valuable insights into the use of RNA modifications in cancer immunotherapy

An Optimization-Based Approach to Social Network Group Decision Making with an Application to Earthquake Shelter-Site Selection

The social network has emerged as an essential component in group decision making (GDM) problems. Thus, this paper investigates the social network GDM (SNGDM) problem and assumes that decision makers offer their preferences utilizing additive preference relations (also called fuzzy preference relations). An optimization-based approach is devised to generate the weights of decision makers by combining two reliable resources: in-degree centrality indexes and consistency indexes. Based on the obtained weights of decision makers, the individual additive preference relations are aggregated into a collective additive preference relation. Further, the alternatives are ranked from best to worst according to the obtained collective additive preference relation. Moreover, earthquakes have occurred frequently around the world in recent years, causing great loss of life and property. Earthquake shelters offer safety, security, climate protection, and resistance to disease and ill health and are thus vital for disaster-affected people. Selection of a suitable site for locating shelters from potential alternatives is of critical importance, which can be seen as a GDM problem. When selecting a suitable earthquake shelter-site, the social trust relationships among disaster management experts should not be ignored. To this end, the proposed SNGDM model is applied to evaluate and select earthquake shelter-sites to show its effectiveness. In summary, this paper constructs a novel GDM framework by taking the social trust relationship into account, which can provide a scientific basis for public emergency management in the major disasters field

Impacts of Sulfuric Acid on the Stability and Separation Performance of Polymeric PVDF-Based Membranes at Mild and High Concentrations: An Experimental Study

This study investigated the effects of an aqueous acidic solution at typical concentrations on polymeric polyvinylidene fluoride (PVDF)-based membranes. Flat-sheet PVDF-based membranes were completely embedded in sulfuric acid at varying concentrations. The effect of the acid concentration after a prolonged exposure time on the chemical, mechanical and physical properties of the membrane were checked via FE-SEM, EDX (Energy-Dispersive Spectrometer), FTIR, XRD, tensile strength, zeta potential, contact angle, porosity, pure water flux measurement and visual observation. The result reveals prompt initiation of reaction between the PVDF membrane and sulfuric acid, even at a mild concentration. As the exposure time extends with increasing concentration, the change in chemical and mechanical properties become more pronounced, especially in the morphology, although this was not really noticeable in either the crystalline phase or the functional group analyses. The ultimate mechanical strength decreased from 46.18 ± 0.65 to 32.39 ± 0.22 MPa, while the hydrophilicity was enhanced due to enlargement of the pores. The flux at the highest concentration and exposure period increased by 2.3 times that of the neat membrane, while the BSA (Bovine Serum Albumin) rejection dropped by 55%. Similar to in an alkaline environment, the stability and performance of the PVDF-based membrane analyzed in this study manifested general deterioration.</jats:p