Achieving both high selectivity and current density for CO2 reduction to formate on nanoporous tin foam electrocatalysts

Currently, low catalytic activity, selectivity and stability are the biggest challenges which restrict the large scale applications of CO2 electrochemical reduction. Formic acid, one of the highest value-added products from electrochemical reduction of CO2, has gathered much interest. Here, we develop nanoporous tin foam catalysts which exhibit significantly high selectivity and faster production rate to formate. In a 0.1 M NaHCO3 solution, the maximum Faradaic efficiency for formate production reaches above 90% with a current density over 23 mA cm-2 , which are among the highest reported value to date under ambient conditions. The improved production rate can be attributed to the high surface area and porous structure. Moreover, the electrocatalysts are quite stable, namely, the Faradaic efficiency remains unchanged during 16 hour electrolysis. This is a promising technology to convert CO2 into useful hydrocarbons

Observation of the Knot Topology of Non-Hermitian Systems in a Single Spin

The non-Hermiticity of the system gives rise to distinct knot topology that has no Hermitian counterpart. Here, we report a comprehensive study of the knot topology in gapped non-Hermitian systems based on the universal dilation method with a long coherence time nitrogen-vacancy center in a $^{\text{12}}$C isotope purified diamond. Both the braiding patterns of energy bands and the eigenstate topology are revealed. Furthermore, the global biorthogonal Berry phase related to the eigenstate topology has been successfully observed, which identifies the topological invariance for the non-Hermitian system. Our method paves the way for further exploration of the interplay among band braiding, eigenstate topology and symmetries in non-Hermitian quantum systems

Improved Limits on an Exotic Spin- and Velocity-Dependent Interaction at the Micrometer Scale with an Ensemble-NV-Diamond Magnetometer

Searching for exotic interactions provides a path for exploring new particles beyond the standard model. Here, we used an ensemble-NV-diamond magnetometer to search for an exotic spin- and velocity-dependent interaction between polarized electron spins and unpolarized nucleons at the micrometer scale. A thin layer of nitrogen-vacancy electronic spin ensemble in diamond is utilized as both the solid-state spin quantum sensor and the polarized electron source, and a vibrating lead sphere serves as the moving unpolarized nucleon source. The exotic interaction is searched by detecting the possible effective magnetic field induced by the moving unpolarized nucleon source using the ensemble-NV-diamond magnetometer. Our result establishes new bounds for the coupling parameter $f_\perp$ within the force range from 5 to 400 $\rm \mu$m. The upper limit of the coupling parameter at 100 $\rm \mu$m is $\lvert f_\perp \rvert \leq 1.1\times 10^{-11}$, which is 3 orders of magnitude more stringent than the previous constraint. This result shows that NV ensemble can be a promising platform to search for hypothetical particles beyond the standard model

Evidence for the Presentation of Major Histocompatibility Complex Class I–restricted Epstein-Barr Virus Nuclear Antigen 1 Peptides to CD8+ T Lymphocytes

The Epstein-Barr virus (EBV)-encoded nuclear antigen 1 (EBNA1) is expressed in all EBV-associated tumors, making it an important target for immunotherapy. However, evidence for major histocompatibility complex (MHC) class I–restricted EBNA1 peptides endogenously presented by EBV-transformed B and tumor cells remains elusive. Here we describe for the first time the identification of an endogenously processed human histocompatibility leukocyte antigen (HLA)-B8–restricted EBNA1 peptide that is recognized by CD8+ T cells. T cell recognition could be inhibited by the treatment of target cells with proteasome inhibitors that block the MHC class I antigen processing pathway, but not by an inhibitor (chloroquine) of MHC class II antigen processing. We also demonstrate that new protein synthesis is required for the generation of the HLA-B8 epitope for T cell recognition, suggesting that defective ribosomal products (DRiPs) are the major source of T cell epitopes. Experiments with protease inhibitors indicate that some serine proteases may participate in the degradation of EBNA1 DRiPs before they are further processed by proteasomes. These findings not only provide the first evidence of the presentation of an MHC class I–restricted EBNA1 epitope to CD8+ T cells, but also offer new insight into the molecular mechanisms involved in the processing and presentation of EBNA1

Naja naja atra

Systemic lupus erythematosus (SLE) is an autoimmune disease and effective therapy for this pathology is currently unavailable. We previously reported that oral administration of Naja naja atra venom (NNAV) had anti-inflammatory and immune regulatory actions. We speculated that NNAV may have therapeutic effects in MRL/lpr SLE mice. Twelve-week-old MRL/lpr mice received oral administration of NNAV (20, 40, and 80 μg/kg) or Tripterygium wilfordii polyglycosidium (10 mg/kg) daily for 16 weeks. The effects of NNAV on SLE manifestations, including skin erythema, proteinuria, and anxiety-like behaviors, were assessed with visual inspection and Multistix 8 SG strips and open field test, respectively. The pathology of spleen and kidney was examined with H&E staining. The changes in autoimmune antibodies and cytokines were determined with ELISA kits. The results showed that NNAV protected against the manifestation of SLE, including skin erythema and proteinuria. In addition, although no apparent histological change was found in liver and heart in MRL/lpr SLE mice, NNAV reduced the levels of glutamate pyruvate transaminase and creatine kinase. Furthermore, NNAV increased serum C3 and reduced concentrations of circulating globulin, anti-dsDNA antibody, and inflammatory cytokines IL-6 and TNF-α. NNAV also reduced lymphadenopathy and renal injury. These results suggest that NNAV may have therapeutic values in the treatment of SLE by inhibiting autoimmune responses

Self-adaptive seismic data reconstruction and denoising using dictionary learning based on morphological component analysis

Data reconstruction and data denoising are two critical preliminary steps in seismic data processing. Compressed Sensing states that a signal can be recovered by a series of solving algorithms if it is sparse in a transform domain, and has been well applied in the field of reconstruction, when, sparse representation of seismic data is the key point. Considering the complexity and diversity of seismic data, a single mathematical transformation will lead to incomplete sparse expression and bad restoration effects. Morphological Component Analysis (MCA) decomposes a signal into several components with outstanding morphological features to approximate the complex internal data structure. However, the representation ability of combined dictionaries is constrained by the number of dictionaries, and cannot be self-adaptively matched with the data features. Dictionary learning overcomes the limitation of fixed base function by training dictionaries that are fully suitable for processed data, but requires huge amount of time and considerable hardware cost. To solve the above problems, a new dictionary library (K-Singluar Value Decomposition learning dictionary and Discrete Cosine Transform dictionary) is hereby proposed based on the efficiency of fixed base dictionary and the high precision of learning dictionary. The self-adaptive sparse representation is achieved under the Morphological Component Analysis framework and is successfully applied to the reconstruction and denoising of seismic data. Real data tests have proved that the proposed method performs better than single mathematical transformation and other combined dictionaries