Molybdenum disulfide (MoS2) is systematically studied using Raman spectroscopy with ultraviolet and visible laser lines. It is shown that only the Raman frequencies of $ E_{2{\rm g}}^1 $ and $ A_{{\rm 1g}}^{} $ peaks vary monotonously with the layer number of ultrathin MoS2 flakes, while intensities or widths of the peaks vary arbitrarily. The coupling between electronic transitions and phonons are found to become weaker when the layer number of MoS2 decreases, attributed to the increased electronic transition energies or elongated intralayer atomic bonds in ultrathin MoS2. The asymmetric Raman peak at 454 cm−1, which has been regarded as the overtone of longitudinal optical M phonons in bulk MoS2, is actually a combinational band involving a longitudinal acoustic mode (LA(M)) and an optical mode ($ A_{{\rm 2u}}^{} $). Our findings suggest a clear evolution of the coupling between electronic transition and phonon when MoS2 is scaled down from three‐ to two‐dimensional geometry.

Checkpoint blockade enhances effector T cell function and has elicited long-term remission in a subset of patients with a broad spectrum of cancers. TIGIT is a checkpoint receptor thought to be involved in mediating T cell exhaustion in tumors; however, the relevance of TIGIT to the dysfunction of natural killer (NK) cells remains poorly understood. Here we found that TIGIT, but not the other checkpoint molecules CTLA-4 and PD-1, was associated with NK cell exhaustion in tumor-bearing mice and patients with colon cancer. Blockade of TIGIT prevented NK cell exhaustion and promoted NK cell-dependent tumor immunity in several tumor-bearing mouse models. Furthermore, blockade of TIGIT resulted in potent tumor-specific T cell immunity in an NK cell-dependent manner, enhanced therapy with antibody to the PD-1 ligand PD-L1 and sustained memory immunity in tumor re-challenge models. This work demonstrates that TIGIT constitutes a previously unappreciated checkpoint in NK cells and that targeting TIGIT alone or in combination with other checkpoint receptors is a promising anti-cancer therapeutic strategy.

Q. (2016). Raman spectroscopy of atomically thin two-dimensional magnetic iron phosphorus trisulfide (FePS3) crystals. 2D Materials, 3(3), 031009-.

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More often than not, a multimedia data described by multiple features, such as color and shape features, can be naturally decomposed of multi-views. Since multi-views provide complementary information to each other, great endeavors have been dedicated by leveraging multiple views instead of a single view to achieve the better clustering performance. To effectively exploit data correlation consensus among multi-views, in this paper, we study subspace clustering for multi-view data while keeping individual views well encapsulated. For characterizing data correlations, we generate a similarity matrix in a way that high affinity values are assigned to data objects within the same subspace across views, while the correlations among data objects from distinct subspaces are minimized. Before generating this matrix, however, we should consider that multi-view data in practice might be corrupted by noise. The corrupted data will significantly downgrade clustering results. We first present a novel objective function coupled with an angular based regularizer. By minimizing this function, multiple sparse vectors are obtained for each data object as its multiple representations. In fact, these sparse vectors result from reaching data correlation consensus on all views. For tackling noise corruption, we present a sparsity-based approach that refines the angular-based data correlation. Using this approach, a more ideal data similarity matrix is generated for multi-view data. Spectral clustering is then applied to the similarity matrix to obtain the final subspace clustering. Extensive experiments have been conducted to validate the effectiveness of our proposed approach.

The grain refinement of 2-8 wt.% Y addition in as-cast Mg-Y binary alloys has been investigated. The results show that the microstructure of as-cast Mg-Y alloys consists of α-Mg matrix and Mg24Y5phase. Mg24Y5can become the effective nucleation core of α-Mg, and refine the grain size of the alloys. The ultimate tensile strength of as-cast Mg-5Y alloy is 180MPa at room temperature. Mg-5Y alloy can be a basis for developing light structural materials.

Dye-sensitized solar cells (DSSCs) are the most promising low-cost photovoltaic devices. Whereas, the absorption bands of most organic sensitizers, the most vital component in DSSCs, are limited to a relatively narrow visible range. To obtain efficient sensitizer, a series of D–A−π–A metal-free dyes have been designed based on one of the best sensitizers WS-9 by modifying auxiliary acceptor and characterized theoretically. The results illustrate that introduction of auxiliary heterocycle acceptor is revealed to very narrow band gap (HOMO–LUMO), leading to an obvious red-shifted broad near-infrared absorption band in the range of 750–1950 nm compared to WS-9 (536 nm). The critical parameters in close connection with the short-circuit current density (J sc), open circuit voltage (V oc), including singlet excited state lifetime (τ), total dipole moments (μnormal), the conduction band of edge of the semiconductor substrate (ΔE CB), and regeneration driving forces (ΔG reg) are superior to those of WS-9. Therefore, these novel sensitizers would be a promising candidate for improving the performance of the DSSCs.

Skyline analysis is a key in a wide spectrum of real applications involving multi-criteria optimal decision making. In recent years, a considerable amount of research has been contributed on efficient computation of skyline probabilities over uncertain environment. Most studies if not all, assume uncertainty lies only in attribute values. To the extent of our knowledge, only one study addresses the skyline probability computation problem in scenarios where uncertainty resides in attribute preferences, instead of values. However this study takes a problematic approach by assuming independent object dominance, which we find is not always true in uncertain preference scenarios. In fact this assumption has already been shown to be not necessarily true in uncertain value scenarios. Motivated by this, we revisit the skyline probability computation over uncertain preferences in this paper.We first show that the problem of skyline probability computation over uncertain preferences is P-complete. Then we propose efficient exact and approximate algorithms to tackle this problem. While the exact algorithm remains exponential in the worst case, our experiments demonstrate its efficiency in practice. The approximate algorithm achieves -approximation by the confidence (1 − δ) with time complexity O(dn 1 2 ln 1 δ ), where n is the number of objects and d is the dimensionality. The efficiency and effectiveness of our methods are verified by extensive experimental results on real and synthetic data sets.