A New Two-Dimensional Functional Material with Desirable Bandgap and Ultrahigh Carrier Mobility

Two-dimensional (2D) semiconductors with direct and modest bandgap and ultrahigh carrier mobility are highly desired functional materials for nanoelectronic applications. Herein, we predict that monolayer CaP3 is a new 2D functional material that possesses not only a direct bandgap of 1.15 eV (based on HSE06 computation), and also a very high electron mobility up to 19930 cm2 V-1 s-1, comparable to that of monolayer phosphorene. More remarkably, contrary to the bilayer phosphorene which possesses dramatically reduced carrier mobility compared to its monolayer counterpart, CaP3 bilayer possesses even higher electron mobility (22380 cm2 V-1 s-1) than its monolayer counterpart. The bandgap of 2D CaP3 can be tuned over a wide range from 1.15 to 0.37 eV (HSE06 values) through controlling the number of stacked CaP3 layers. Besides novel electronic properties, 2D CaP3 also exhibits optical absorption over the entire visible-light range. The combined novel electronic, charge mobility, and optical properties render 2D CaP3 an exciting functional material for future nanoelectronic and optoelectronic applications

Ranking reputation and quality in online rating systems

How to design an accurate and robust ranking algorithm is a fundamental problem with wide applications in many real systems. It is especially significant in online rating systems due to the existence of some spammers. In the literature, many well-performed iterative ranking methods have been proposed. These methods can effectively recognize the unreliable users and reduce their weight in judging the quality of objects, and finally lead to a more accurate evaluation of the online products. In this paper, we design an iterative ranking method with high performance in both accuracy and robustness. More specifically, a reputation redistribution process is introduced to enhance the influence of highly reputed users and two penalty factors enable the algorithm resistance to malicious behaviors. Validation of our method is performed in both artificial and real user-object bipartite networks

Learning biological neuronal networks with artificial neural networks: neural oscillations

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of first-principles-based artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by neural circuits in the brain. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.Comment: 18 pages, 8 figure

A Survey on Approximate Multiplier Designs for Energy Efficiency: From Algorithms to Circuits

Given the stringent requirements of energy efficiency for Internet-of-Things edge devices, approximate multipliers, as a basic component of many processors and accelerators, have been constantly proposed and studied for decades, especially in error-resilient applications. The computation error and energy efficiency largely depend on how and where the approximation is introduced into a design. Thus, this article aims to provide a comprehensive review of the approximation techniques in multiplier designs ranging from algorithms and architectures to circuits. We have implemented representative approximate multiplier designs in each category to understand the impact of the design techniques on accuracy and efficiency. The designs can then be effectively deployed in high-level applications, such as machine learning, to gain energy efficiency at the cost of slight accuracy loss.Comment: 38 pages, 37 figure

Data from a comparative proteomic analysis of tumor-derived lung-cancer CD105+ endothelial cells

AbstractIncreasing evidence indicates that tumor-derived endothelial cells (TECs) are more relevant for the study of tumor angiogenesis and for screening antiangiogenic drugs than normal ECs (NECs). In this data article, high-purity (>98%) primary CD105+ NECs and TECs purified from a mouse Lewis lung carcinoma model bearing 0.5cm tumors were identified using 2D-PAGE and Matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS). All the identified proteins were categorized functionally by Gene Ontology (GO) analysis, and gene-pathway annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, protein–protein interaction networks were also built. The proteomics and bioinformatics data presented here provide novel insights into the molecular characteristics and the early modulation of the TEC proteome in the tumor microenvironment

Symmetry-breaking-induced nonlinear optics at a microcavity surface

Second-order nonlinear optical processes lie at the heart of many applications in both classical and quantum regimes1,2,3. Inversion symmetry, however, rules out the second-order nonlinear electric-dipole response in materials widely adopted in integrated photonics (for example, SiO_2, Si and Si_3N_4). Here, we report nonlinear optics induced by symmetry breaking at the surface of an ultrahigh-Q silica microcavity under a sub-milliwatt continuous-wave pump. By dynamically coordinating the double-resonance phase matching, a second harmonic is achieved with an unprecedented conversion efficiency of 0.049% W^(−1), 14 orders of magnitude higher than that of the non-enhancement case. In addition, the nonlinear effect from the intrinsic symmetry breaking at the surface can be identified unambiguously, with guided control of the pump polarization and the recognition of the second-harmonic mode distribution. This work not only extends the emission frequency range of silica photonic devices, but also lays the groundwork for applications in ultra-sensitive surface analysis

Selection and evaluation of phosphate-solubilizing bacteria from grapevine rhizospheres for use as biofertilizers

Phosphate-solubilizing bacteria (PSB) have the ability to solubilize insoluble phosphorus (P) and release soluble P. Extensive research has been performed with respect to PSB isolation from the rhizospheres of various plants, but little is known about the prevalence of PSB in the grapevine rhizosphere. In this study, we aimed to isolate and identify PSB from the grapevine rhizosphere in five vineyards of Northwest China, to characterize their plant-growth-promoting (PGP) traits, evaluate the effect of stress on their phosphate-solubilizing activity (PSA), and test their ability to stimulate the growth of Vitis vinifera L. cv. Cabernet Sauvignon. From the vineyard soils, 66 PSB isolates were screened, and 10 strains with high PSA were identified by 16S rRNA sequencing. Sequence analysis revealed that these 10 strains belonged to 4 genera and 5 species: Bacillus aryabhattai, B. megaterium, Klebsiella variicola, Stenotrophomonas rhizophila, and Enterobacter aerogenes. The selected PSB strains JY17 (B. aryabhattai) and JY22 (B. aryabhattai) were positive for multiple PGP traits, including nitrogen fixation and production of indole acetic acid (IAA), siderophores, 1-aminocyclopropane-1-carboxylate (ACC) deaminase, chitinase, and protease. JY17 and JY22 showed strong PSA under stress conditions of high pH, high salt, and high temperature. Therefore, these two isolates can be used as biofertilizers in saline-alkaline soils. The inoculation with PSB significantly facilitated the growth of V. vinifera cv. Cabernet Sauvignon under greenhouse conditions. Use of these PSB as biofertilizers will increase the available P content in soils, minimize P-fertilizer application, reduce environmental pollution, and promote sustainable agriculture

Extraosseous (extramedullary) plasmacytomas: a clinicopathologic and immunophenotypic study of 32 Chinese cases

<p>Abstract</p> <p>Background</p> <p>Extraosseous plasmacytoma, so called extramedullary plasmacytoma (EMP) is relatively rare in China. The aim was investigate the clinicopathologic features of EMP and the role of Immunophenotype and genotype detection in diagnosis of EMP.</p> <p>Methods</p> <p>Thirty-two cases of EMP were investigated retrospectively by histopathology, immunophenotype, genotype and survival analysis.</p> <p>Results</p> <p>Clinically, the mean age of the patients was 53.4. Most of the patients received no treatment after the diagnosis was established, and the prognosis was relatively poor. Histologically, in 40% of the cases, the neoplastic cells were grade II or III. The neoplastic cells expressed one or more PC associated antigens. The immunophenotype of EMP and inflammation of sinonasal regions with numerous PC infiltrations were compared and showed some difference in expression of CD45, CD27, CD44v6 and Bcl-2 as well. Ig light chain restriction was detected in 87.5% of the cases.</p> <p>Conclusions</p> <p>we described 32 Chinese cases of EMP, compare with that reported in the literature, some differences are presented, including higher percentage of grade II and III cases, clinically inconsistent treatment and management as well as poor outcome of the disease.</p