Two-dimensional crystals are emerging materials for nanoelectronics. Development of the field requires candidate systems with both a high carrier mobility and, in contrast to graphene, a sufficiently ...large electronic bandgap. Here we present a detailed theoretical investigation of the atomic and electronic structure of few-layer black phosphorus (BP) to predict its electrical and optical properties. This system has a direct bandgap, tunable from 1.51 eV for a monolayer to 0.59 eV for a five-layer sample. We predict that the mobilities are hole-dominated, rather high and highly anisotropic. The monolayer is exceptional in having an extremely high hole mobility (of order 10,000 cm(2) V(-1) s(-1)) and anomalous elastic properties which reverse the anisotropy. Light absorption spectra indicate linear dichroism between perpendicular in-plane directions, which allows optical determination of the crystalline orientation and optical activation of the anisotropic transport properties. These results make few-layer BP a promising candidate for future electronics.
Background and Aims
Hepatic macrophages can be activated by many factors such as gut‐derived bacterial components and factors released from damaged hepatocytes. Macrophage polarization toward a ...proinflammatory phenotype (M1) represents an important event in the disease progression of nonalcoholic fatty liver disease (NAFLD). However, the underlying molecular mechanisms remain incompletely understood. Exosomes have been identified as important mediators for cell–cell communication by transferring various biological components such as microRNAs (miRs), proteins, and lipids. The role of exosomes in crosstalk between hepatocytes and macrophages in disease progression of NAFLD is yet to be explored.
Approach and Results
In the present study, we reported that lipotoxic injury–induced release of hepatocyte exosomes enriched with miR‐192‐5p played a critical role in the activation of M1 macrophages and hepatic inflammation. Serum miR‐192‐5p levels in patients with NAFLD positively correlated with hepatic inflammatory activity score and disease progression. Similarly, the serum miR‐192‐5p level and the number of M1 macrophages, as well as the expression levels of the hepatic proinflammatory mediators, were correlated with disease progression in high‐fat high‐cholesterol diet–fed rat models. Lipotoxic hepatocytes released more miR‐192‐5p‐enriched exosomes than controls, which induced M1 macrophage (cluster of differentiation 11b–positive CD11b+/CD86+) activation and increase of inducible nitric oxide synthase, interleukin 6, and tumor necrosis factor alpha expression. Furthermore, hepatocyte‐derived exosomal miR‐192‐5p inhibited the protein expression of the rapamycin‐insensitive companion of mammalian target of rapamycin (Rictor), which further inhibited the phosphorylation levels of Akt and forkhead box transcription factor O1 (FoxO1) and resulted in activation of FoxO1 and subsequent induction of the inflammatory response.
Conclusions
Hepatocyte‐derived exosomal miR‐192‐5p plays a critical role in the activation of proinflammatory macrophages and disease progression of NAFLD through modulating Rictor/Akt/FoxO1 signaling. Serum exosomal miR‐192‐5p represents a potential noninvasive biomarker and therapeutic target for nonalcoholic steatohepatitis.
Ultrafast‐response (20 μs) UV detectors, which are visible‐blind and self‐powered, in devices where an n‐type ZnO nanowire partially lies on a p‐type GaN film, are demonstrated. Moreover, a ...CdSe‐nanowire red‐light detector powered by a nanoscale ZnO/GaN photovoltaic cell is also demonstrated, which extends the device function to a selective multiwavelength photodetector and shows the function of an optical logical AND gate.
The vibration signals of faulty rotating machinery are typically nonstationary, nonlinear, and mixed with abundant compounded background noise. To extract the potential excitations from the observed ...rotating machinery, signal demodulation and time-frequency analysis are indispensable. This work proposes a novel particle swarm optimization-based variational mode decomposition method, which adopts the minimum mean envelope entropy to optimize the parameters (<inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">K</tex-math></inline-formula>) in the existing variational mode decomposition. The proposed fault-detection framework separated the observed vibration signals into a series of intrinsic modes. A certain number of the intrinsic modes are then selected by means of the Hilbert transform-based square envelope spectral kurtosis. Subsequently, in this study, the feature representations were reconstructed via the selected intrinsic modes; then, the envelope spectra of the real faulty conditions were generated in the rotating machinery. To verify the performance of the proposed method, a testbed platform of a gearbox with a combination of different faults was implemented. The experimental results demonstrated that the proposed method represented the patterns of the fault frequency more explicitly than the available empirical mode decomposition, the local mean decomposition, and the wavelet package transform method.
Oil-immersed transformer is one of the most important electrical equipment in power distribution and transmission systems. Dielectric response method is a well-recognized method to diagnose the ...insulation defect of oil-immersed transformers. However, the applicability of this method is restricted due to the long testing time. Under some special field conditions, the method is not even applicable. In this article, a novel testing method is proposed based on the following ideas: first, the low-frequency dielectric parameters are extracted by using mixing frequency excitation; then, parameters of the extended Debye equivalent circuit are determined based on cuckoo search optimization algorithm; finally, the specific parameters are used to the established simulation model and obtain the recovery voltage curve. Compared with the traditional method, the testing time of the proposed method has been greatly reduced. Besides, dielectric parameters in both frequency domain and time domain can be obtained simultaneously. The applicability of the proposed method is verified by the dielectric response measurements on a laboratory transformer and a real power transformer in a substation.
Background
Obesity may impact surgical outcomes of gastrectomy. Whether visceral fat area (VFA) is a better obesity parameter than body mass index (BMI) is still controversial. The aim of this study ...is to compare the accuracy and effectiveness of VFA and BMI in predicting the short-term surgical outcomes of gastrectomy.
Methods
Patients who were diagnosed with gastric cancer were measured for BMI and VFA preoperatively and then divided into a VFA-H (VFA-high) group and VFA-L (VFA-low) group, at the cutoff point of 100 cm
2
, and a BMI-H (BMI-high) group and BMI-L (BMI-low) group, at the cutoff point of 25 kg/m
2
. The short-term surgical outcomes were compared between the different groups.
Results
In total, 276 patients were enrolled in this study; 55 (19.9%) patients were classified into the BMI-H group, and 122 (44.2%) patients were classified into the VFA-H group. There was a significant correlation between BMI and VFA (
r
= 0.652,
p
< 0.001). Compared with the VFA-L group, the VFA-H group had a higher incidence of postoperative complications (31.1% vs. 13.0%;
p
< 0.001), longer operation duration (270.0 (235.0–305.0) vs. 255.0 (223.8–295.0),
p
= 0.046), and more blood loss (100.0 (100.0–150.0) vs. 80.0 (80.0–100.0),
p
< 0.001), while the BMI-H group had more blood loss than the BMI-L group (100.0 (100.0–120.0) vs. 100.0(80.0–100.0),
p
= 0.006). Logistic regression showed that VFA was an independent risk factor for postoperative complications (odds ratio 2.813, 95% CI 1.523–5.194;
p
= 0.001).
Conclusion
For gastric cancer patients, VFA is superior to BMI in accurately and effectively illuminating the impact of obesity on short-term surgical outcomes.
Trial Registration
Clinicaltrials.gov
: NCT02800005.
Few-shot semantic segmentation aims to segment novel-class objects in a query image with only a few annotated examples in support images. Although progress has been made recently by combining ...prototype-based metric learning, existing methods still face two main challenges. First, various intra-class objects between the support and query images or semantically similar inter-class objects can seriously harm the segmentation performance due to their poor feature representations. Second, the latent novel classes are treated as the background in most methods, leading to a learning bias, whereby these novel classes are difficult to correctly segment as foreground. To solve these problems, we propose a dual-branch learning method. The class-specific branch encourages representations of objects to be more distinguishable by increasing the inter-class distance while decreasing the intra-class distance. In parallel, the class-agnostic branch focuses on minimizing the foreground class feature distribution and maximizing the features between the foreground and background, thus increasing the generalizability to novel classes in the test stage. Furthermore, to obtain more representative features, pixel-level and prototype-level semantic learning are both involved in the two branches. The method is evaluated on PASCAL-5 i 1-shot, PASCAL-5 i 5-shot, COCO-20 i 1-shot, and COCO-20 i 5-shot, and extensive experiments show that our approach is effective for few-shot semantic segmentation despite its simplicity.
The magnon blockade effect in a parity‐time (PT) symmetric‐like three‐mode cavity magnomechanical system involving the magnon–photon and magnon–phonon interactions is investigated. In the broken and ...unbroken PT‐symmetric regions, the second‐order correlation function is calculated analytically and numerically, respectively, and the optimal value of detuning is further determined. By adjusting different system parameters, the different blockade mechanisms are studied and it is found that the perfect magnon blockade effect can be observed under the weak parameter mechanism. This work paves a way to achieve the magnon blockade in experiment.
Based on a parity‐time symmetric‐like three‐mode cavity magnomechanical system, a new type of magnon blockade scheme is proposed. The magnon blockade effect in different blockade mechanisms is discussed. It is found that the perfect magnon blockade effect can be obtained under the weak parameter mechanism. This work paves a way to achieve the magnon blockade in experiment.
In school, a teacher plays an important role in various classroom teaching patterns. Likewise to this human learning activity, the learning using privileged information (LUPI) paradigm provides ...additional information generated by the teacher to ’teach’ learning models during the training stage. Therefore, this novel learning paradigm is a typical Teacher–Student Interaction mechanism. This paper is the first to present a random vector functional link (RVFL) network based on the LUPI paradigm, called RVFL+. The novel RVFL+ incorporates the LUPI paradigm that can leverage additional source of information into the RVFL, which offers an alternative way to train the RVFL. Rather than simply combining two existing approaches, the newly-derived RVFL+ fills the gap between classical randomized neural networks and the newfashioned LUPI paradigm. Moreover, the proposed RVFL+ can perform in conjunction with the kernel trick for highly complicated nonlinear feature learning, termed KRVFL+. Furthermore, the statistical property of the proposed RVFL+ is investigated, and the authors present a sharp and high-quality generalization error bound based on the Rademacher complexity. Competitive experimental results on 14 real-world datasets illustrate the great effectiveness and efficiency of the novel RVFL+ and KRVFL+, which can achieve better generalization performance than state-of-the-art methods.
•This paper presents a new RVFL+, which is an alternative way to train the RVFL.•The RVFL+ bridges the gap between randomized neural networks and the LUPI.•The KRVFL+ is also proposed in order to handle highly nonlinear relationships.•This paper provides a theoretical guarantee using the Rademacher complexity.•Performances are evaluated on 14 real datasets using state-of-the-art methods.
Recently, memory-based methods have exhibited remarkable performance in Video Object Segmentation (VOS) by employing non-local pixel-wise matching between the query and memory. Nevertheless, these ...methods suffer from two limitations: 1) Non-local pixel-wise matching can result in the incorrect segmentation of background distractor objects, and 2) memory features with substantial temporal redundancy consume significant computing resources and reduce the inference speed. To address the limitations, we first propose a local attention mechanism to suppress background features, and we introduce a novel training framework based on contrast learning to ensure the network learns reliable and robust pixel-wise correspondence between query and memory. We adaptively determine whether to update the memory based on the variation of foreground objects. Next, we propose a dynamic memory bank, which utilizes a lightweight and differentiable soft modulation gate to determine the number of memory features to remove along the temporal dimension. This allows efficient and flexible management of memory features. Our network achieves competitive results (e.g., 92.1% on DAVIS 2016 val, 87.6%/81.3% on DAVIS 2017 val/test, 87.0% on YouTube-VOS 2018 val) compared with the state-of-the-art methods while maintaining a faster inference speed of 25+FPS. Moreover, our network demonstrates a favorable balance between performance and speed when dealing with the long-time video dataset.
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