Abstract In recent years, the power conversion efficiencies of halide perovskite solar cells (PSCs) have reached 25.7%. Further commercialization puts forward higher requirements for stability PSCs under different stresses. Current research on predominantly focuses investigating effects temperature, humidity, oxygen, ultraviolet light, and electrical bias stress, while reverse has been poorly studied among many factors. When large‐area application panels occurs, shading effect local hot...

Network embedding, aiming to project a network into low-dimensional space, is increasingly becoming focus of research. Semi-supervised embedding takes advantage labeled data, and has shown promising performance. However, existing semi-supervised methods would get unappealing results in the completely-imbalanced label setting where some classes have no nodes at all. To alleviate this, we propose novel method, termed Relaxed Similarity Dissimilarity Embedding (RSDNE). Specifically, benefit...

A rational design of low bandgap formamidine tin based perovskite solar cell is conducted via device simulation. The parameters that influence the performance are comprehensively investigated and optimized for higher performance.

A nickel foam with a three-dimensional reticulated structure has been prepared by an electrodeposition technique. The microcrystalline of the layer was maintained following treatment in air at 600°C for 4 min. Sintering reductive decomposed NH3 atmosphere 40 min, either 980 or 850°C, transformed product into compact crystal flat surface and large grains.

Speech separation has been employed in important applications such as automatic speech, paralinguistics, speech recognition, hearing aids, and human-machine interactions. In recent years, deep neural networks have widely used for music separation. Some of these breakthrough successful models based on embedding vectors proposed, clustering. this paper, we propose a node encoder Squash-norm clustering (ESDC) an enhanced discriminative learning framework by combining encoder, Squash-norm, (DC)....

The electromagnetic theory is used in order to characterize the polarization processes glasses. change free energy owing phase transformation of glasses presence an electric field . analysis shows that may be reduced or enhanced by depending on ratio dielectric constants old and new phases. This means can either stimulate inhibit nucleation process. qualitatively consistent with experimental results. Furthermore, we extend it all materials upon application field. These results suggest a...

In this paper, we introduce a discriminative vector learning method and apply it to single-channel speech separation. First, samples are transformed into vectors using two backbone networks. These easily separated by simple clustering algorithms. Among them, with lower similarity different clusters, while in the same cluster have higher similarity. This property is very important image segmentation, audio separation, data problems. our work, design network architecture improve...

Abstract During natural evolution, the spindles often scale with cell sizes to orchestrate accurate chromosome segregation. Whether in cancer when constraints on genome integrity are relaxed, cells may evolve spindle confer other advantages has not been investigated. Using invasion as a selective pressure vitro , we found that highly metastatic clone displays lengthened metaphase spindle, faster elongation correlates transiently elevated speed of migration. We kinesin-5 is upregulated this...

Deep learning has increasingly been employed to identify minerals. However, deep can only be used minerals in the distribution of training set, while any mineral outside spectrum set is inevitably categorized erroneously within a predetermined class from set. To solve this problem, study introduces approach that amalgamates One-Class Support Vector Machines (OCSVM) with ResNet architecture for out-of-distribution detection. Initially, undergoes using comprising well-defined Subsequently,...

Multi-domain optical network provisioning is a key focus area as users continue to demand scalable bandwidth services across wider regions. To date, range of distributed schemes have been proposed achieve lightpath routing domain boundaries. In general, these solutions rely upon hierarchical and strategies are mostly heuristics based. As such, it difficult gauge their true load-carrying capacity effectiveness. Hence in order address this concern, effort proposes formal optimization-based...

In this work, we developed a new model of chat robot with facial expression interaction. Different from the voice assistant that only interacts text and voice, let interact user specific role play. A text-sentiment-analysis network is added to system recognize emotion response sentences. Moreover, created 3D-constructed anime character "Midoriko" have image more vivid. Our goal provide better experience users. The technical parts work based on neural techniques.

MgO–Al2O3–SiO2 (MAS) cordierite based glass ceramics were prepared by volume crystallisation. X-ray diffraction, Scanning electron microscopy and Energy diffraction scanning used to investigate crystallisation behaviour the influence of P2O5 on microstructure MAS ceramics. The results showed that P5+ could promote phase separation was divided into two areas, such as Mg4Al2Ti9O25 containing area at <900°C. Mg3(PO4)2 in both advantageous precipitation μ cordierite, which further transformed α...

In this paper, we propose an estimated high frequency compensated (EHFC) algorithm for super resolution images. It is based on iterative back projection (IBP) method combined with models according to different applications. The proposed not only improves the quality of enlarged images produced by zero-order, bilinear, or bicubic interpolation methods, but also accelerates convergence speed IBP. experiments general tested images, EHFC can increase 1 ~ 6.5 times and gets 0.4 0.7 dB PSNR gain....

This work proposes an emotion recognition system by adopting facial expression and speech tonality on deep learning networks. Both convolutional neural networks long short term memory are used for feature training. The two features can be trained together to acquire higher accuracy. Moreover, Structure Evolution which is inspired the Genetic Algorithm added optimize parameters in model. experimental results show joint model optimized surpasses single at least 10% outperforms state-of-the-art over 1%.

The resistivity behaviour of high porosity nickel foam as a function has been investigated experimentally. results were compared with number empirical and theoretical models. It was found that new model based on structural properties gave the closest fit to experimental data. This provides convenient means controlling porous metals in production thus enables manufacture better electrodes.