In this paper, we study the heat engine where a charged AdS black hole surrounded by dark energy is the working substance and the mechanical work is done via the
PdV
term in the first law of black ...hole thermodynamics in the extended phase space. We first investigate the effects of a kind of dark energy (quintessence field in this paper) on the efficiency of the RN-AdS black holes as the heat engine defined as a rectangular closed path in the
P
–
V
plane. We get the exact efficiency formula and find that the quintessence field can improve the heat engine efficiency, which will increase as the field density
ρ
q
grows. At some fixed parameters, we find that a larger volume difference between the smaller black holes(
V
1
) and the bigger black holes(
V
2
) will lead to a lower efficiency, while the bigger pressure difference
P
1
-
P
4
will make the efficiency higher, but it is always smaller than 1 and will never be beyond the Carnot efficiency, which is the maximum value of the efficiency constrained by thermodynamics laws; this is consistent to the heat engine in traditional thermodynamics. After making some special choices for the thermodynamical quantities, we find that the increase of the electric charge
Q
and the normalization factor
a
can also promote the heat engine efficiency, which would infinitely approach the Carnot limit when
Q
or
a
goes to infinity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With the rise and development of deep learning, computer vision has been tremendously transformed and reshaped. As an important research area in computer vision, scene text detection and recognition ...has been inevitably influenced by this wave of revolution, consequentially entering the era of deep learning. In recent years, the community has witnessed substantial advancements in mindset, methodology and performance. This survey is aimed at summarizing and analyzing the major changes and significant progresses of scene text detection and recognition in the deep learning era. Through this article, we devote to: (1) introduce new insights and ideas; (2) highlight recent techniques and benchmarks; (3) look ahead into future trends. Specifically, we will emphasize the dramatic differences brought by deep learning and remaining grand challenges. We expect that this review paper would serve as a reference book for researchers in this field. Related resources are also collected in our Github repository (
https://github.com/Jyouhou/SceneTextPapers
).
Abstract
In the wake of the 2014 judicial reforms, are Chinese judges in most circumstances free in their decision-making? Based primarily on interviews with judges, this article argues that although ...a truncated hierarchy has led to increased judicial autonomy, the state maintains its tight grip over judges. In its new form, the state’s control is more indirect, external, ex post, diffused, and ideological. It allows the state to closely monitor judges’ entire handling of cases (hence the designation “panoptic”). It has some similarities with, yet fundamentally differs from, existing patterns in authoritarian states. While judges’ accountability continues to be largely a bureaucratic matter, this Chinese form of control has nonetheless been effective at a time of soaring caseloads, a slimmed-down judiciary, and increasing insistence on legitimacy. This article seeks to deepen understanding of developments in Chinese courts and, more widely, judicial politics in authoritarian states.
This study attempts to document the nexus between weather, COVID-19 outbreak in Wuhan and the Chinese economy. We used daily average temperature (hourly data), daily new confirmed cases of COVID-19 ...in Wuhan, and RMB (Chinese currency) exchange rate to represent the weather, COVID-19 outbreak and the Chinese economy, respectively. The methodology of Wavelet Transform Coherence (WTC), Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) is employed to analyze the daily data collected from 21st January 2020 to 31st March 2020. The results have revealed a significant coherence between the series at different time-frequency combinations. The overall results suggest the insignificance of an increase in temperature to contain or slow down the new COVID-19 infections. The RMB exchange rate and the COVID-19 showed an out phase coherence at specific time-frequency spots suggesting a negative but limited impact of the COVID-19 outbreak in Wuhan on the Chinese export economy. Our results are contrary to many earlier studies which suggest a significant role of temperature in slowing down the COVID-19 spread. These results can have important policy implications for the containment of COVID-19 spread and macro-economic management with respect to changes in the weather.
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•We have examined the covariance nexus between temperature, COVID-19 and exchange rate in Wuhan City, China.•Novel methods of Wavelet Transform Coherence, Partial and Multiple Wavelet Coherence are employed for analysis.•Temperature played no role in the containment of COVID-19 in Wuhan.•COVID-19 outbreak in Wuhan had a negative but limited impact on RMB exchange rate against USD during our observation period.
We investigate the valuation of exchange options when the market is affected by changing economic conditions as well as liquidity risks. The volatility and expected returns of both stocks are assumed ...to be controlled by a continuous‐time Markov chain to reflect the effects of varying economic conditions, and a liquidity discounting factor is employed to capture the impact of market liquidity on stock prices. Once the model has been established, we construct a risk‐neutral measure with the use of regime‐switching Esscher transform, and the characteristic function is then derived in an analytical form, so that a closed‐form formula for exchange options can be presented. We further analyze the effects of the two considered factors on exchange option prices numerically.
We perform a comprehensive study of the dark energy equation of state (EoS) utilizing the model-independent Gaussian processes (GP). Using a combination of the Union 2.1 data set, the 30 newly added ...H(z) cosmic chronometer data points and Planck’s shift parameter, we modify the usual GaPP code and provide a tighter constraint on the dark energy EoS than the previous literature about GP reconstructions. Subsequently, we take the “controlling variable method ” to investigate directly the effects of the variable matter density parameter Ωm0, variable cosmic curvature Ωk0, and variable Hubble constant H0 on the dark energy EoS. We find that too small or large Ωm0, Ωk0, and H0 are all disfavored by our GP reconstructions based on current cosmological observations. Subsequently, we find that variables Ωm0 and Ωk0 affect the reconstructions of the dark energy EoS but hardly affect the reconstructions of the normalized comoving distance D(z) and its derivatives D′(z) and D′′(z). However, variable H0 affects the reconstructions of the dark energy EoS by affecting obviously those of D(z), D′(z), and D′′(z). Furthermore, we find that the results of our reconstructions support substantially the recent local measurement of H0 reported by Riess et al.
Recently, a great many deep convolutional neural network (CNN)-based methods have been proposed for hyperspectral image (HSI) classification. Although the proposed CNN-based methods have the ...advantages of spatial feature extraction, they are difficult to handle the sequential data with and CNNs are not good at modeling the long-range dependencies. However, the spectra of HSI are a kind of sequential data, and HSI usually contains hundreds of bands. Therefore, it is difficult for CNNs to handle HSI processing well. On the other hand, the Transformer model, which is based on an attention mechanism, has proved its advantages in processing sequential data. To address the issue of capturing relationships of sequential spectra in HSI in a long distance, in this study, Transformer is investigated for HSI classification. Specifically, in this study, a new classification framework titled spatial-spectral Transformer (SST) is proposed for HSI classification. In the proposed SST, a well-designed CNN is used to extract the spatial features, and a modified Transformer (a Transformer with dense connection, i.e., DenseTransformer) is proposed to capture sequential spectra relationships, and multilayer perceptron is used to finish the final classification task. Furthermore, dynamic feature augmentation, which aims to alleviate the overfitting problem and therefore generalize the model well, is proposed and added to the SST (SST-FA). In addition, to address the issue of limited training samples in HSI classification, transfer learning is combined with SST, and another classification framework titled transferring-SST (T-SST) is proposed. At last, to mitigate the overfitting problem and improve the classification accuracy, label smoothing is introduced for the T-SST-based classification framework (T-SST-L). The proposed SST, SST-FA, T-SST, and T-SST-L are tested on three widely used hyperspectral datasets. The obtained results reveal that the proposed models provide competitive results compared to the state-of-the-art methods, which shows that the concept of Transformer opens a new window for HSI classification.
Backscattering suppression in silicon-on-insulator (SOI) is one of the central issues to reduce energy loss and signal distortion, enabling for capability improvement of modern information processing ...systems. Valley physics provides an intriguing way for robust information transfer and unidirectional coupling in topological nanophotonics. Here we realize topological transport in a SOI valley photonic crystal slab. Localized Berry curvature near zone corners guarantees the existence of valley-dependent edge states below light cone, maintaining in-plane robustness and light confinement simultaneously. Topologically robust transport at telecommunication is observed along two sharp-bend interfaces in subwavelength scale, showing flat-top high transmission of ~10% bandwidth. Topological photonic routing is achieved in a bearded-stack interface, due to unidirectional excitation of valley-chirality-locked edge state from the phase vortex of a nanoscale microdisk. These findings show the prototype of robustly integrated devices, and open a new door towards the observation of non-trivial states even in non-Hermitian systems.
With the rapid growth of new-energy batteries and metallurgical industry, water pollution caused by toxic heavy-metals from these sectors has increased to a new level, which is seriously threating ...the eco-system and human health. Thus, the effective disposal of metal-bearing water has become a vital requirement. To resolve such a problem, developing eco-friendly biochar-based adsorbents has become urgent. As an eco-friendly material, biochar has attracted increasingly attention due to its low-cost, high surface area and abundant functional groups. However, pristine biochar also shows low adsorption efficiency for heavy-metals. Consequently, improving its adsorption efficiency via modification is considered as one of most effective techniques. In the last 15 years, various methods were proposed to modify biochar. However, review articles on the usage of modified-biochars for heavy-metals adsorption are unavailable. To summarize these newly-developed modification methods including organic-modified, nonmetal-modified, metal-modified, metal/organic-modified, and metal/mineral-modified, this review will focus on the preparation, characterizations and applications of modified-biochar adsorbents (MBAs) for heavy-metals. More emphasis will be on the adsorption of MBAs for heavy-metals in a single-metal, mixed multi-metal, and mixed metal/organic matter solution systems. Meanwhile, the adsorption mechanism of MBAs for Cr(VI), Cd (II), Pb(II) and Cu(II) will be highlighted. It is found that the adsorption mechanism of MBAs in different mixed multi-metal solution systems is complicated and competitive adsorption is inevitable. Typically, the effect of functional groups from MBAs on heavy-metals adsorption is diverse, more studies are required in the future. Finally, the present state and future perspective will be discussed.
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•Modified-biochar for heavy-metals adsorption in various systems was reviewed.•Competition among heavy-metals in mixed multi-metal system is a key process.•Functional groups on MBAs surface play a key role in heavy-metals adsorption.•Biochar modification is a vital way to rise its sorption ability for heavy-metals.•Adsorption mechanism of MBAs for heavy-metals in mixed solution system is diverse.
Recent research in topological photonics has not only proposed and realized novel topological phenomena such as one‐way broadband propagation and robust transport of light, but also designed and ...fabricated photonic devices with high‐performance indexes, which are immune to fabrication errors such as defects or disorders. Photonic crystals, which are periodic optical structures with the advantages of good light field confinement and multiple adjusting degrees of freedom, provide a powerful platform to control the flow of light. With the topology defined in the reciprocal space, photonic crystals have been widely used to reveal different topological phases of light and demonstrate topological photonic functionalities. This review presents the physics of topological photonic crystals with different dimensions, models, and topological phases. The design methods of topological photonic crystals are introduced. Furthermore, the applications of topological photonic crystals in passive and active photonics are reviewed. These studies pave the way for applying topological photonic crystals in practical photonic devices.
For the ability to improve the robustness of photonic devices under different kinds of defects, topological photonic crystals have attracted increasing attention and have been used as a platform for studying intriguing physical phenomena and realizing novel functional devices. This review provides an introduction to the fundamental physics, optical design, and promising applications of topological photonic crystals in different dimensions.
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