On the equivalence of the Nernst theorem and its consequence

One general consequence of the Nernst theorem is derived, i.e., the various heat capacities of a thermodynamic system under different constraints approach zero as the temperature approaches absolute zero. The temperature dependence of the heat capacity of any thermodynamic system at ultra-low temperatures is revealed through this consequence. Moreover, the general form and the simplest expression of the heat capacities of thermodynamic systems at ultra-low temperatures are deduced. Some significant discussion and results are given. One new research method is provided by using this consequence. Finally, the equivalence between the Nernst theorem and its consequence is rigorously proved, so that this consequence may be referred to another description of the third law of thermodynamics

Ultrafast Charge Transfer in Atomically Thin MoS2/WS2 Heterostructures

Van der Waals heterostructures have recently emerged as a new class of materials, where quantum coupling between stacked atomically thin two-dimensional (2D) layers, including graphene, hexagonal-boron nitride, and transition metal dichalcogenides (MX2), give rise to fascinating new phenomena. MX2 heterostructures are particularly exciting for novel optoelectronic and photovoltaic applications, because 2D MX2 monolayers can have an optical bandgap in the near-infrared to visible spectral range and exhibit extremely strong light-matter interactions. Theory predicts that many stacked MX2 heterostructures form type-II semiconductor heterojunctions that facilitate efficient electron-hole separation for light detection and harvesting. Here we report the first experimental observation of ultrafast charge transfer in photo-excited MoS2/WS2 heterostructures using both photoluminescence mapping and femtosecond (fs) pump-probe spectroscopy. We show that hole transfer from the MoS2 layer to the WS2 layer takes place within 50 fs after optical excitation, a remarkable rate for van der Waals coupled 2D layers. Such ultrafast charge transfer in van der Waals heterostructures can enable novel 2D devices for optoelectronics and light harvesting

Optimal design of sand blown wind tunnel

This work investigates the airflow driven by dual axial-flow fans in an atmospheric boundary layer (ABL) wind tunnel and the expected entrainment of sand movement together. The present study is conducted via 3D numerical simulation based on modelling the entire wind tunnel, including the power fan sections. Three configurations of dual fans in the tunnel are proposed. Simulation results show that the airflow in the tunnel with dual-fan configuration can satisfy the logarithmic distribution law for ABL flows. The airflow driven by the dual fans placed together at the tunnel outlet is highly similar to that in the tunnel with single fans. Although the boundary layer thickness is reduced, the maximum airflow velocity (53.393 m/s) and turbulence intensity (12.02%), which are respectively 1.75 and 1.49 times higher than those under the single-fan configuration, can be reached when dual fans are separately placed at the tunnel inlet and outlet. The simulation and experiment manifest that the separated arrangement of dual fans in the tunnel should be suitable for the experimental study of aeolian sand transport. Some measures, such as wind tunnel construction adjustment and optimal roughness element arrangement, are necessary to guarantee the required boundary layer thickness in the wind tunnel

Retrieval-Augmented Meta Learning for Low-Resource Text Classification

Meta learning have achieved promising performance in low-resource text classification which aims to identify target classes with knowledge transferred from source classes with sets of small tasks named episodes. However, due to the limited training data in the meta-learning scenario and the inherent properties of parameterized neural networks, poor generalization performance has become a pressing problem that needs to be addressed. To deal with this issue, we propose a meta-learning based method called Retrieval-Augmented Meta Learning(RAML). It not only uses parameterization for inference but also retrieves non-parametric knowledge from an external corpus to make inferences, which greatly alleviates the problem of poor generalization performance caused by the lack of diverse training data in meta-learning. This method differs from previous models that solely rely on parameters, as it explicitly emphasizes the importance of non-parametric knowledge, aiming to strike a balance between parameterized neural networks and non-parametric knowledge. The model is required to determine which knowledge to access and utilize during inference. Additionally, our multi-view passages fusion network module can effectively and efficiently integrate the retrieved information into low-resource classification task. The extensive experiments demonstrate that RAML significantly outperforms current SOTA low-resource text classification models.Comment: Under Revie

Prompt Learning With Knowledge Memorizing Prototypes For Generalized Few-Shot Intent Detection

Generalized Few-Shot Intent Detection (GFSID) is challenging and realistic because it needs to categorize both seen and novel intents simultaneously. Previous GFSID methods rely on the episodic learning paradigm, which makes it hard to extend to a generalized setup as they do not explicitly learn the classification of seen categories and the knowledge of seen intents. To address the dilemma, we propose to convert the GFSID task into the class incremental learning paradigm. Specifically, we propose a two-stage learning framework, which sequentially learns the knowledge of different intents in various periods via prompt learning. And then we exploit prototypes for categorizing both seen and novel intents. Furthermore, to achieve the transfer knowledge of intents in different stages, for different scenarios we design two knowledge preservation methods which close to realistic applications. Extensive experiments and detailed analyses on two widely used datasets show that our framework based on the class incremental learning paradigm achieves promising performance.Comment: Under Revie

Molecular Characterization of a Fus3/Kss1 Type MAPK from Puccinia striiformis f. sp. tritici, PsMAPK1

Puccinia striiformis f. sp. tritici (Pst) is an obligate biotrophic fungus that causes the destructive wheat stripe rust disease worldwide. Due to the lack of reliable transformation and gene disruption method, knowledge about the function of Pst genes involved in pathogenesis is limited. Mitogen-activated protein kinase (MAPK) genes have been shown in a number of plant pathogenic fungi to play critical roles in regulating various infection processes. In the present study, we identified and characterized the first MAPK gene PsMAPK1 in Pst. Phylogenetic analysis indicated that PsMAPK1 is a YERK1 MAP kinase belonging to the Fus3/Kss1 class. Single nucleotide polymerphisms (SNPs) and insertion/deletion were detected in the coding region of PsMAPK1 among six Pst isolates. Real-time RT-PCR analyses revealed that PsMAPK1 expression was induced at early infection stages and peaked during haustorium formation. When expressed in Fusarium graminearum, PsMAPK1 partially rescued the map1 mutant in vegetative growth and pathogenicity. It also partially complemented the defects of the Magnaporthe oryzae pmk1 mutant in appressorium formation and plant infection. These results suggest that F. graminearum and M. oryzae can be used as surrogate systems for functional analysis of well-conserved Pst genes and PsMAPK1 may play a role in the regulation of plant penetration and infectious growth in Pst

Secure Deduplication Based on Rabin Fingerprinting over Wireless Sensing Data in Cloud Computing

The rapid advancements in the Internet of Things (IoT) and cloud computing technologies have significantly promoted the collection and sharing of various data. In order to reduce the communication cost and the storage overhead, it is necessary to exploit data deduplication mechanisms. However, existing data deduplication technologies still suffer security and efficiency drawbacks. In this paper, we propose two secure data deduplication schemes based on Rabin fingerprinting over wireless sensing data in cloud computing. The first scheme is based on deterministic tags and the other one adopts random tags. The proposed schemes realize data deduplication before the data is outsourced to the cloud storage server, and hence both the communication cost and the computation cost are reduced. In particular, variable-size block-level deduplication is enabled based on the technique of Rabin fingerprinting which generates data blocks based on the content of the data. Before outsourcing data to the cloud, users encrypt the data based on convergent encryption technologies, which protects the data from being accessed by unauthorized users. Our security analysis shows that the proposed schemes are secure against offline brute-force dictionary attacks. In addition, the random tag makes the second scheme more reliable. Extensive experimental results indicate that the proposed data deduplication schemes are efficient in terms of the deduplication rate, the system operation time, and the tag generation time

Spatial and Temporal Variability of Polycyclic Aromatic Hydrocarbons in Sediments from Yellow River-Dominated Margin

Polycyclic aromatic hydrocarbons (PAHs) were analyzed for surface sediments and a sediment core from the Yellow River-dominated margin. The concentration of 16 USEPA priority PAHs in surface sediments ranged from 5.6 to 175.4 ng g−1 dry weight sediment (dws) with a mean of 49.1 ng g−1 dws. From 1930 to 2011, the distribution of PAHs (37.2 to 210.6 ng g−1 dws) was consistent with the socioeconomic development of China. The PAHs’ concentration peaked in 1964 and 1986, corresponding to the rapid economic growth in China (1958–1965) and the initiation of the “Reform and Open” policy in 1978, respectively. The applications of molecular diagnostic ratios and principal component analysis suggest that PAHs are predominantly produced by the coal and biomass combustion, whereas the contribution of petroleum combustions slightly increased after the 1970s, synchronous with an increasing usage of oil and gas in China

X-ray Nanocomputed Tomography in Zernike Phase Contrast for Studying 3D Morphology of Li–O 2 Battery Electrode

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