Extreme events have become more frequent in the Northern Hemisphere mid‐latitudes in recent decades, hugely impacting the ecosystem and society. The quasi‐resonance amplification (QRA) of planetary ...waves is considered one of the dynamic mechanisms leading to extreme weather. However, the specific impact of resonant waves caused by QRA on surface heat extremes is still an open issue. Here we show that the QRA of planetary waves leading to heat extremes is closely related to double jets, accompanied by the enhancement of atmospheric blocking and the weakening of planetary wave escaping into the stratosphere. Our results illustrate the important role of mid‐latitude planetary waves with zonal wavenumber m = 6–8 caused by QRA in the increasingly frequent heat waves in recent years, as it can increase the coverage area and occurrence frequency of heat extremes in mid‐latitudes and show a significant impact on preferred regions, especially in Eurasia.
Plain Language Summary
In the summer of 2022, the Northern Hemisphere mid‐latitudes were affected by widespread, intense heat waves that developed more quickly than climatologists had expected, hugely impacting the ecosystem and society. Understanding the extent and causes of extreme heat can help local authorities better prepare for the extreme weather that may occur in the near future. Planetary wave, also known as Rossby wave, manifested as a large‐scale oscillation of the midlatitude atmospheric flow, usually forms a snaking shape over the Earth, leading to persistent surface weather systems and often resulting in extreme events. Existing studies have shown that, planetary wave is one of the important dynamic mechanism behind heat waves. At certain frequencies and wavelengths (short‐wavelength), this circumglobal waves disturbance can be significantly amplified through resonance, resulting in heat extremes. Our work indicates that resonant wave plays an increasingly important role in heat events over Northern Hemisphere mid‐latitudes. The long‐term changes in resonant wave trend deserve continuous attention, because an improved understanding of planetary waves behind extreme events can help assess future wave activity's potential social and economic effects.
Key Points
The influence of resonant waves on heat extremes in the Northern Hemisphere mid‐latitude summer is increasing, especially in Eurasi
The occurrence of resonant waves is closely related to double jets, accompanied by the enhancement of atmospheric blocking
The occurrence of resonant waves is accompanied by the weakening of the upward‐propagating planetary waves
Selecting risk factors is essential for measuring energy corporate risk. However, the comprehensive identification of energy corporate risk factors is still a difficult issue. This paper innovatively ...uses the text mining approach to comprehensively identify energy corporate risk factors from textual risk disclosures reported in financial statements. Based on 131,755 risk factor headings from 3707 Form 10-K filings from 840 U.S. energy corporations over the period 2010–2016, 66 types of risk factors that affect energy corporate risks are identified. Furthermore, we develop a hierarchical system for 66 energy corporate risk factors by dividing energy corporations into nine subsectors. Thus, the hierarchical energy corporate risk factor system provides fundamental support for further energy corporate risk measurement. Researchers can comprehensively and effectively select risk factors in measuring risks of the entire energy industry or each of nine energy subsectors.
•Selecting risk factors is essential for energy corporate risk measurement.•We propose to identify energy corporate risk factors from textual risk disclosures.•A risk factor hierarchical system for the whole energy industry is constructed.•This system consists of general and unique risk factors for nine energy subsectors.•We lay a foundation for further energy corporate risk measurement.
There is a rapidly increasing amount of de novo genome assembly using next-generation sequencing (NGS) short reads; however, several big challenges remain to be overcome in order for this to be ...efficient and accurate. SOAPdenovo has been successfully applied to assemble many published genomes, but it still needs improvement in continuity, accuracy and coverage, especially in repeat regions.
To overcome these challenges, we have developed its successor, SOAPdenovo2, which has the advantage of a new algorithm design that reduces memory consumption in graph construction, resolves more repeat regions in contig assembly, increases coverage and length in scaffold construction, improves gap closing, and optimizes for large genome.
Benchmark using the Assemblathon1 and GAGE datasets showed that SOAPdenovo2 greatly surpasses its predecessor SOAPdenovo and is competitive to other assemblers on both assembly length and accuracy. We also provide an updated assembly version of the 2008 Asian (YH) genome using SOAPdenovo2. Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp, respectively, which is 3-fold and 50-fold longer than the first published version. The genome coverage increased from 81.16% to 93.91%, and memory consumption was ~2/3 lower during the point of largest memory consumption.
Abstract
Gravity waves (GWs) are important for the vertical coupling of the Martian atmosphere. The middle atmosphere is the key region where GWs propagate to the upper thermosphere and generate ...momentum and energy exchange, but the knowledge of middle-atmosphere GWs is incomplete, due to the lack of observations with the kilometer-scale resolution. We have analyzed the climatology of GW activity in the middle and upper atmosphere of Mars using 20–180 km temperature profiles measured by the Atmospheric Chemistry Suite instrument on board the Trace Gas Orbiter. The results show that the amplitudes of GWs extracted in this study are generally less than 15% and that the centers of the strongest GW activity vary significantly with the seasons. Second, the strongest GW activity in the mesosphere indicates the strong dissipation effects of the mesopause, and the mid-atmospheric GWs show a seasonal pattern that is stronger in the winter hemisphere. During the global dust event of MY34, the enhancement of GWs in the middle atmosphere is most pronounced at low and middle latitudes where the dust storms are active. It is possible that changes in the temperature structure of the middle atmosphere adjust the atmospheric circulation and thus improve the propagation of GWs. Furthermore, GW activity is stronger on the dayside than on the nightside, and there is no significant correlation between amplitudes and background temperature. This suggests a limited role of convective instability in limiting the growth of GWs in the middle atmosphere, with nonlinear damping competing with that of molecular diffusion at different harmonics.
Deep learning models can produce unstable results by introducing imperceptible perturbations that are difficult for humans to recognize. This can have a significant impact on the accuracy and ...security of deep learning applications due to their poorly understood interpretability. As a field critical to security research, this problem clearly exists in underwater acoustic target recognition for ocean sensing. To address this issue, this article investigates the reliability of state-of-the-art deep learning models by exploring adversarial attack methods that add small, exquisite perturbations on acoustic Mel-spectrograms to generate adversarial spectrograms. Experimental results based on real-world datasets reveal that these models can be forced to learn unexpected features when subjected to adversarial spectrograms, resulting in significant accuracy drops. Specifically, when employing the iterative attack method, the overall accuracy of all models experiences a significant decrease of approximately 70% for two datasets under stronger perturbations.
The great losses caused by financial fraud have attracted continuous attention from academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus pandemic (COVID-19) ...unexpectedly shocks the global financial system and accelerates the use of digital financial services, which brings new challenges in effective financial fraud detection. This paper provides a comprehensive overview of intelligent financial fraud detection practices. We analyze the new features of fraud risk caused by the pandemic and review the development of data types used in fraud detection practices from quantitative tabular data to various unstructured data. The evolution of methods in financial fraud detection is summarized, and the emerging Graph Neural Network methods in the post-pandemic era are discussed in particular. Finally, some of the key challenges and potential directions are proposed to provide inspiring information on intelligent financial fraud detection in the future.
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•Financial fraud in the post-pandemic era is becoming more sophisticated and insidious•We review the development of financial fraud detection from data and method perspectives•Graph neural network methods are emphasized due to their capacity for heterogeneous data analysis•Future directions of financial fraud detection are discussed from task, data, and model-oriented perspectives
Abstract
The drivers of reputational risk are still far from explicit, making proactive risk management and quantitative research rather difficult. The Basel Committee on Banking Supervision ...encourages financial institutions to systematically identify reputational risk drivers; however, such drivers still represent an unsolved problem. Therefore, the objective of this paper is to systemically identify reputational risk drivers from textual risk disclosures in financial reports. We find that textual risk disclosures in financial reports contain abundant information about the causes of reputational risk, thus indicating the possibility of systematically identifying the reputational risk drivers. To accurately extract reputational risk drivers from massive and unstructured textual risk disclosure data, we modify a text mining method to make it more suitable for this type of textual data with noise words. Based on 352,326 risk headings extracted from 11,921 annual reports released by 1570 U.S. financial institutions from 2006 to 2019, a total of 13 reputational risk drivers are identified to extend upon existing studies. The importance of reputational risk drivers and their dynamic evolutions are also quantified to discover the drivers of greatest concern. This paper can clarify the sources of reputational risk to help companies realize proactive reputational risk management and provide a theoretical basis for further quantitative studies, especially the measurement of reputational risk.
To further explore the long-term stability of nano-dielectrics, experiments were carried out to investigate the moisture absorption characteristics and electrical properties of silicone rubber (SiR) ...doped with different inorganic nanoparticles. Thermogravimetric analysis (TGA) is utilized to research the moisture absorption characteristics including mass fraction and binding forms. The trap depth and electron orbitals are calculated by density functional theory to explain the influence mechanism of water molecules on SiR. It is found that the addition of nanoparticles will increase the moisture content of SiR. Additionally, the nano-TiO2-doped SiR absorbs more water and binds with water relatively more loosely than nano-Al2O3. There is a degradation of space charge inhibition capability and breakdown strength after moisture absorption, which might be explained by shallow traps brought by water molecules and the narrowed forbidden bandwidth of SiR.
In this work, the wear and friction behavior of nanoscale SiCp (1 vol.%) reinforced Mg composite were investigated. Experiments were carried out by rubbing a GCr15 steel ball on the surface of pin ...specimens with the different sliding velocities of 0.1, 0.3 and 0.5 m/s at distinctive normal loads of 10, 20, and 30 N, respectively (without the aid of lubricant). Detailed analysis demonstrated that SiCp efficiently block the grain growth and improve the mechanical properties of the composite due to grain refining and dislocation strengthening. As a result, the wear resistance of composite was more prominent s compared with the initial alloy under all test condition. With the increase of sliding speed or load, the wear rate of composite increases gradually. The wear rate is reduced by 12% compared to the alloy, particularly in high load condition. Under low speeds, abrasive wear and slight oxidative wear were prevalent. Subsequently, the wear mechanism transitions to the initial delamination wear as the sliding speed increases. Severe plastic deformation occurs on the surface of the friction sample under high load, and the surface damage is serious.
Interest in macrocycles as potential therapeutic agents has increased rapidly. Macrocyclization of bioactive acyclic molecules provides a potential avenue to yield novel chemical scaffolds, which can ...contribute to the improvement of the biological activity and physicochemical properties of these molecules. In this study, we propose a computational macrocyclization method based on Transformer architecture (which we name Macformer). Leveraging deep learning, Macformer explores the vast chemical space of macrocyclic analogues of a given acyclic molecule by adding diverse linkers compatible with the acyclic molecule. Macformer can efficiently learn the implicit relationships between acyclic and macrocyclic structures represented as SMILES strings and generate plenty of macrocycles with chemical diversity and structural novelty. In data augmentation scenarios using both internal ChEMBL and external ZINC test datasets, Macformer display excellent performance and generalisability. We showcase the utility of Macformer when combined with molecular docking simulations and wet lab based experimental validation, by applying it to the prospective design of macrocyclic JAK2 inhibitors.
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