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Nonlayered two-dimensional (2D) magnets have attracted special attention, as many of them possess magnetic order above room temperature and enhanced chemical stability compared to most existing vdW magnets, which offers remarkable opportunities for developing compact spintronic devices. However, the growth of these materials is quite challenging due to the inherent three-dimensionally bonded nature, which hampers the study of their magnetism. Here, we demonstrate the controllable growth of air-stable pure γ-Fe2O3nanoflakes by a confined-vdW epitaxial approach. The lateral size of the nanoflakes could be adjusted from hundreds of nanometers to tens of micrometers by precisely controlling the annealing time. Interestingly, a lateral-size-dependent magnetic domain configuration was observed. As the sizes continuously increase, the magnetic domain evolves from single domain to vortex and finally to multidomain. This work provides guidance for the controllable synthesis of 2D inverse spinel-type crystals and expands the range of magnetic vortex materials into magnetic semiconductors.

Adenosine-to-inosine (A-to-I) RNA editing, constituting nearly 90% of all RNA editing events in humans, has been reported to contribute to the tumorigenesis in diverse cancers. However, the comprehensive map for functional A-to-I RNA editingevents in cancers is still insufficient. To fill this gap, we systematically and intensively analyzed multiple tumorigenic mechanisms of A-to-I RNA editing events in samples across 33 cancer types from The Cancer Genome Atlas. For individual candidate among ∼ 1,500,000 quantified RNA editing events, we performed diverse types of downstream functional annotations. Finally, we identified 24,236 potentially functional A-to-I RNA editing events, including the cases in APOL1, IGFBP3, GRIA2, BLCAP, and miR-589-3p. These events might play crucial roles in the scenarios of tumorigenesis, due to their tumor-related editing frequencies or probable effects on altered expression profiles, protein functions, splicing patterns, and microRNA regulations of tumor genes. Our functional A-to-I RNA editing events (https://ccsm.uth.edu/CAeditome/) will help better understand the cancer pathology from the A-to-I RNA editing aspect.

In recent years, more and more people suffer from voice-related diseases. Given the limitations of current pathological speech conversion methods, that is, a method can only convert a single kind of pathological voice. In this study, we propose a novel Encoder-Decoder Generative Adversarial Network (E-DGAN) to generate personalized speech for pathological to normal voice conversion, which is suitable for multiple kinds of pathological voices. Our proposed method can also solve the problem of improving the intelligibility and personalizing custom speech of pathological voices. Feature extraction is performed using a mel filter bank. The conversion network is an encoder-decoder structure, which is used to convert the mel spectrogram of pathological voices to the mel spectrogram of normal voices. After being converted by the residual conversion network, the personalized normal speech is synthesized by the neural vocoder. In addition, we propose a subjective evaluation metric named “content similarity” to evaluate the consistency between the converted pathological voice content and the reference content. The Saarbrücken Voice Database (SVD) is used to verify the proposed method. The intelligibility and content similarity of pathological voices are increased by 18.67% and 2.60%, respectively. Besides, an intuitive analysis based on a spectrogram was done and a significant improvement was achieved. The results show that our proposed method can improve the intelligibility of pathological voices and personalize the conversion of pathological voices into the normal voices of 20 different speakers. Our proposed method is compared with five other pathological voice conversion methods, and our proposed method has the best evaluation results.

The urgent need for immediate personal protection against chemical warfare agents (CWAs) spurs the requirement on robust and highly efficient catalytic systems that can be conveniently integrated to wearable devices. Herein, as a new concept for CWA decontamination catalyst design, sub-nanoscale, catalytically active zirconium-oxo molecular clusters are covalently integrated in flexible polymer network as crosslinkers for the full exposure of catalytic sites as well as robust framework structures. The obtained membrane catalysts exhibit high swelling ratio with aqueous content as 84 wt% and therefore, demonstrate quasi-homogeneous catalytic activity toward the rapid hydrolysis of both CWA, soman (GD) (t1/2 = 5.0 min) and CWA simulant, methyl paraoxon (DMNP) (t1/2 = 8.9 min). Meanwhile, due to the covalent nature of cross-linkages and the high flexibility of polymer strands, the membranes possess promising mechanical strength and toughness that can stand the impact of high gas pressures and show high permeation for both CO2and O2, enabling their extended applications in the field of collective/personal protective materials with body comfort.

Hydrogel-based electronics have received growing attention because of their great flexibility and stretchability. However, the fabrication of conductive hydrogels with high stretchability, excellent toughness, outstanding sensitivity, and low-temperature stability still remains a great challenge. In this study, a type of conductive hydrogels consisting of a double network (DN) structure is synthesized. The dynamically cross-linked chitosan (CS) and the flexible polyacrylamide network doped with polyaniline constitute the DN through the hydrogen bonds between the hydroxyl, amide, and aniline groups. This type of hydrogels displays excellent mechanical performance, striking conductivity, and remarkable freezing tolerance. The flexible electronic sensors based on the double-network hydrogels demonstrate superior strain sensitivity and linear response on various deformations. Additionally, the good antifreezing property of the hydrogels allows the sensors to exhibit excellent performance at −20 °C.

The Carboniferous shale in the Guizhong Depression of central Guangxi presents good exploration potential of shale gas, but its exploration effectiveness is restricted by the unclear distribution, quality and potential of high-quality shale. In this paper, the Lower Carboniferous Luzhai shale was taken as the research object in order to guide the exploration of Carboniferous shale gas in the Guizhong Depression. Based on the field outcrops, well drilling, well logging and test data of the Guizhong Depression and its surrounding areas, the shale formation was studied systematically based on the characteristics of distribution, organic geochemistry and reservoir, and the preservation conditions. Then, the development characteristics of black shale were confirmed and the distribution laws of high-quality shale were summarized. Finally, shale gas exploration was analyzed and the favorable exploration areas were defined. And the following research results were obtained. First, the Luzhai shale in the Guizhong Depression is mainly carbonaceous shale and siliceous shale of deepwater continental shelf facies. Second, the high-quality Luzhai shale is 20–60 m thick and it is characterized by high total organic carbon, good type of organic matters, moderate maturity of organic matter, high content of brittle minerals, good reservoir property and developed pores of organic matters. Third, regional caprocks and roofs & floors are well developed in the Liucheng Slope and the Yishan Sag. They are weakly deformed, suffer from less uplift and denudation, and are far away from the strong strike–slip reverse fault, so they have good preservation conditions. Fourth, shallow wells which were drilled in the surface structures of the Guizhong Depression in the early stage present abundant gas shows, and most of them produce gas flow, which reveals a promising prospect of shale gas exploration in this area. In conclusion, the wide and gentle synclines with large burial depth in the Liucheng Slope and the Yishan Sag are the favorable areas for shale gas exploration in the Guizhong Depression.

Recursive query processing has experienced a recent resurgence, as a result of its use in many modern application domains, including data integration, graph analytics, security, program analysis, networking and decision making. Due to the large volumes of data being processed, several research efforts across multiple communities have explored how to scale up recursive queries, typically expressed in Datalog. Our experience with these tools indicate that their performance does not translate across domains---e.g., a tool designed for large-scale graph analytics does not exhibit the same performance on program-analysis tasks, and vice versa.Starting from the above observation, we make the following two contributions. First, we perform a detailed experimental evaluation comparing a number of state-of-the-art Datalog systems on a wide spectrum of graph analytics and program-analysis tasks, and summarize the pros and cons of existing techniques. Second, we design and implement our own general-purpose Datalog engine, called RecStep, on top of a parallel single-node relational system. We outline the techniques we applied on RecStep, as well as the contribution of each technique to the overall performance. Using RecStep as a baseline, we demonstrate that it generally out-performs state-of-the-art parallel Datalog engines on complex and large-scale Datalog evaluation, by a 4-6X margin. An additional insight from our work is that it is possible to build a high-performance Datalog system on top of a relational engine, an idea that has been dismissed in past work.

Clarifying the sedimentary environment and main controlling factors of source rocks is significant for the oil and gas exploration in the Qiangtang Basin. Based on the detailed observation results, this study analyzed the organic geochemical characteristics and trace metals of source rocks in the Upper Triassic Xiaochaka Formation in the Woruoshan Mountain and investigated the depositional conditions and their implications for the formation of source rocks. The source rocks of the Xiaochaka Formation mainly consist of dark mudstones with low-medium abundance of organic matter. They have type II2-III kerogen and middle thermal maturity. This strata had a warm and humid climate during its deposition. Affected by the sea-level fluctuation, the water of this strata evolved from freshwater to brackish water and then freshwater from bottom to top. The Xiaochaka Formation had an oxic environment overall and high paleoproductivity. The formation of the source rocks in the Woruoshan mainly had a “productivity model” controlled by paleoclimate and freshwater flux. The warm and humid paleoclimate and freshwater transport contributed to the high paleoproductivity of water columns, which counteracted the unfavorable preservation conditions. As a result, type Ⅱ2-Ⅲ source rocks were finally formed.

Although the application of inorganic fertilizer is a widespread agronomic practice used to boost soil productivity and crop yields, the effects on the soil microbiome and the metabolic mechanisms involved in the high-yield response of crops to long-term fertilization remain poorly described. In this study, an integrated metagenomic and metabolomic analysis was used for the first time to explore the mechanism of crop yield response to the 20-year application of nitrogen-phosphorus-potassium fertilizer in a subtropical agroecosystem in southwest China. Soil bacterial and fungal communities were monitored using 16S rRNA (bacteria) and ITS1 full-length gene (fungi) amplicon sequencing technology, and metabolites were detected using LC-MS. The results revealed that long-term fertilization shaped the composition of bacteria and fungi to increase crop yields, in addition to providing nutrients. Long-term fertilization significantly increased the relative abundance of PGPR and AMF and promoted the secretion of soil metabolites, like carbohydrates, organic acids, and organic nitrogen compounds, which were primarily enriched in amino acid metabolism pathways. The increases in carbon and nitrogen sources and bioactive substances in soil promoted increases in plant biomass, which maintained soil quality and production capacity. The findings highlighted the importance of soil metabolites in maintaining soil productivity as well as crop yields, and proposed that regulating key metabolites could increase crop yields in agroecosystems.

• Periodic sinusoidal variation is added simultaneously to inter-core coupling and loss-gain constants in the model of PT-symmetric nonlinear dual-core waveguides. • The stability of solitons features an optimum relation under the management. • Under the adiabatic approximation, the stability boundary for two-component soliton is predicted in an analytical form. • The periodic management can lead to multiple-collision phenomenology in interactions between the stable solitons. We consider a dual-core nonlinear waveguide with the parity-time (PT) symmetry, realized in the form of equal gain and loss terms carried by the coupled cores. To expand a previously found stability region for solitons in this system, and explore possibilities for the development of dynamical control of the solitons, we introduce "management" in the form of periodic sinusoidal variation of the loss-gain (LG) coefficients, along with synchronous variation of the inter-core coupling (ICC) constant. This system, which can be realized in optics (in the temporal and spatial domains alike), features strong robustness when amplitudes of the variation of the LG and ICC coefficients keep a ratio equal to that of their constant counterparts, allowing one to find exact solutions for PT -symmetric solitons. A stability region for the solitons is identified in terms of the management amplitude and period, as well as the soliton's amplitude. In the long-period regime, the solitons evolve adiabatically, making it possible to predict their stability boundaries in an analytical form. The system keeping the Galilean invariance, collisions between moving solitons are considered too. Slowly moving solitons undergo multiple collisions, but eventually separate. [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks (DCNN) have achieved remarkable performance for single image super-resolution (SISR). Although some recent works have introduced multi-scale representation into DCNN-based super-resolution, they neglect to explore the interdependencies across different scales. To address this issue, we propose a high-order cross-scale attention network (HOCSANet) for SISR reconstruction. Specifically, a novel high-order cross-scale attention block (HOCSABlock) is developed to integrate the multi-scale representation with attention mechanism, in which both in-scale and cross-scale feature correlations are exploited and utilized to adaptively rescale the multi-scale features. Moreover, we introduce a dual-nested residual block (DNRBlock), which combines plain residual block and wide-activated residual block and learns more informative features from the difference between them. Experimental results demonstrate the superiority of the proposed HOCSANet over several state-of-the-art SISR methods. [ABSTRACT FROM AUTHOR]