Joining of metallic glasses in liquid via ultrasonic vibrations.

Joining processes especially for metallic materials play critical roles in manufacturing industries and structural applications, therefore they are essential to human life. As a more complex technique, under-liquid joining has far-reaching implications for national defense, offshore mining. Furthermore, up-to-now, the effective joining of metals in extreme environments, such as the flammable organo-solvent or the arctic liquid nitrogen, is still uninvestigated. Therefore, an efficient under-liquid joining approach is urgently called for. Here we report a method to join different types of metallic glasses under water, seawater, alcohol and liquid-nitrogen. The dynamic heterogeneity and liquid-like region expansion induces fluid-like behavior under ultrasonic vibration to promote oxide layer dispersion and metal bonding, allowing metallic glasses to be successfully joined in heat-free conditions, while still exhibiting excellent tensile strength (1522 MPa), bending strength (2930 MPa) and improved corrosion properties. Our results provide a promising strategy for manufacturing under offshore, polar, oil-gas and space environments.

Dissolvable templates to prepare Pt-based porous metallic glass for the oxygen reduction reaction.

Oxygen reduction reaction (ORR) plays a crucial role in electrochemical energy conversion and storage devices such as metal-air batteries and water electrolyzers. Herein, a hierarchical nanoporous platinum-based metallic glass (NPMG) was developed by a facile fabrication method by dissolving in a liquid. The surface topography of the sample can be easily modulated by controlling the particle size of sodium chloride. As a result, the NPMG was proved to be efficient and robust as the ORR catalysts with super hydrophilicity and self-renewal capacity. The half-wave potential of the platinum-based porous material was 835 mV at 0.1 M KOH, even higher than that of the commercial Pt/C catalyst (823 mV) and the previously reported platinum material. In particular, platinum-based porous materials have extremely long stability (more than 500 h) through the self-renewal surface, which perfectly meets the requirements of catalyst stability in batteries. Our study has a better inspiration for developing and applying novel catalysts to prepare metal-air batteries.

A new hybrid optimization prediction model for PM2.5 concentration considering other air pollutants and meteorological conditions.

With the development of economy, the problem of air pollution has become increasingly serious. As an important detection index of air pollutants, how to accurately and effectively predict PM2.5 concentration is a significant issue related to human health and development. In this paper, a new hybrid optimization prediction model for PM2.5 concentration based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), variational mode decomposition optimized by COOT optimization algorithm (COOT-VMD), and least square support vector machine (LSSVM) optimized by the JAYA optimization algorithm (JAYA-LSSVM), named CEEMDAN-COOT-VMD-JAYA-LSSVM, is proposed. To avoid artificially setting the limits of the decomposition layer and penalty factor of VMD parameters, an improved VMD by COOT optimization algorithm, named COOT-VMD, is proposed. First, the original sequence of PM2.5 concentration is decomposed by CEEMDAN. Second, the high complexity component with low prediction accuracy after once decomposition is decomposed by COOT-VMD. Third, a prediction model of optimized LSSVM by JAYA optimization algorithm, named JAYA-LSSVM, is proposed. JAYA-LSSVM is used to predict all components considering other air pollutants such as PM10, SO2, NO2, CO, and O3 and meteorological conditions such as wind speed, temperature, sunlight, relative humidity and average air pressure. Finally, all predicted values are reconstructed to obtain the final prediction results. PM2.5 concentration from April 1, 2016 to March 29, 2021 in Xi'an and Shenyang is used as the experimental data to verify the proposed model. The results of experiment in Xi'an show that the RMSE, MAE, MAPE and R2 are 2.843, 1.8344, 2.94%, and 0.99525 respectively. The results of experiment in Shenyang show that the RMSE, MAE, MAPE and R2 are 2.2714, 1.673, 3.13%, and 0.99573 respectively. Compared to other single and hybrid models, the proposed model can accurately predict PM2.5 concentration. Diebold Mariano test results display the proposed prediction model is superior to all comparison models at 99% confidence level.

Geographic distribution and prevalence of human echinococcosis at the township level in the Tibet Autonomous Region.

BACKGROUND: Echinococcosis, a zoonotic parasitic disease, is caused by larval stages of cestodes in the Echinococcus genus. Echinococcosis is highly prevalent in ten provinces/autonomous regions of western and northern China. In 2016, an epidemiological survey of Tibet Autonomous Region (TAR) revealed that the prevalence of human echinococcosis was 1.66%, which was much higher than the average prevalence in China (0.24%). Therefore, to improve on the current prevention and control measures, it is important to understand the prevalence and spatial distribution characteristics of human echinococcosis at the township level in TAR. METHODS: Data for echinococcosis cases in 2018 were obtained from the annual report system of echinococcosis of Tibet Center for Disease Control and Prevention. Diagnosis had been performed via B-ultrasonography. The epidemic status of echinococcosis in all townships in TAR was classified according to the relevant standards of population prevalence indices as defined in the national technical plan for echinococcosis control. Spatial scan statistics were performed to establish the geographical townships that were most at risk of echinococcosis. RESULTS: In 2018, a total of 16,009 echinococcosis cases, whose prevalence was 0.53%, were recorded in 74 endemic counties in TAR. Based on the order of the epidemic degree, all the 692 townships were classified from high to low degrees. Among them, 127 townships had prevalence rates ≥ 1%. The high prevalence of human echinococcosis in TAR, which is associated with a wide geographic distribution, is a medical concern. Approximately 94.65% of the villages and towns reported echinococcosis cases. According to spatial distribution analysis, the prevalence of human echinococcosis was found to be clustered, with the specific clustering areas being identified. The cystic echinococcosis primary cluster covered 88 townships, while that of alveolar echinococcosis's covered 38 townships. CONCLUSIONS: This study shows spatial distributions of echinococcosis with different epidemic degrees in 692 townships of TAR and high-risk cluster areas at the township level. Our findings indicate that strengthening the echinococcosis prevention and control strategies in TAR should directed at townships with a high prevalence and high-risk clustering areas.

Prevalence and spatial distribution characteristics of human echinococcosis in China.

BACKGROUND: Echinococcosis is a zoonotic parasitic disease caused by larval stages of cestodes belonging to the genus Echinococcus. The infection affects people's health and safety as well as agropastoral sector. In China, human echinococcosis is a major public health burden, especially in western China. Echinococcosis affects people health as well as agricultural and pastoral economy. Therefore, it is important to understand the prevalence status and spatial distribution of human echinococcosis in order to advance our knowledge of basic information for prevention and control measures reinforcement. METHODS: Report data on echinococcosis were collected in 370 counties in China in 2018 and were used to assess prevalence and spatial distribution. SPSS 21.0 was used to obtain the prevalence rate for CE and AE. For statistical analyses and mapping, all data were processed using SPSS 21.0 and ArcGIS 10.4, respectively. Chi-square test and Exact probability method were used to assess spatial autocorrelation and spatial clustering. RESULTS: A total of 47,278 cases of echinococcosis were recorded in 2018 in 370 endemic counties in China. The prevalence rate of human echinococcosis was 10.57 per 10,000. Analysis of the disease prevalence showed obvious spatial positive autocorrelation in globle spatial autocorrelation with two aggregation modes in local spatial autocorrelation, namely high-high and low-high aggregation areas. The high-high gathering areas were mainly concentrated in northern Tibet, western Qinghai, and Ganzi in the Tibetan Autonomous Region and in Sichuan. The low-high clusters were concentrated in Gamba, Kangma and Yadong counties of Tibet. In addition, spatial scanning analysis revealed two spatial clusters. One type of spatial clusters included 71 counties in Tibet Autonomous Region, 22 counties in Qinghai, 11 counties in Sichuan, three counties in Xinjiang Uygur Autonomous Region, two counties in Yunnan, and one county in Gansu. In the second category, six types of spatial clusters were observed in the counties of Xinjiang Uygur Autonomous Region, and the Qinghai, Gansu, and Sichuan Provinces. CONCLUSION: This study showed a serious prevalence of human echinococcosis with obvious spatial aggregation of the disease prevalence in China. The Qinghai-Tibet Plateau is the "hot spot" area of human echinococcosis in China. Findings from this study indicate that there is an urgent need of joint strategies to strengthen efforts for the prevention and control of echinococcosis in China, especially in the Qinghai-Tibet Plateau.

A Ramie bZIP Transcription Factor BnbZIP2 Is Involved in Drought, Salt, and Heavy Metal Stress Response.

bZIP transcription factors play key roles in plant growth, development, and stress signaling. A bZIP gene BnbZIP2 (GenBank accession number: KP642148) was cloned from ramie. BnbZIP2 has a 1416 base pair open reading frame, encoding a 471 amino acid protein containing a characteristic bZIP domain and a leucine zipper. BnbZIP2 shares high sequence similarity with bZIP factors from other plants. The BnbZIP2 protein is localized to both nuclei and cytoplasm. Transcripts of BnbZIP2 were found in various tissues in ramie, with significantly higher levels in female and male flowers. Its expression was induced by drought, high salinity, and abscisic acid treatments. Analysis of the cis-elements in promoters of BnbZIP2 identified cis-acting elements involved in growth, developmental processes, and a variety of stress responses. Transgenic Arabidopsis plants' overexpression of BnbZIP2 exhibited more sensitivity to drought and heavy metal Cd stress during seed germination, whereas more tolerance to high-salinity stress than the wild type during both seed germination and plant development. Thus, BnbZIP2 may act as a positive regulator in plants' response to high-salinity stress and be an important candidate gene for molecular breeding of salt-tolerant plants.