Search

BackgroundsThe goal of this study is to explore the transmission dynamics for recent large-scale COVID-19 outbreaks in Shaanxi Province on the Chinese mainland. Furthermore, the potential effects of the Spring Festival travel rush on the ongoing COVID-19 pandemic were depicted.MethodsThis study uses baseline data from a large cohort to investigate the characteristics of the recent COVID-19 epidemic in Shaanxi province. A cluster sampling method was used to recruit the study participants during the COVID-19 pandemic in Shaanxi province since Dec. 1st, 2022. A total of 44 sampling cluster (11 village in rural areas and 33 residences in urban areas) were chosen for enrollment of study participants. A self-developed questionnaire was applied to data collection of socio-demographic and COVID-19 pandemic related information.ResultsA total of 14,744 study participants were enrolled in the baseline survey and 12,111 completed survey data were extracted for analysis. The cumulative infection attack rate (IAR) of COVID-19 among the study participants was 84.7%. The cumulative IAR in urban and rural areas were 85.6% and 83.7%, respectively. A peak of COVID-19 self-reported diagnosis could be observed from Dec. 15th, 2022 to Jan. 1st, 2023 in the provincial level. Beside this major peak of the recent epidemic (around Dec.20th, 2022), a small but steep rise could also be identified between Jan 13thto 14th, 2023. Individuals who escaped the first wave of COVID-19 outbreaks may face danger of infection from returnees during the 2023 Spring Festival.ConclusionAccording to the COVID-19 cumulative IAR data, the herd community was primarily achieved in Shaanxi province’s urban and rural areas. The epidemic in Shaanxi province has been exacerbated by mass population movement during the Spring Festival travel rush in both urban and rural areas. Further surveillance should be performed to monitor the spread of SARS-CoV-2 infections.

Aims: In addition to pineal gland, many cells, tissues, and organs also synthesize melatonin (N-acetyl-5-methoxytryptamine). Embryos are a group of special cells and whether they can synthesize melatonin is still an open question. However, melatonin application promoted embryo development in many species in in vitro condition. The purpose of this study was to investigate whether embryos can synthesize melatonin; if it is so, what are the impacts of the endogenously produced melatonin on embryo development and the associated molecular mechanisms. These have never been reported previously. Results: Melatonin synthesis was observed at different stages of embryonic development. Aanat (aralkylamine N-acetyltransferase), a rate-limiting enzyme for melatonin production, was found to mostly localize in the mitochondria. Aanat knockdown significantly impeded embryonic development, and melatonin supplementation rescued it. The potential mechanisms might be that melatonin preserved mitochondrial intact and its function, thus providing sufficient adenosine 5'-triphosphate for the embryo development. In addition, melatonin scavenged intracellular reactive oxygen species (ROS) and reduced the DNA mutation induced by oxidative stress. In the molecular level, Aanat knockdown reduced tet methylcytosine dioxygenase 2 (Tet2) expression and DNA demethylation in blastocyst and melatonin supplementation rescued these processes. Innovation: This is the first report to show that embryos synthesize melatonin, and its synthetic enzyme Aanat was located in the mitochondria of embryos. An effect of melatonin is to maintain Tet2 expression and normal methylation status, and thereby promote embryonic development. Conclusion: Embryos can produce melatonin that reduces ROS production, preserves mitochondrial function, and maintains Tet2 expression and the normal DNA methylation.

Studying the early changes in post-fire vegetation communities may improve the overall resilience of forests. The necessity for doing so was demonstrated by the Bobcat Fire, which seriously threatened the central San Gabriel Mountains and the Angeles National Forest in California. This study aimed to monitor and quantify the effects of climatological and topographic conditions along with burn severity on early (within 1 year) post-fire forests and shrubs community regeneration. In this study, we used Sentinel-2(MSI) intensive time-series imagery (July 2020–October 2021) to make a confusion matrix combined with 389 vegetation sample points on Google Earth Pro. The overall accuracy (OA) and the Kappa coefficient, calculated from the confusion matrix, were used as evaluation parameters to validate the classification results. With multiple linear regression models and Environmental Systems Research Institute (ESRI) historical images, we analyzed the effects of climate and slope aspects on the regeneration of post-fire forest and shrub communities. We also quantitatively analyzed the regeneration rates based on five burn severity types. The results show that the normalized burning rate (NBR) was the most accurate vegetation classification indicator in this study (OA: 92.3–99.5%, Kappa: 0.88–0.98). The vegetation classification accuracy based on SVM is about 6.6% higher than K-Means. The overall accuracy of the burn area is 94.87%. Post-fire climate factors had a significant impact on the regeneration of the two vegetation communities (R2: 0.42–0.88); the optimal regeneration slope was 15–35°; and the fire severity changed the original competition relationship and regeneration rate. The results provide four main insights into the regeneration of post-fire vegetation communities: (1) climate factors in the first regenerating season have important impacts on the regeneration of forest and shrub communities; (2) daytime duration and rainfall are the most significant factors for forests and shrubs regeneration; (3) tolerable low burn severity promotes forests regeneration; and (4) forests have a certain ability to resist fires, while shrubs can better tolerate high-intensity fire ecology. This study could support the implementation of strategies for regionalized forest management and the targeted enhancement of post-fire vegetation community resilience.

Advanced oxidation technology is attracting attention as an effective method of water treatment that can degrade various organic pollutants. The combination of photocatalysis (UV) and ozone (O3) and titanium dioxide (TiO2) is a promising advanced oxidation technology. The combination of ozone, hydrogen peroxide, ultraviolet light and other oxidants for catalytic oxidation is also the current mainstream advanced oxidation technology. They can effectively degrade emerging water pollutants and alleviate water pollution problems. Titanium dioxide, hydrogen peroxide, and ozone are all popular catalysts because of their low cost, non-toxicity, strong oxidizing ability, and easy contact with various surfaces.

In this work, experiments and molecular dynamics (MD) simulations are carried out to explore the synergistic effect of supercritical CO2 (scCO2) and organic solvent on intercalation and exfoliation of graphene. Experimental characterizations via transmission electron microscopy, atomic force microscopy and Raman spectroscopy indicate that by combining scCO2 and organic solvent (N-methylpyrrolidone, NMP), few-layer graphene is successfully exfoliated from graphite, among which over 30% is 1-4 layers, and 55% is 5-8 layers. Systematic experiments have shown that compared with pure scCO2 or NMP, the mixed scCO2 and NMP can significantly increase the amount of graphene and the rate of few-layer graphene, and the optimum volume fraction of NMP is 25%. Parallel MD simulations indicate that the scCO2 molecules first diffuse into the interlayer of graphite, and then the larger NMP molecules insert as wedges and further expand interlayer spacing, promoting intercalation and exfoliation. The iteration of scCO2 diffusion and the NMP wedge can generate positive feedback to improve the exfoliation productivity and efficiency. This work explores the synergistic effect of scCO2 and NMP on the exfoliation of graphene, which may provide useful insights for exfoliation of other two dimensional materials.

The anti-inflammatory activity of melatonin (MT) has been well documented, however, little is known regarding endogenously occurring MT in this respect, especially for large animals. In the current study, we created a MT-enriched animal model (goats) overexpressing the MT synthetase gene Aanat. The responses of these animals to lipopolysaccharide (LPS) stimulation were systematically studied. It was found that LPS treatment exacerbated the inflammatory response in wild-type (WT) goats and increased their temperature to 40 &deg, C. In addition, their granulocyte counts were also significantly elevated. In contrast, these symptoms were not observed in transgenic goats with LPS treatment. The rescue study with MT injection into WT goats who were treated with LPS confirmed that the protective effects in transgenic goats against LPS were attributed to a high level of endogenously produced MT. The proteomic analysis in the peripheral blood mononuclear cells (PBMCs) isolated from the transgenic animals uncovered several potential mechanisms. MT suppressed the lysosome formation as well as its function by downregulation of the lysosome-associated genes Lysosome-associated membrane protein 2 (LAMP2), Insulin-like growth factor 2 receptor (IGF2R), and Arylsulfatase B (ARSB). A high level of MT enhanced the antioxidant capacity of these cells to reduce the cell apoptosis induced by the LPS. In addition, the results also uncovered previously unknown information that showed that MT may have protective effects on some human diseases, including tuberculosis, bladder cancer, and rheumatoid arthritis, by downregulation of these disease-associated genes. All these observations warranted further investigations.

With recent significant development in the portable device market, cloud computing is getting more and more utilized. Many sensitive data are stored in cloud central servers. To ensure privacy, these data are usually encrypted before being uploaded—making file searching complicated. Although previous cloud computing searchable encryption schemes allow users to search encrypted data by keywords securely, these techniques only support exact keyword search and will fail if there are some spelling errors or if some morphological variants of words are used. In this paper, we provide the solution for fuzzy keyword search over encrypted cloud data. K-grams is used to produce fuzzy results. For security reasons, we use two separate servers that cannot communicate with each other. Our experiment result shows that our system is effective and scalable to handle large number of encrypted files.

Accounting for 10% of the electricity consumption in the US, artificial lighting represents one of the easiest ways to cut household energy bills and greenhouse gas (GHG) emissions by upgrading to energy-efficient technologies such as compact fluorescent lamps (CFL) and light emitting diodes (LED). However, given the high initial cost and rapidly improving trajectory of solid-state lighting today, estimating the right time to switch over to LEDs from a cost, primary energy, and GHG emissions perspective is not a straightforward problem. This is an optimal replacement problem that depends on many determinants, including how often the lamp is used, the state of the initial lamp, and the trajectories of lighting technology and of electricity generation. In this paper, multiple replacement scenarios of a 60 watt-equivalent A19 lamp are analyzed and for each scenario, a few replacement policies are recommended. For example, at an average use of 3 hr day−1 (US average), it may be optimal both economically and energetically to delay the adoption of LEDs until 2020 with the use of CFLs, whereas purchasing LEDs today may be optimal in terms of GHG emissions. In contrast, incandescent and halogen lamps should be replaced immediately. Based on expected LED improvement, upgrading LED lamps before the end of their rated lifetime may provide cost and environmental savings over time by taking advantage of the higher energy efficiency of newer models.

As cloud computing becomes more and more utilized, sensitive data are being stored in cloud central servers. To ensure privacy, these data are usually encrypted before uploading, which makes searching complicated. In this paper we propose architecture of fuzzy keyword search with safe index. Bloom filter is used to build safe index which increases the searching effectiveness on a large dataset. The size of index is fixed so that the space efficiency is promoted. The experiment result shows that our searching scheme is effective and can be adapted to large encrypted file system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3419