Hydrophobic multiscale cavities for high-performance and self-cleaning surface-enhanced Raman spectroscopy (SERS) sensing

Cavity array, with excellent optical capture capability, has received increasing attention for the surface-enhanced Raman spectroscopy (SERS)-active substrates. Here, we proposed molybdenum disulfide (MoS2) nanocavities growing on pyramid Si (PSi) composed of in situ reduced Au nanoparticles (AuNPs), which can form the multiscale cavities (MSCs), and is facile for the couple of the plasmon. We demonstrated that the PSi/MoS2/Au MSCs can serve as highly sensitive, uniform, and stable SERS substrates for rhodamine 6G (R6G), crystal violet, and adenosine triphosphate detection, benefiting from the synergistic effect of the enhanced light trapping and the effective plasmonic couple. The couple of the plasmon in the MSCs is evidently proved by finite-difference time domain simulation, showing the strong electromagnetic field is located around the cavity wall. Moreover, the excellent hydrophobicity of the PSi/MoS2/AuNPs substrate endows it with the ability for the directional monitoring of organic pollutant in a mixture of oil and water. Finally, we demonstrated the MSCs with outstanding photocatalytic performance could achieve the renewable utilization by self-cleaning, which was attributed to the fast electron transfer and effective light absorption. The proposed PSi/MoS2/AuNPs MSC represents a robust mean using the plasmonic metal/semiconductor heterostructure for high-performance SERS sensors and photodegradation

Tribological properties and wear mechanisms of DC pulse plasma nitrided austenitic stainless steel in dry reciprocating sliding tests

Expanded austenite (Gamma-N), or S-phase, is a special phase of low-temperature nitrided austenite containing highly super-saturated nitrogen in the form of heterogeneous Cr-N nano-clusters. A nitrided layer of singe phase N is known to provide austenitic stainless steel with combined high hardness, good wear resistance and superior corrosion resistance. This paper reports recent experiments on a comparative study of the sliding wear properties and wear mechanisms of nitrided austenite stainless steel AISI 316, with a special attention paid on worn surface structural evolutions induced by frictional heating and sliding deformation. The samples were prepared by DC pulsed plasma nitriding treatments of various time at a fixed power. Knoop micro-indentation has revealed hardening behaviour of the nitrided samples. The reciprocating ball-on-disc sliding wear and friction properties were investigated at ambient environment conditions using an alumina counterpart ball. The worn surfaces have been analysed by XRD,FEG-SEM and EDX to show wear induced changes in the crystalline characteristics and the wear mechanisms of tribo-oxidation, cracking, abrasive wear and ploughing deformation. Moreover, longitudinal cross-sectional foils of the worn samples have been prepared and analysed using TEM, to investigate the wear induced structural changes, including tribofilm formation, plastic deformation and delamination in depths of nano-scale

The effect of precursor concentration on the particle size, crystal size, and optical energy gap of CexSn1â’xO2 nanofabrication

In the present work, a thermal treatment technique is applied for the synthesis of CexSn1−xO2 nanoparticles. Using this method has developed understanding of how lower and higher precursor values affect the morphology, structure, and optical properties of CexSn1−xO2 nanoparticles. CexSn1−xO2 nanoparticle synthesis involves a reaction between cerium and tin sources, namely, cerium nitrate hexahydrate and tin (II) chloride dihydrate, respectively, and the capping agent, polyvinylpyrrolidone (PVP). The findings indicate that lower x values yield smaller particle size with a higher energy band gap, while higher x values yield a larger particle size with a smaller energy band gap. Thus, products with lower x values may be suitable for antibacterial activity applications as smaller particles can diffuse through the cell wall faster, while products with higher x values may be suitable for solar cell energy applications as more electrons can be generated at larger particle sizes. The synthesized samples were profiled via a number of methods, such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). As revealed by the XRD pattern analysis, the CexSn1−xO2 nanoparticles formed after calcination reflect the cubic fluorite structure and cassiterite-type tetragonal structure of CexSn1−xO2 nanoparticles. Meanwhile, using FT-IR analysis, Ce-O and Sn-O were confirmed as the primary bonds of ready CexSn1−xO2 nanoparticle samples, whilst TEM analysis highlighted that the average particle size was in the range 6−21 nm as the precursor concentration (Ce(NO3)3·6H2O) increased from 0.00 to 1.00. Moreover, the diffuse UV-visible reflectance spectra used to determine the optical band gap based on the Kubelka–Munk equation showed that an increase in x value has caused a decrease in the energy band gap and vice versa

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

LST-GCN: Long Short-Term Memory Embedded Graph Convolution Network for Traffic Flow Forecasting

Traffic flow prediction is an important part of the intelligent transportation system. Accurate traffic flow prediction is of great significance for strengthening urban management and facilitating people’s travel. In this paper, we propose a model named LST-GCN to improve the accuracy of current traffic flow predictions. We simulate the spatiotemporal correlations present in traffic flow prediction by optimizing GCN (graph convolutional network) parameters using an LSTM (long short-term memory) network. Specifically, we capture spatial correlations by learning topology through GCN networks and temporal correlations by embedding LSTM networks into the training process of GCN networks. This method improves the traditional method of combining the recurrent neural network and graph neural network in the original spatiotemporal traffic flow prediction, so it can better capture the spatiotemporal features existing in the traffic flow. Extensive experiments conducted on the PEMS dataset illustrate the effectiveness and outperformance of our method compared with other state-of-the-art methods

Study on noise enhancement injection in laser gyroscopes based on random noise variation rates

In the process of injecting random noise into a mechanical vibration laser gyroscope, the amplitude of the injected noise decays significantly as the noise frequency increases. To address this phenomenon, theoretical research was conducted on the transfer function of random noise in a mechanical vibration laser gyroscope, and a transfer function of random noise enhancement injection efficiency was established, which is related to the damping coefficient and resonant frequency. A method for enhancing random noise injection efficiency based on the rate of random noise level variation was proposed, and a circuit system for random noise enhancement injection in mechanical vibration laser gyroscopes was designed. The results showed that compared with the original random noise injection technology, random noise enhancement injection technology can effectively suppress the serious attenuation of high-frequency random noise amplitude, increase random noise injection efficiency by about 41.27%, reduce the random walk of the laser gyroscope's angle by about 17.73%, and improve its accuracy by about 27.02%. Random noise enhancement injection technology provides an important reference for improving the performance of mechanical vibration laser gyroscopes

Delivery of infection from asymptomatic carriers of COVID-19 in a familial cluster

OBJECTIVES: With the ongoing outbreak of COVID-19 around the world, it has become a worldwide health concern. One previous study reported a family cluster with asymptomatic transmission of COVID-19. Here, we report another series of cases and further demonstrate the repeatability of the transmission of COVID-19 by pre-symptomatic carriers. METHODS: A familial cluster of five patients associated with COVID-19 was enrolled in the hospital. We collected epidemiological and clinical characteristics, laboratory outcomes from electronic medical records, and also affirmed them with the patients and their families. RESULTS: Among them, three family members (Case 3/4/5) had returned from Wuhan. Additionally, two family members, those who had not travelled to Wuhan, also contracted COVID-19 after contacting with the other three family members. Case 1 developed severe pneumonia and was admitted to the ICU. Case 3 and Case 5 presented fever and cough on days 2 through 3 of hospitalization and had ground-glass opacity changes in their lungs. Case 4 presented with diarrhoea and pharyngalgia after admission without radiographic abnormalities. Case 2 presented no clinical or radiographic abnormalities. All the cases had an increasing level of C-reactive protein. CONCLUSIONS: Our findings indicate that COVID-19 can be transmitted by asymptomatic carriers during the incubation period

Effect of Ag nanoparticles on wafer-scale quasi-free-standing graphene characterization by surface enhanced Raman spectroscopy

Quasi-free-standing graphene (QFSG) obtained by H intercalation on SiC (0001) substrate paves a new way for widening the applications in microelectronics field. In this work, the direct and efficient characterization of wafer-scale quasi-free-standing graphene on SiC was presented by Ag-assisting Raman spectroscopy. The Si-H peak existing at the interface between graphene and substrate was tested unambiguously. The effects of Ag distribution and particle size on Raman enhancement were clarified both theoretically and experimentally. It was found that relative larger Ag particles at aggregation area were accompanied with the better enhancement. Moreover, Raman mapping with Ag assisting was executed on QFSG obtained under different growth conditions and the corresponding QFSG coverages were evaluated effectively. The optimum H intercalation temperature was determined to be around 1000 °C with the coverage being 73%. This study would supply a new approach for uniform and wafer-scale QFSG fabrication