The habitual characteristic of smart phone use under relevant cues among Chinese college students

Excessive smartphone use may be habitual behavior induced by cues associated with the phone. Habitual behavior occurs outside of awareness and is characterized by lack of control. It is not like problematic smartphone use (PSU) (Brand et al., 2016), which is used to either limit behavior or produce pleasure and relieve feelings of pain, stress, and failure despite significant harmful consequences. 62 college students participated in experiments to test the effects of visual cues and self-control, which are the important characteristic of habitual behavior in smartphone-related behavior. The results showed that a significantly larger amount of cue-related phone use behavior occurred in the setting where participants (a) had their smartphones in sight and (b) were given no instructions to exert self-control, compared to when neither of the two conditions was imposed. The habitual model is a useful framework for understanding PSU and can help people avoid it with less stress. The results provide substantial implications for reducing the frequency and duration of smartphone use among college populations

Application of surface enhanced Raman scattering and competitive adaptive reweighted sampling on detecting furfural dissolved in transformer oil

Detecting the dissolving furfural in mineral oil is an essential technical method to evaluate the ageing condition of oil-paper insulation and the degradation of mechanical properties. Compared with the traditional detection method, Raman spectroscopy is obviously convenient and timesaving in operation. This study explored the method of applying surface enhanced Raman scattering (SERS) on quantitative analysis of the furfural dissolved in oil. Oil solution with different concentration of furfural were prepared and calibrated by high-performance liquid chromatography. Confocal laser Raman spectroscopy (CLRS) and SERS technology were employed to acquire Raman spectral data. Monte Carlo cross validation (MCCV) was used to eliminate the outliers in sample set, then competitive adaptive reweighted sampling (CARS) was developed to select an optimal combination of informative variables that most reflect the chemical properties of concern. Based on selected Raman spectral features, support vector machine (SVM) combined with particle swarm algorithm (PSO) was used to set up a furfural quantitative analysis model. Finally, the generalization ability and prediction precision of the established method were verified by the samples made in lab. In summary, a new spectral method is proposed to quickly detect furfural in oil, which lays a foundation for evaluating the ageing of oil-paper insulation in oil immersed electrical equipment

Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers

The aging of oil-paper insulation in power transformers may cause serious power failures. Thus, effective monitoring of the condition of the transformer insulation is the key to prevent major accidents. The purpose of this study was to explore the feasibility of confocal laser Raman spectroscopy (CLRS) for assessing the aging condition of oil-paper insulation. Oil-paper insulation samples were subjected to thermal accelerated ageing at 120 °C for up to 160 days according to the procedure described in the IEEE Guide. Meanwhile, the dimension of the Raman spectrum of the insulation oil was reduced by principal component analysis (PCA). The 160 oil-paper insulation samples were divided into five aging stages as training samples by clustering analysis and with the use of the degree of polymerization of the insulating papers. In addition, the features of the Raman spectrum were used as the inputs of a multi-classification support vector machine. Finally, 105 oil-paper insulation testing samples aged at a temperature of 130 °C were used to further test the diagnostic capability and universality of the established algorithm. Results demonstrated that CLRS in conjunction with the PCA-SVM technique provides a new way for aging stage assessment of oil-paper insulation equipment in the field

In Situ Detection of Trace Furfural in Aqueous Solution Based on Au Nanoparticle/Au Film Surface-Enhanced Raman Spectroscopy

Furfural is an important chemical solvent and intermediate. Sensitive detection of this compound has attracted great interest in various fields. Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive method for material detection because of its optical enhancement effect of plasmonic nanostructures. This study presents a simple and versatile method to synthesize a SERS substrate, where polyaminothiophenol (PATP) was used to realize the stable combination of Au nanoparticles (AuNPs) and Au film via self-assembly. The near-field electric field distribution was calculated using the finite difference time domain (FDTD) simulation to determine the parameters responsible for electric field enhancement. The simulation results show that SERS enhanced factors are sensitive to interparticle spacing and materials for solid support but insensitive to particle size. Moreover, the experimental results show that the optimized substrates with the highest Raman activity were formed by six layers of 60 nm AuNPs decorated on a 30 nm thick Au film, thereby validating the simulation results. The SERS factor of the optimal substrates is approximately 5.57 × 103, and the in situ detection limit is 4.8 ppm. The 3D Raman spectra, relative standard deviation values for major peaks, and changes in signal intensity with time show the good reproducibility and stability of the substrates

Promotion effects and mechanisms of molybdenum disulfide on the propagation of antibiotic resistance genes in soil

The rapid development of nanotechnology has aroused considerable attentions toward understanding the effects of engineered nanomaterials (ENMs) on the propagation of antibiotic resistance. Molybdenum disulfide (MoS2) is an extensively used ENM and poses potential risks associated with environmental exposure; nevertheless, the role of MoS2 toward antibiotic resistance genes (ARGs) transfer remains largely unknown. Herein, it was discovered that MoS2 nanosheets accelerated the horizontal transfer of RP4 plasmid across Escherichia coli in a dose-dependent manner (0.5–10 mg/L), with the maximum transfer frequency 2.07-fold higher than that of the control. Integration of physiological, transcriptomics, and metabolomics analyses demonstrated that SOS response in bacteria was activated by MoS2 due to the elevation of oxidative damage, accompanied by cell membrane permeabilization. MoS2 promoted bacterial adhesion and intercellular contact via stimulating the secretion of extracellular polysaccharides. The ATP levels were maximally increased by 305.7 % upon exposure to MoS2, and the expression of plasmid transfer genes was up-regulated, contributing to the accelerated plasmid conjugation and increased ARG abundance in soil. Our findings highlight the roles of emerging ENMs (e.g., MoS2) in ARGs dissemination, which is significant for the safe applications and risk management of ENMs under the development scenarios of nanotechnology

Fabrication of tunable hierarchical MXene@AuNPs nanocomposites constructed by self-reduction reactions with enhanced catalytic performances

MXene, a new type of two-dimensional layered transition metal carbide material differing from graphene, demonstrates intriguing chemical/physical properties and wide applications in recent years. Here, the preparation of the self-assembled MXene-gold nanoparticles (MXene@AuNPs) nanocomposites with tunable sizes is reported. The nanocomposites are obtained via the self-reduction reactions of MXene material in a HAuCl4 solution at room temperature. The sizes of the Au particles can be well-controlled by regulating the self-reduction reaction time. They can greatly influence the catalytic behaviors of the MXene@AuNPs composites. MXene@AuNPs composites with optimized reduction time show high catalytic performances and good cycle stability for model catalytic reactions of nitro-compounds, such as 2-nitrophenol and 4-nitrophenol. This work demonstrates a new approach for the preparation of tunable MXene-based self-assembled composites

Fabrication of hierarchical MXene-based AuNPs-containing core–shell nanocomposites for high efficient catalysts

MXene is a new type of layered two-dimensional transition metal carbide materials differing from graphene, demonstrating intriguing chemical/physical properties. Here the chemical modification of MXene and next fabrication of core–shell MXene–COOH@(PEI/PAA)n composites have been investigated. The obtained MXene-based composites were treated with gold nanoparticles to form MXene–COOH@(PEI/PAA)n@AuNPs nanocomposites, and their catalytic properties for nitro-compounds were studied. The prepared nanocomposites demonstrated good catalytic activity and reproducibility, showing potential applications in composite catalysts and environmental fields. Keywords: MXene, Core–shell composite, Nitro-compounds, Gold nanoparticle, Catalytic activit