Regulation of welding residual stress in laser-welded AISI 304 steel-niobium joints using a Cu interlayer

Residual stress and deformation in a welded joint will significantly reduce its service life, and thus the analysis and regulation of residual stresses are very important. In this paper, a SYSWELD software was used to numerically simulate the temperature field, residual stress field, and the welding deformation during welding with and without a Cu interlayer. Thermocouples were used to measure the thermal cycle curves, and X-ray diffraction (XRD) was used to measure the residual stresses of the joints. The results show that the addition of a Cu interlayer does not significantly change the temperature field, and that the high temperature region on the niobium side is wider. In addition, the peak temperature in the centre of the welds and the temperature gradient perpendicular to the weld are greatly reduced by a Cu interlayer. Furthermore, a Cu interlayer contributes to a certain increase in both transverse and longitudinal residual stresses. Because the weld involves three different materials, steel, niobium, and Cu, the residual stresses in the welds are more complex. The simulation of the welding deformation shows that the transverse shrinkage in the thickness direction can be homogenized by the Cu interlayer, which leads to a significant reduction in deformation.acceptedVersio

Deep Learning Overloaded Vehicle Identification for Long Span Bridges Based on Structural Health Monitoring Data

Overloaded vehicles bring great harm to transportation infrastructures. BWIM (bridge weigh-in-motion) method for overloaded vehicle identification is getting more popular because it can be implemented without interruption to the traffic. However, its application is still limited because its effectiveness largely depends on professional knowledge and extra information, and is susceptible to occurrence of multiple vehicles. In this paper, a deep learning based overloaded vehicle identification approach (DOVI) is proposed, with the purpose of overloaded vehicle identification for long-span bridges by the use of structural health monitoring data. The proposed DOVI model uses temporal convolutional architectures to extract the spatial and temporal features of the input sequence data, thus provides an end-to-end overloaded vehicle identification solution which neither needs the influence line nor needs to obtain velocity and wheelbase information in advance and can be applied under the occurrence of multiple vehicles. Model evaluations are conducted on a simply supported beam and a long-span cable-stayed bridge under random traffic flow. Results demonstrate that the proposed deep-learning overloaded vehicle identification approach has better effectiveness and robustness, compared with other machine learning and deep learning approaches

Analysis of a Periodic Single Species Population Model Involving Constant Impulsive Perturbation

This is a continuation of the work of Tan et al. (2012). In this paper a periodic single species model controlled by constant impulsive perturbation is investigated. The constant impulse is realized at fixed moments of time. With the help of the comparison theorem of impulsive differential equations and Lyapunov functions, sufficient conditions for the permanence and global attractivity are established, respectively. Also, by comparing the above results with corresponding known results of Tan et al. (2012) (i.e., the above model with linear impulsive perturbations), we find that the two different types of impulsive perturbations have influence on the above dynamics. Numerical simulations are presented to substantiate our analytical results

Entrepreneurial orientation and external technology acquisition: an empirical test on performance of technology-based new ventures

This research investigates the effects of entrepreneurial orientation and external technology acquisition on the performance of technology-based new ventures in the context of a transitional economy. An analysis of the cross-sectional data from 123 Chinese technology-based new ventures was conducted. The results of the analysis support the contention that both the acquisition of external technology and entrepreneurial orientation improve new ventures’ performance. Additionally, the interaction of entrepreneurial orientation and external technology acquisition positively moderates the relationship between entrepreneurial orientation and performance of technology-based new ventures. Overall, this study contributes to our enhanced understanding of the complex relationship among entrepreneurial orientation, external technology acquisition and firm performance under transitional economic conditions. Firms from emerging economies, especially technologybased new ventures, may find the study findings useful in guiding their decision on external technology acquisition

Delivery of Quantum Dot-siRNA Nanoplexes in SK-N-SH Cells for BACE1 Gene Silencing and Intracellular Imaging

The fluorescent quantum dots (QDs) delivered small interfering RNAs (siRNAs) targeting β-secretase (BACE1) to achieve high transfection efficiency of siRNAs and reduction of β-amyloid (Aβ) in nerve cells. The CdSe/ZnS QDs with the conjugation of amino-polyethylene glycol (PEG) were synthesized. Negatively charged siRNAs were electrostatically adsorbed to the surface of QDs to develop QD-PEG/siRNA nanoplexes. The QD-PEG/siRNAs nanoplexes significantly promote the transfection efficiency of siRNA, and the siRNAs from non-packaged nanoplexes were widely distributed in cell bodies and processes and efficiently silenced BACE1 gene, leading to the reduction of Aβ. The biodegradable PEG polymer coating could protect QDs from being exposed to the intracellular environment and restrained the release of toxic Cd2+. Therefore, the QD-PEG/siRNA nanoplexes reported here might serve as ideal carriers for siRNAs. We developed a novel method of siRNA delivery into nerve cells. We first reported that the QD-PEG/siRNA nanoplexes were generated by the electrostatic interaction and inhibited the Alzheimer's disease (AD)-associated BACE1 gene. We also first revealed the dynamics of QD-PEG/siRNAs within nerve cells via confocal microscopy and the ultrastructural evidences under transmission electron microscopy (TEM). This technology might hold promise for the treatment of neurodegenerative diseases such as AD

Rational Design of Synergistic Structure Between Single-Atoms and Nanoparticles for CO2 Hydrogenation to Formate Under Ambient Conditions

Single-atom catalysts (SACs) as the new frontier in heterogeneous catalysis have attracted increasing attention. However, the rational design of SACs with high catalytic activities for specified reactions still remains challenging. Herein, we report the rational design of a Pd1-PdNPs synergistic structure on 2,6-pyridinedicarbonitrile-derived covalent triazine framework (CTF) as an efficient active site for CO2 hydrogenation to formate under ambient conditions. Compared with the catalysts mainly comprising Pd1 and PdNPs, this hybrid catalyst presented significantly improved catalytic activity. By regulating the ratio of Pd1 to PdNPs, we obtained the optimal catalytic activity with a formate formation rate of 3.66 molHCOOM·molPd−1·h−1 under ambient conditions (30°C, 0.1 MPa). Moreover, as a heterogeneous catalyst, this hybrid catalyst is easily recovered and exhibits about a 20% decrease in the catalytic activity after five cycles. These findings are significant in elucidating new rational design principles for CO2 hydrogenation catalysts with superior activity and may open up the possibilities of converting CO2 under ambient conditions

Recent advances in hydrothermal carbonisation:from tailored carbon materials and biochemicals to applications and bioenergy

Introduced in the literature in 1913 by Bergius, who at the time was studying biomass coalification, hydrothermal carbonisation, as many other technologies based on renewables, was forgotten during the "industrial revolution". It was rediscovered back in 2005, on the one hand, to follow the trend set by Bergius of biomass to coal conversion for decentralised energy generation, and on the other hand as a novel green method to prepare advanced carbon materials and chemicals from biomass in water, at mild temperature, for energy storage and conversion and environmental protection. In this review, we will present an overview on the latest trends in hydrothermal carbonisation including biomass to bioenergy conversion, upgrading of hydrothermal carbons to fuels over heterogeneous catalysts, advanced carbon materials and their applications in batteries, electrocatalysis and heterogeneous catalysis and finally an analysis of the chemicals in the liquid phase as well as a new family of fluorescent nanomaterials formed at the interface between the liquid and solid phases, known as hydrothermal carbon nanodots