LiNbO3 crystals activated by Sm3+ and co-doped with Zr4+ (Sm:Zr:LN) or Hf4+ (Sm:Hf:LN) were prepared by the Czochralski method. Detailed investigation on spectroscopic properties was conducted on the frame of Judd-Ofelt (J-O) theory. The J-O intensity parameters Ωi (i = 2, 4, 6), fluorescence branching ratios and radiative lifetime of excited level 4G5/2 were determined. Furthermore, the thermal stability of the strong orange-red emissions obtained under near-UV excitation in both crystals was evaluated. As high as 100% and 97% of integrated intensities at room temperature in Sm:Zr:LN and Sm:Hf:LN respectively were retained at 423 K, demonstrating the suppressed thermal attenuation. The temperature sensing performance based on fluorescence intensity ratio strategy was degraded at higher temperatures with relatively low sensitivities, while the shift of CIE chromaticity coordinates of Sm:Zr:LN and Sm:Hf:LN in the orange-red region was insignificant, demonstrating the color constancy with increasing temperature. With the efficient and thermally stable orange-red luminescence, Sm:Zr:LN and Sm:Hf:LN could serve as promising candidate materials for near-UV excited white light-emitting diodes. 相似文献
Cellulose microfibers (CMFs) having surfaces modified with polydopamine (PDPA) and octadecylamine (ODA) were prepared, and their reinforcing abilities for polypropylene (PP) were investigated. The PDPA coating was made via self-polymerization of dopamine (P-CMF), and subsequent alkylation was conducted by the reaction with ODA (OP-CMF). The modified CMFs exhibited improved dispersibility in the PP matrix due to the reduced hydrophilicity. The OP-CMF/PP composite prepared by batch mixing had a higher tensile modulus compared to that for the pure PP and composites with unmodified CMFs. However, excess alkylation lowered the tensile modulus, and the presence of an optimal degree of alkylation was demonstrated. The CMF/PP-IM composites fabricated by injection molding exhibited improved tensile properties compared to those prepared by batch mixing. Both the tensile modulus and yield stress were increased by increasing the CMF content and improved by the surface modification of the CMFs. 相似文献
Sampling or task jitter affects the performance of digital control systems but realistic simulation of this effect has not been possible to date. Our previous work has developed a novel method to simulate sampling jitter in MATLAB/Simulink simulation software where the jitter is generated randomly. What has been missing is a way to capture sampling jitter from a target platform and then feed this timing information into the simulation. This paper presents a low-cost and novel solution to these problems. The method uses an Arduino board to capture task jitter from two different hardware platforms with multiple stressing conditions. Then the recorded performance data is used to drive realistic simulations of a control system. Measurement shows that the task jitter data does not follow any specific random distribution such as Gaussian or Uniform. Furthermore, very occasional timing patterns, which may not be picked up while testing a real system, can result in extreme controller responses. This novel method allows comparisons of different platforms and reduces the effort required to choose the most appropriate platform for full implementation.
Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization. 相似文献
Fire spread and growth on real‐scale four cushion mock‐ups of residential upholstered furniture (RUF) were investigated with the goal of identifying whether changes in five classes of materials (barrier, flexible polyurethane foam, polyester fiber wrap, upholstery fabric, and sewing thread), referred to as factors, resulted in statistically significant changes in burning behavior. A fractional factorial experimental design plus practical considerations yielded a test matrix with 20 material combinations. Experiments were repeated a minimum of two times. Measurements included fire spread rates derived from video recordings and heat release rates (HRRs). A total of 13 experimental parameters (3 based on the videos and 10 on the HRR results), referred to as responses, characterized the measurements. Statistical analyses based on Main Effects Plots (main effects) and Block Plots (main effects and factor interactions) were used. The results showed that three of the factors resulted in statistically significant effects on varying numbers of the 13 responses. The Barrier and Fabric factors had the strongest main effects with roughly comparable magnitudes. Foam was statistically significant for fewer of the responses and its overall strength was weaker than for Barrier and Fabric. No statistically significant main effects were identified for Wrap or Thread. Multiple two‐term interactions between factors were identified as being statistically significant. The Barrier*Fabric interaction resulted in the highest number of and strongest statistically significant effects. The existence of two‐term interactions means that it will be necessary to consider their effects in approaches designed to predict the burning behavior of RUF. 相似文献