Innovative or Not? The Effects of Consumer Perceived Value on Purchase Intentions for the Palace Museum’s Cultural and Creative Products

A museum’s core activities traditionally focus on such areas as collections’ care, exhibitions and scholarship. Income generation, including retail activities, is considered secondary. Academic research into museums’ merchandise, especially into the perceived value and purchase intentions, is limited. Drawing on literature embracing both core museum functions and marketing, this research, based on the Palace Museum in Beijing, China, explores the impact of the perceived value of a museum’s cultural and creative products on purchase intentions. Combining the results of in-depth interviews with museum visitors and experts, this study defines a construct composed of six perceived value dimensions, namely quality, social, price, innovation, educational, and experience values. A relationship model of perceived value and purchase intentions is proposed. Some 346 valid survey responses were obtained by distributing a questionnaire online and on-site at the Palace Museum, and hypotheses were tested by structural equation modelling. Results showed that innovation and experience values have a significant positive effect on purchase intentions, while quality, social, price, and educational values had no significant influence on purchase intentions. This research outlines feasible strategies and actions for the development of cultural and creative products at museums that have a strong tourism role

Monitoring Reaction Intermediates in Plasma-Driven SO2, NO, and NO2 Remediation Chemistry Using in Situ SERS Spectroscopy

In situ surface-enhanced Raman scattering (SERS) spectroscopy is used to identify the key reaction intermediates during the plasma-based removal of NO and SO2 under dry and wet conditions on Ag nanoparticles. Density functional theory (DFT) calculations are used to confirm the experimental observations by calculating the vibrational modes of the surface-bound intermediate species. Here, we provide spectroscopic evidence that the wet plasma increases the SO2 and the NOx removal through the formation of highly reactive OH radicals, driving the reactions to H2SO4 and HNO3, respectively. We observed the formation of SO3 and SO4 species in the SO2 wet-plasma-driven remediation, while in the dry plasma, we only identified SO3 adsorbed on the Ag surface. During the removal of NO in the dry and wet plasma, both NO2 and NO3 species were observed on the Ag surface; however, the concentration of NO3 species was enhanced under wet-plasma conditions. By closing the loop between the experimental and DFT-calculated spectra, we identified not only the adsorbed species associated with each peak in the SERS spectra but also their orientation and adsorption site, providing a detailed atomistic picture of the chemical reaction pathway and surface interaction chemistry.Fil: Li, Shujin. University of Southern California; Estados UnidosFil: Zhao, Bofan. University of Southern California; Estados UnidosFil: Aguirre, Alejo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Wang, Yu. University of Southern California; Estados UnidosFil: Li, Ruoxi. University of Southern California; Estados UnidosFil: Yang, Sisi. University of Southern California; Estados UnidosFil: Aravind, Indu. University of Southern California; Estados UnidosFil: Cai, Zhi. University of Southern California; Estados UnidosFil: Chen, Ran. University of Southern California; Estados UnidosFil: Jensen, Lasse. University of Southern California; Estados UnidosFil: Cronin, Stephen B.. University of Southern California; Estados Unido

Differential expression of cyclins CCNB1 and CCNG1 is involved in the chondrocyte damage of kashin-beck disease

The purpose of this study was clarify the relationship between the differential expression of cyclins CCNB1 and CCNG1 and chondrocyte damage in Kashin-Beck disease. Systematic review and high-throughput sequencing of chondrocytes derived from Kashin-Beck disease patients were combined to identify the differentially expressed cyclins and cyclin-dependent kinase genes. In parallel, weaned SD rats were treated with low selenium for 4 weeks and then T-2 toxin for 4 weeks. Knee cartilage was collected to harvest chondrocytes for gene expression profiling. Finally, the protein expression levels of CCNB1 and CCNG1 were verified in knee cartilage tissue of Kashin-Beck disease patients and normal controls by immunohistochemical staining. The systematic review found 52 cartilage disease-related cyclins and cyclin-dependent kinase genes, 23 of which were coexpressed in Kashin-Beck disease, including 15 upregulated and 8 downregulated genes. Under the intervention of a low selenium diet and T-2 toxin exposure, CCNB1 (FC = 0.36) and CCNG1 (FC = 0.73) showed a downward expression trend in rat articular cartilage. Furthermore, compared to normal controls, CCNB1 protein in Kashin-Beck disease articular cartilage was 71.98% and 66.27% downregulated in the superficial and middle zones, respectively, and 12.06% upregulated in the deep zone. CCNG1 protein was 45.66% downregulated in the superficial zone and 12.19% and 9.13% upregulated in the middle and deep zones, respectively. The differential expression of cyclins CCNB1 and CCNG1 may be related to articular cartilage damage in Kashin-Beck disease

Streamflow Forecasting via Two Types of Predictive Structure-Based Gated Recurrent Unit Models

Data-intelligent methods designed for forecasting the streamflow of the Fenhe River are crucial for enhancing water resource management. Herein, the gated recurrent unit (GRU) is coupled with the optimization algorithm improved grey wolf optimizer (IGWO) to design a hybrid model (IGWO-GRU) to carry out streamflow forecasting. Two types of predictive structure-based models (sequential IGWO-GRU and monthly IGWO-GRU) are compared with other models, such as the single least-squares support vector machine (LSSVM) and single extreme learning machine (ELM) models. These models incorporate the historical streamflow series as inputs of the model to forecast the future streamflow with data from January 1956 to December 2016 at the Shangjingyou station and from January 1958 to December 2016 at the Fenhe reservoir station. The IGWO-GRU model exhibited a strong ability for mapping in streamflow series when the parameters were carefully tuned. The monthly predictive structure can effectively extract the instinctive hydrological information that is more easily learned by the predictive model than the traditional sequential predictive structure. The monthly IGWO-GRU model was found to be a better forecasting tool, with an average qualification rate of 91.66% in two stations. It also showed good performance in absolute error and peak flow forecasting

Foxtail Millet Ear Detection Method Based on Attention Mechanism and Improved YOLOv5

In the foxtail millet field, due to the dense distribution of the foxtail millet ears, morphological differences among foxtail millet ears, severe shading of stems and leaves, and complex background, it is difficult to identify the foxtail millet ears. To solve these practical problems, this study proposes a lightweight foxtail millet ear detection method based on improved YOLOv5. The improved model proposes to use the GhostNet module to optimize the model structure of the original YOLOv5, which can reduce the model parameters and the amount of calculation. This study adopts an approach that incorporates the Coordinate Attention (CA) mechanism into the model structure and adjusts the loss function to the Efficient Intersection over Union (EIOU) loss function. Experimental results show that these methods can effectively improve the detection effect of occlusion and small-sized foxtail millet ears. The recall, precision, F1 score, and mean Average Precision (mAP) of the improved model were 97.70%, 93.80%, 95.81%, and 96.60%, respectively, the average detection time per image was 0.0181 s, and the model size was 8.12 MB. Comparing the improved model in this study with three lightweight object detection algorithms: YOLOv3_tiny, YOLOv5-Mobilenetv3small, and YOLOv5-Shufflenetv2, the improved model in this study shows better detection performance. It provides technical support to achieve rapid and accurate identification of multiple foxtail millet ear targets in complex environments in the field, which is important for improving foxtail millet ear yield and thus achieving intelligent detection of foxtail millet

Isolation of biosynthesis related transcripts of 2,3,5,4'-tetrahydroxy stilbene-2-O-β-D-glucoside from Fallopia multiflora by suppression subtractive hybridization

2,3,5,4'-tetrahydroxy stilbene-2-O-ß-D-glucoside (THSG) exerts multiple pharmacodynamic actions, found in Fallopia multiflora, but the biosynthesis pathway of THSG is still unclear. To clear this ambiguity, we constructed suppression subtractive hybridization (SSH) libraries to screen the genes involved in THSG biosynthesis from two F. multiflora varieties, which vary significantly in THSG content. Twelve non-redundant differentially expressed sequence tags were obtained and the full lengths of 4 unreported fragments were amplified by rapid amplification of cDNA ends. We totally got 7 full-length transcripts, and all of them were aligned to the transcriptome and digital gene expression tag profiling database of four F. multiflora tissues (root, stem and leaf from Deqing F. multiflora and another root from Chongqing F. multiflora; data unpublished) using local BLAST. The results showed that there was a significant, organ specific difference in the expression of fragments and full-length sequences. All the sequences were annotated by aligning to nucleotide and protein databases. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that THSG biosynthesis was correlated with multiple life activities

In situ synthesis of nickel-boron amorphous alloy nanoparticles electrode on nanoporous copper film/brass plate for ethanol electro-oxidation

Fujian Provincial Natural Science Foundation [2010J01292]; Fund of Fujian Provincial Key Laboratory of Nanomaterials [NM10-04]; Program for Excellent Talents of Huaqiao University, PR China [08BS205]Ni-B amorphous alloy nanoparticles electrode (Ni-B/NPCF) has been synthesized in situ by microinjection method on nanoporous Cu film (NPCF) fabricated on brass plate by dealloying method. The structure, morphology and electrochemical performance of the electrode are obtained by X-ray diffraction, scanning electron microscopy, cyclic voltammetry (CV), double potential step chronoamperometry (DPSCA) and linear sweep voltammetry (LSV). The results show the Ni-B alloy is amorphous with atom clusters structure consisting of nanoparticles with the size of 50-100 nm. The values of proton diffusion coefficient and redox species of the Ni-B/NPCF electrode are more than an order of magnitude as big as the reported values. Ethanol oxidation in KOH solution at the Ni-B/NPCF electrode suggests the onset oxidation potential has a negative shift of 49 mV and the oxidation peak current increases by 43.36 times, and the reaction activation free energy decreases by 254.37 kJ mol(-1), in comparison with the bulk Ni electrode. In addition, the reaction rate constant for ethanol oxidation at the Ni-B/NPCF electrode is improved by about two orders of magnitude compared with the reported value. Finally, the CV test indicates the Ni-B/NPCF electrode has a relatively stable redox behavior after 1000 potential cycles. Copyright (C) 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved

Synthesis of functionalized 4H-Chromenes catalyzed by lipase immobilized on magnetic nanoparticles

In the work, mucor miehei lipase (MML) was covalently immobilized on the 2,4,6-trichloro-1,3,5-triazine (TCT)-modified magnetite nanoparticles. Then, the immobilized MML was utilized in the synthesis of functionalized 4H-Chromenes via a multicomponent reaction firstly. Under the optimized reaction conditions, immobilized MML displayed high catalytic performance (Yield: 81–96%) and excellent reusability, indicating a high potential for practical operation

Prediction of BMI traits in the Chinese population based on the gut metagenome

Abstract Background Identifying individual characteristics based on trace evidence left at a crime scene is crucial in forensic identification. Microbial communities found in fecal traces have high individual specificity and could serve as potential markers for forensic characterization. Previous research has established that predicting body type based on the relative abundance of the gut microbiome is relatively accurate. However, the long-term stability and high individual specificity of the gut microbiome are closely linked to changes at the genome level of the microbiome. No studies have been conducted to deduce body shape from genetic traits. Therefore, in this study, the vital role of gut bacterial community characteristics and genetic traits in predicting body mass index (BMI) was investigated using gut metagenomic data from a healthy Chinese population. Results Regarding the gut microbial community, the underweight group displayed increased α-diversity in comparison to the other BMI groups. There were significant differences in the relative abundances of 19 species among these three BMI groups. The BMI prediction model, based on the 31 most significant species, showed a goodness of fit (R2) of 0.56 and a mean absolute error (MAE) of 2.09 kg/m2. The overweight group exhibited significantly higher α-diversity than the other BMI groups at the level of gut microbial genes. Furthermore, there were significant variations observed in the single-nucleotide polymorphism (SNP) density of 732 contigs between these three BMI groups. The BMI prediction model, reliant on the 62 most contributing contigs, exhibited a model R2 of 0.72 and an MAE of 1.56 kg/m2. The model predicting body type from 44 contigs correctly identified the body type of 93.55% of the study participants. Conclusion Based on metagenomic data from a healthy Chinese population, we demonstrated the potential of genetic traits of gut bacteria to predict an individual’s BMI. The findings of this study suggest the effectiveness of a novel method for determining the body type of suspects in forensic applications using the genetic traits of the gut microbiome and holds great promise for forensic individual identification