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Pyropia haitanensis was cultured under two CO2 (410 (LC), 1000 (HC) μL L-1) concentrations and six chloramphenicol (CAP)-methanol solutions (0, 0+methanol, 10, 50, 100, 250 μg mL-1) to investigate the effects of elevated CO2 and CAP on its growth, photosynthesis and biochemical characteristics. HC had no obvious effects on the growth rate (RGR) with CAP in the range of 10 to 100 μg mL-1, but the decrease of RGR by HC was statistically significant with the CAP dosage at 250 μg mL-1. HC had no significant effect on net photosynthetic rates (Pn) in the present of CAP (10-250 μg mL-1). CAP greatly reduced net photosynthesis as well as the maximal photochemical yield (Fv/Fm) and photosynthetic efficiency (αETR). In contrast, the maximum relative electron transport rates (rETRm) were almost constant with the CAP dosage from 10 to 100 μg mL-1. HC significantly increased the energy fluxes (per RC) for absorption (ABS/RC), trapping (TRo/RC) and transport fluxes (ETo/RC) with the dosage of CAP at 250 μg mL-1. Principal component analysis (PCA) indicated that CAP was positively correlated with the synthesis of free amino acids (FAA), contents of umami-, sweet- and essential AA were significantly enhanced with the interaction of HC and higher CAP dosage at 100 μg mL-1, which led to the variation of flavor in algae. Furthermore, phycobiliproteins and soluble protein (SP) contents were remarkably reduced by CAP. Contents of chlorophyll a (Chl a), carotenoids (Car), soluble carbohydrates (SC) and C/N ratios were almost unchanged among treatments. The study indicates that future ocean acidification has no obvious effects on the biomass productivity of P. haitanensis, maintained steady photosynthetic activities with the CAP (within 100 μg mL-1) and induces better flavor. The data obtained have important theoretical relevance for in-depth understanding of algal responses to global changes and oceanic contamination. [ABSTRACT FROM AUTHOR]

Byline: Xin. Li, Qi. Liu, Tongyang. Niu, Hongning. Jia, Tingting. Liu, Zikai. Xin, Zhiguang. Li, Xiaomeng. Zhou, Rui. Li, Yaling. Liu, Hui. Dong Objectives: Sleep disturbances are common in amyotrophic [...]

Stimuli‐responsive crystalline materials have received much attention for being potential candidates of smart materials. However, the occurrence of polymorphism‐driven stimuli responses in crystalline materials remains interesting but rare. Herein, three polymorphs of an acylhydrazone derivative, N′‐[(E)‐(1‐benzofuran‐2‐yl) methylidene] pyridine −4‐carbohydrazide (BFMP) were prepared. Form‐1 undergoes a photomechanical response via E→Z photoisomerization under UV irradiation, accompanied by a decrease in fluorescence intensity and a change from colorless to yellow. Two types of Z→E thermal isomerization mechanisms with significant differences in conversion rate were observed at different temperatures in form‐1. The solid‐melt‐solid transition has a faster conversion rate compared to the solid‐solid transition due to freedom from lattice confinement. The transition from form‐2 to form‐3 can be achieved under grinding, coupled with a significant decrease in fluorescence intensity. The similar molecular stacking pattern of form‐2 and form‐3 provides a structural basis for the grinding‐induced crystalline transition behavior. In addition, the presence of the pyridine moiety imparts an acidochromic property. The combination of photochromism and acidochromism explores the possible applications of acylhydrazone derivatives in information encryption. [ABSTRACT FROM AUTHOR]

The bulk density of the particles, which is directly related to transportation and storage costs, is an important basic characteristic of products as well as an important parameter in many processing systems. This work quantified the relationship between the tapped bulk density of raspberry ketone with different degrees of agglomeration and morphological metrics (particle shape descriptors and roughness descriptors) and size metrics (size descriptors) and developed an artificial neural network (ANN) prediction model for the tapped bulk density of raspberry ketone. Samples prepared under different conditions were sieved and remixed, the tapped bulk density of the particles was then measured, and the descriptor features of the particles were obtained by combining them with image processing. The dimensions of the variables were decreased by principal component analysis and variance processing. To overcome the hyperparameter estimation of the heuristic-based artificial neural networks, the network model architectures were optimized by a neural architecture search strategy combining two-objective optimization. The results demonstrated that the tapped bulk density of raspberry ketone products is not only related to the descriptors of particle size and shape but also has a non-negligible relationship with particle roughness descriptors. The performance of the optimal ANN model demonstrated that the model can well predict the tapped bulk density of raspberry ketone with different degrees of agglomeration. The ANN model obtained by extracting morphology and size metrics through online image analysis can be used to measure the tapped bulk density in real-time and has the potential to be used for developing model-based online process monitoring. [ABSTRACT FROM AUTHOR]