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AbstractThis paper studied the vibro-acoustic characteristics of functionally graded sandwich plate in hygrothermal environment, where the core layer is composed of functionally graded materials with viscoelasticity. The viscoelastic behavior of the materials is described by a linear standard solid viscoelastic model, and the viscoelastic parameters are dependent of the frequency. Based on the first-order shear deformation theory and the linear deformation, the dynamic governing equation and acoustic formulas are established. By solutions the complex frequency, sound insulation and acoustic radiation responses of the plate are obtained. Then the effects of parameter variations on the vibration and acoustic performances are analyzed. [ABSTRACT FROM AUTHOR]

The core layer is very important in studying the vibration and noise problems of sandwich structures. The present paper studied the free vibration and sound insulation characteristics of FG-CNTRC sandwich plates with FG-CNT face sheets and different cores including the soft core (epoxy), hard core (aluminum) and porous metal foam core with different porosity distributions. By Hamilton's principle the dynamic equations of FG-CNTRC sandwich plates are formulated based on the third-order shear deformation theory (TSDT), and the sound insulation expression is given under the excitation of the sound pressure. The theoretical solution of natural frequency and sound insulation are compared with the finite element simulation results and validated. The natural frequency of the square sandwich plate are compared with the rectangular case. The free vibration and sound insulation performance of FG-CNTRC sandwich plates are analyzed and discussed, and parametric studies are performed to evaluate the effects of CNT volume fraction, CNT distribution patterns, CNT orientation angles, porosity coefficient and incident angles on the vibro-acoustic characteristics of the sandwich plate. Some new results are presented to be used as references for the further research. [ABSTRACT FROM AUTHOR]

Nutrients such as phosphorus and nitrogen lead to extensive growth of harmful algae in lakes and reservoirs, which results in eutrophication. The driving mechanism of primary productivity change in lakes and reservoirs at a wide spatial and temporal scale remains largely unknown. We establish a water quality database using a stacking machine learning model, including monthly chlorophyll‐a (Chl‐a), total nitrogen (TN) and phosphorus (TP) concentrations in 255 lakes and 332 reservoirs from 1980 to 2018. We find an increase in the number of lakes and reservoirs at risk of algal blooms, with approximately 2.66% exhibiting Chl‐a concentrations exceeding 30 μg L−1 by 2018. Variations in Chl‐a concentrations were not entirely synchronized at the individual and regional levels with TN and TP concentrations, or their stoichiometric ratios, as estimated by a hierarchical linear model spanning 1980 to 2018. Further, we discovered unexpected effects of geographical features (i.e., latitude, longitude, and slope) and meteorological factors (i.e., air temperature) on Chl‐a concentrations in the lakes and reservoirs with higher TP concentrations (>0.041 mg L−1 for lakes and >0.027 mg L−1 for reservoirs), through the use of multiple regression trees and structural equation model analysis. Our findings underscore the importance of (a) implementing flexible nutrient pollution control approaches based on nutrient ecoregions that consider geographical variations, and (b) developing mitigation and adaptation strategies to address the uncertain risks posed by climate change in the prevention and control of eutrophication in lakes and reservoirs. Key Points: We achieved high accuracy in predicting Chl‐a concentrations using a stacking modelTN and TP and their stoichiometric ratios did not always align with Chl‐a concentrationsGeographical characteristics and climatic influences dominate the Chl‐a concentrations with higher TP concentrations [ABSTRACT FROM AUTHOR]

BACKGROUND: The Angoumois grain moth, Sitotroga cerealella, is a destructive pest of maize, wheat, and rice, causing economic losses and threatening food security. This study aimed to develop and characterize microcapsules of mesoporous silica nanospheres (MSN) and cyclodextrin‐modified mesoporous silica nanospheres (CDMSN) containing two aldehydes, nonanal and decanal, found in plant essential oils, to assess their attractiveness to S. cerealella populations. RESULTS: Microcapsules with 2:1 ratio of nonanal and decanal exhibited an average encapsulation efficiency of 39.82% for MSN loaded with nonanal and decanal (MSN‐ND) and 46.10% for CDMSN loaded with nonanal and decanal (CDMSN‐ND). They have an elliptical shape with particle sizes of 115 nm for MSN and 175 nm for CDMSN. Gas chromatography–mass spectrometry analysis revealed in vitro release of nonanal in MSN at 96.24% and decanal at 96.42% by the 36th day. CDMSN showed releases of 93.83% for nonanal and 93.74% for decanal by the 50th day. CDMSN‐ND attracted adult S. cerealella for 43 days, while MSN‐ND remained effective for 29 days. In mass trapping assays in simulated grain warehouse, both MSN‐ND and CDMSN‐ND trapped over 50% of the adult population within 7 days, significantly reducing grain infestation rates below 10% by inhibiting F1 adult emergence. At temperatures ranging from 20 °C to 35 °C, both microcapsules exhibited significant and effective attraction rates for S. cerealella. Stored wheat seeds treated with CDMSN and CDMSN‐ND over 1 year showed no significant differences in key germination parameters. CONCLUSION: Microencapsulated nonanal and decanal offer a promising, sustainable approach for controlling S. cerealella infestation in stored grains, contributing to global food security. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Author(s): Lian Feng [sup.1] [sup.2] , Yanhui Dai [sup.1] [sup.2] , Xuejiao Hou [sup.1] [sup.2] , Yang Xu [sup.1] [sup.2] , Junguo Liu [sup.1] [sup.2] , Chunmiao Zheng [sup.1] [sup.2] [...]