Porous bulk superhydrophobic nanocomposites for extreme environments

Robust superhydrophobic materials providing protections from harsh weather events such as hurricanes, high temperatures, and humid/frigid conditions have proven challenging to achieve. Here, we report a porous bulk nanocomposite comprising carbon nanotube (CNT)-reinforced polytetrafluoroethylene (PTFE). The nanocomposites are prepared using a templated approach by infusing a CNT/PTFE dispersion into a sponge followed by thermal annealing and decomposition of the sponge template. Importantly, an excess accretion of CNT/PFFE particle mixture on the sponge resulted in nanocomposites with unique and hierarchical porous microstructure, featuring nanochannels near the surface connected to microscale pores inside. The superhydrophobic nanocomposite could resist liquid jets impacting at a velocity of �85.4 m s1 (Weber number of �202,588) and exhibits excellent high-temperature resistance as well as mechanochemical robustness. The porous nanocomposites display excellent icephobicity both with and without infusion with polydimethylsiloxane/silicone oil. These properties should facilitate exploitation as stiff/strong structural polymeric foams used in a variety of fields

A panther chameleon skin-inspired core@shell supramolecular hydrogel with spatially organized multi-luminogens enables programmable color change

Organization of different iridophores into a core@shell structure constitutes an evolutionary novelty for panther chameleons that allows their skins to display diverse color change. Inspired by this natural color-changing design, we present a responsive core@shell-structured multi-luminogen supramolecular hydrogel system that generates a programmable multi-color fluorescent change. Specifically, red Eu$^{3+}$-amidopicolinate (R) luminogen is incorporated into the core hydrogel, while blue naphthalimide (B) and green perylene-tetracarboxylic acid (G) luminogens are grown into two supramolecular shell hydrogels. The intensities of G/B luminogens could then be controlled independently, which enables its emission color to be programmed easily from red to blue or green, nearly covering the full visible spectrum. Because of the differential excitation energies between these luminogens, a desirable excitation wavelength-dependent fluorescence is also achieved. Colorful materials with a patterned core@shell structure are also demonstrated for anti-counterfeiting, opening up the possibility of utilizing a bioinspired core@shell structure to develop an efficient multi-color fluorescent system with versatile uses

Observation of Dirac hierarchy in three-dimensional acoustic topological insulators

Dirac cones (DCs) play a pivotal role in various unique phenomena ranging from massless electrons in graphene to robust surface states in topological insulators (TIs). Recent studies have theoretically revealed a full Dirac hierarchy comprising an eightfold bulk DC, a fourfold surface DC, and a twofold hinge DC, associated with a hierarchy of topological phases including first-order to third-order three-dimensional (3D) topological insulators, using the same 3D base lattice. Here, we report the first experimental observation of the Dirac hierarchy in 3D acoustic TIs. Using acoustic measurements, we unambiguously reveal that lifting of multifold DCs in each hierarchy can induce two-dimensional (2D) topological surface states with a fourfold DC in a first-order 3D TI, one-dimensional (1D) topological hinge states with a twofold DC in a second-order 3D TI, and zero-dimensional (0D) topological corner states in a third-order 3D TI. Our work not only expands the fundamental research scope of Dirac physics, but also opens up a new route for multidimensional robust wave manipulation

Characterization of Non-heading Mutation in Heading Chinese Cabbage (Brassica rapa L. ssp. pekinensis)

Heading is a key agronomic trait of Chinese cabbage. A non-heading mutant with flat growth of heading leaves (fg-1) was isolated from an EMS-induced mutant population of the heading Chinese cabbage inbred line A03. In fg-1 mutant plants, the heading leaves are flat similar to rosette leaves. The epidermal cells on the adaxial surface of these leaves are significantly smaller, while those on the abaxial surface are much larger than in A03 plants. The segregation of the heading phenotype in the F2 and BC1 population suggests that the mutant trait is controlled by a pair of recessive alleles. Phytohormone analysis at the early heading stage showed significant decreases in IAA, ABA, JA and SA, with increases in methyl IAA and trans-Zeatin levels, suggesting they may coordinate leaf adaxial-abaxial polarity, development and morphology in fg-1. RNA-sequencing analysis at the early heading stage showed a decrease in expression levels of several auxin transport (BrAUX1, BrLAXs, and BrPINs) and responsive genes. Transcript levels of important ABA responsive genes, including BrABF3, were up-regulated in mid-leaf sections suggesting that both auxin and ABA signaling pathways play important roles in regulating leaf heading. In addition, a significant reduction in BrIAMT1 transcripts in fg-1 might contribute to leaf epinastic growth. The expression profiles of 19 genes with known roles in leaf polarity were significantly different in fg-1 leaves compared to wild type, suggesting that these genes might also regulate leaf heading in Chinese cabbage. In conclusion, leaf heading in Chinese cabbage is controlled through a complex network of hormone signaling and abaxial-adaxial patterning pathways. These findings increase our understanding of the molecular basis of head formation in Chinese cabbage

Application of nonparametric discriminant analysis for assessing food safety issues of Caribbean imports

Caribbean food imports often face detentions and refusals by the US resulting in a major loss of income. In this paper, we consider a classification procedure based on transvariation probabilities to correctly identify cases that lead to food detention. This is based upon several background variables on fourteen Latin American and Caribbean countries. A method for selecting variables according to their contribution towards predicting detention is given. For our particular sample, the selection method chose foreign direct investment as the variable that carried the most information in determining food detention. After removing variables that were non-informative about food detention status, a leave-one-out cross-validation shows that methods based on transvariation probabilities were superior to classical methods in predicting food detention

Proceedings of the 28th West Indies Agricultural Economics Conference

Caribbean food imports often face detentions and refusals by the US resulting in a major loss of income. In this paper, we consider a classification procedure based on transvariation probabilities to correctly identify cases that lead to food detention. This is based upon several background variables on fourteen Latin American and Caribbean countries. A method for selecting variables according to their contribution towards predicting detention is given. For our particular sample, the selection method chose foreign direct investment as the variable that carried the most information in determining food detention. After removing variables that were non-informative about food detention status, a leave-one-out cross-validation shows that methods based on transvariation probabilities were superior to classical methods in predicting food detention

Bacillus sp. QSI-1 modulate quorum sensing signals reduce Aeromonas hydrophila level and alter gut microbial community structure in fish

Quorum sensing (QS) is a cell density dependent process that enables bacteria to communicate with each other based on the production, secretion and sensing of the auto-inducer molecules and then subsequently regulate virulence associated gene expression. Interrupting quorum sensing may represent a novel alternative approach to combat bacterial pathogen. Several bacteria can produce quorum quenching (QQ) enzymes. However, the role of QQ bacteria in shaping the microbiota and the level of N-acyl-homoserine lactones (AHLs, a prevalent type of QS molecules) producing bacteria remains largely unknown. The objective of this study was to examine the presence of AHLs in the fish intestine and investigate the modulation of gut microbiota and its effect on Aeromonas hydrophila level by a QQ enzyme producing probiotic Bacillus sp.QSI-1. AHLs were found in fish gut content and were confirmed in Aeromonas species using Chromobacterium violaceum CV026 and Agrobacterium tumefaciens AT 136 (pZLR4) as reporter strains. We demonstrated that the composition of fish gut microbiota was affected by quenching bacteria QSI-1, and the percentage of A. hydrophila was decreased significantly. Taken together, these results provide valuable insights into QQ enzyme producing probiotics can modulate the microbiota structure and decrease the percentage of AHL-producing pathogenic bacteria in the gut. These data strongly suggest that QQ probiotics may serve as non-antibiotic feed additive in aquaculture to control bacterial diseases

GCN-Transformer for short-term passenger flow prediction on holidays in urban rail transit systems

The short-term passenger flow prediction of the urban rail transit system is of great significance for traffic operation and management. The emerging deep learning-based models provide effective methods to improve prediction accuracy. However, most of the existing models mainly predict the passenger flow on general weekdays, while few studies focus on predicting the holiday passenger flow, which can provide more significant information for operators because congestions or accidents generally occur on holidays. To this end, we propose a deep learning-based model named GCN-Transformer comprising graph conventional neural network (GCN) and Transformer for short-term passenger flow prediction on holidays. The GCN is applied to extract the spatial features of passenger flows and the Transformer is applied to extract the temporal features of passenger flows. Moreover, in addition to the historical passenger flow data, social media data are also incorporated into the prediction model, which has been proven to have a potential correlation with the fluctuation of passenger flow. The GCN-Transformer is tested on two large-scale real-world datasets from Nanning, China during the New Year holiday and is compared with several conventional prediction models. Results demonstrate its better robustness and advantages among baseline methods, which provides overwhelming support for practical applications of short-term passenger flow prediction on holidaysComment: 26 pages, 10 figures, 5 table

Patterned-Liquid-Crystal for Novel Displays

The “Patterned-Liquid-Crystal for Novel Displays” is a Special Issue focused on new insights and explorations in the field of liquid crystals arranged in a periodic patterned way [...