A tunable plasmonic refractive index sensor with nanoring-strip graphene arrays

In this paper, a tunable plasmonic refractive index sensor with nanoring-strip graphene arrays is numerically investigated by the finite difference time domain (FDTD) method. The simulation results exhibit that by changing the sensing medium refractive index nmed of the structure, the sensing range of the system is large. By changing the doping level ng, we noticed that the transmission characteristics can be adjusted flexibly. The resonance wavelength remains entirely the same and the transmission dip enhancement over a big range of incidence angles [0,45] for both TM and TE polarizations, which indicates that the resonance of the graphene nanoring-strip arrays is insensitive to angle polarization. The above results are undoubtedly a new way to realize various tunable plasmon devices, and may have a great application prospect in biosensing, detection and imaging

Heavy Metals Migration in Soil in Tailing Dam Region of Shuikoushan, Hunan Province, China

AbstractThe nonferrous mining industry in China has been exploiting rich domestic mineral resources in order to sustain rapidly economic and social development. The paper chooses the tailing dam region as the research object in the Shuikoushan, and researches the distribution of Pb, Zn, Cu, Cd, As, Cr, which reveals heavy metal migration regularities in layers from new and old tailing dam region. In addition, this article focuses on making the research of Potential Ecological Risk Index appraisal to the heavy metal contamination level. The results showed that the concentrations of heavy metals in old tailing dam region were much higher than those of in the new tailing dam region. As well, the concentrations of most heavy metal reduced progressively with the soil depth increasing for the new tailing dam region, while the change tendency was inversely for the old one. Potential ecological risk index showed that the potential ecological risks were at low and low to moderate level in tailing dam region

An eco-friendly way to fire retardant flexible polyurethane foam: layer-by-layer assembly of fully bio-based substances

The objective of the present study is to develop fully renewable and environmentally benign techniques for improving the fire safety of flexible polyurethane foams (PUFs). A multilayered coating made from cationic chitosan (CS) and anionic alginate (AL) was deposited on PUFs through layer-by-layer assembly. This coating system exhibits a slight influence on the thermal stability of PUF, but significantly improves the char formation during combustion. Cone calorimetry reveals that 10 CS-AL bilayers (only 5.7% of the foams weight) lead to a 66% and 11% reduction in peak heat release rate and total heat release, respectively, compared with those of the uncoated control. The notable decreased fire hazards of PUF are attributed to the CS-AL coatings being beneficial to form an insulating protective layer on the surface of burning materials that inhibits the oxygen and heat permeation and slows down the flammable gases in the vapor phase, and thereby improves the flame resistance. This water-based, environmentally benign natural coating will stimulate further efforts in improving fire safety for a variety of polymer substrates

Brain-inspired Graph Spiking Neural Networks for Commonsense Knowledge Representation and Reasoning

How neural networks in the human brain represent commonsense knowledge, and complete related reasoning tasks is an important research topic in neuroscience, cognitive science, psychology, and artificial intelligence. Although the traditional artificial neural network using fixed-length vectors to represent symbols has gained good performance in some specific tasks, it is still a black box that lacks interpretability, far from how humans perceive the world. Inspired by the grandmother-cell hypothesis in neuroscience, this work investigates how population encoding and spiking timing-dependent plasticity (STDP) mechanisms can be integrated into the learning of spiking neural networks, and how a population of neurons can represent a symbol via guiding the completion of sequential firing between different neuron populations. The neuron populations of different communities together constitute the entire commonsense knowledge graph, forming a giant graph spiking neural network. Moreover, we introduced the Reward-modulated spiking timing-dependent plasticity (R-STDP) mechanism to simulate the biological reinforcement learning process and completed the related reasoning tasks accordingly, achieving comparable accuracy and faster convergence speed than the graph convolutional artificial neural networks. For the fields of neuroscience and cognitive science, the work in this paper provided the foundation of computational modeling for further exploration of the way the human brain represents commonsense knowledge. For the field of artificial intelligence, this paper indicated the exploration direction for realizing a more robust and interpretable neural network by constructing a commonsense knowledge representation and reasoning spiking neural networks with solid biological plausibility

Resistance-gene-directed discovery of a natural-product herbicide with a new mode of action.

Bioactive natural products have evolved to inhibit specific cellular targets and have served as lead molecules for health and agricultural applications for the past century1-3. The post-genomics era has brought a renaissance in the discovery of natural products using synthetic-biology tools4-6. However, compared to traditional bioactivity-guided approaches, genome mining of natural products with specific and potent biological activities remains challenging4. Here we present the discovery and validation of a potent herbicide that targets a critical metabolic enzyme that is required for plant survival. Our approach is based on the co-clustering of a self-resistance gene in the natural-product biosynthesis gene cluster7-9, which provides insight into the potential biological activity of the encoded compound. We targeted dihydroxy-acid dehydratase in the branched-chain amino acid biosynthetic pathway in plants; the last step in this pathway is often targeted for herbicide development10. We show that the fungal sesquiterpenoid aspterric acid, which was discovered using the method described above, is a sub-micromolar inhibitor of dihydroxy-acid dehydratase that is effective as a herbicide in spray applications. The self-resistance gene astD was validated to be insensitive to aspterric acid and was deployed as a transgene in the establishment of plants that are resistant to aspterric acid. This herbicide-resistance gene combination complements the urgent ongoing efforts to overcome weed resistance11. Our discovery demonstrates the potential of using a resistance-gene-directed approach in the discovery of bioactive natural products

Human Mitochondrial tRNA Mutations in Maternally Inherited Deafness

AbstractMutations in mitochondrial tRNA genes have been shown to be associated with maternally inherited syndromic and non-syndromic deafness. Among those, mutations such as tRNALeu(UUR)3243A>G associated with syndromic deafness are often present in heteroplasmy, and the non-syndromic deafness-associated tRNA mutations including tRNASer(UCN)7445A>G are often in homoplasmy or in high levels of heteroplasmy. These tRNA mutations are the primary factors underlying the development of hearing loss. However, other tRNA mutations such as tRNAThr15927G>A and tRNASer(UCN)7444G>A are insufficient to produce a deafness phenotype, but always act in synergy with the primary mitochondrial DNA mutations, and can modulate their phenotypic manifestation. These tRNA mutations may alter the structure and function of the corresponding mitochondrial tRNAs and cause failures in tRNAs metabolism. Thereby, the impairment of mitochondrial protein synthesis and subsequent defects in respiration caused by these tRNA mutations, results in mitochondrial dysfunctions and eventually leads to the development of hearing loss. Here, we summarized the deafness-associated mitochondrial tRNA mutations and discussed the pathophysiology of these mitochondrial tRNA mutations, and we hope these data will provide a foundation for the early diagnosis, management, and treatment of maternally inherited deafness