Superhydrophobic Plant Leaves with Micro-line Structures： An Optimal Biomimetic Objective in Bionic Engineering

It has been well demonstrated that there are two kinds of surface morphologies, including binary structures （namely micro-and nanostructures） and less common unitary structures （such as micro-line structures）, which play crucial roles in endowing the plant leaves with superhydrophobic properties. In this work, five superhydrophobic plant leaves in nature are introduced, by means of the combination of surface morphology and wettability with the aid of Scanning Electron Microscopy （SEM） and contact angle measurement. The results indicate that either the binary structures or the unitary structures enable the construction of a superhydrophobic surface, and the latter shows likely better mechanics compared with the former according to the corresponding theory. This research aims at introducing two different types of corresponding morphologies of superhydrophobic plant leaves.

Application of Nuclear Analysis in Assessment of Environmental Pollution Part 1 Contamination of Plant and Soilby Fluorine

Fluorine contaminates the environment. The study of fluorine contamination profile can be made easy by the use of nuclear analytic method. Measurement of prompt gamma emitted from bombarding fluorine polluted environmental sample with proton beam from accelerator provides rapid assessment of fluorine contamination. In this paper, 340 keV proton beam induced F 19 (P,αγ) O 16 reaction is performed, measurement of prompt gamma 6130 keV gives fluorine content in the soil and leaves of plants (parasol, cotton and glossy privet), taken from the fluorine polluted area.

Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM Approaches

The Fused Modified Grasshopper Optimization Algorithm has been proposed,which selects the most specific feature sets from images of the disease of plant leaves.The Proposed algorithm ensures the detection of diseases during the early stages of the diagnosis of leaf disease by farmers and,finally,the crop needed to be controlled by farmers to ensure the survival and protection of plants.In this study,a novel approach has been suggested based on the standard optimization algorithm for grasshopper and the selection of features.Leaf conditions in plants are a major factor in reducing crop yield and quality.Any delay or errors in the diagnosis of the disease can lead to delays in the management of plant disease spreading and damage and related material losses.Comparative new heuristic optimization of swarm intelligence,Grasshopper Optimization Algorithm was inspired by grasshopper movements for their feeding strategy.It simulates the attitude and social interaction of grasshopper swarm in terms of gravity and wind advection.In the decision on features extracted by an accelerated feature selection algorithm,popular approaches such as ANN and SVM classifiers had been used.For the evaluation of the proposed model,different data sets of plant leaves were used.The proposed model was successful in the diagnosis of the diseases of leaves the plant with an accuracy of 99.41 percent(average).The proposed biologically inspired model was sufficiently satisfied,and the best or most desirable characteristics were established.Finally,the results of the research for these data sets were estimated by the proposed Fused Modified Grasshopper Optimization Algorithm(FMGOA).The results of that experiment were demonstrated to allow classification models to reduce input features and thus to increase the precision with the presented Modified Grasshopper Optimization Algorithm.Measurement and analysis were performed to prove the model validity through model parameters such as precision,recall,f-measure,and precision.

Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling

Current understanding about how the virus that causes COVID-19 spreads is largely based on what is known about similar coronaviruses.Some of the Natural products are suitable drugs against SARS-CoV-2 main protease.For recognizing a strong inhibitor,we have accomplished dock-ing studies on the major virus protease with 4 natural product species as anti COVID-19(SARS-CoV-2),namely“Vidarabine”,“Cytarabine”,“Gem-citabine”and“Matrine”which have been extracted fromGillan’s leaves plants.These are known as Chuchaq,Trshvash,Cote-Couto and Khlvash in Iran.Among these four studied compounds,Cytarabine appears as a suitable com-pound with high effectiveness inhibitors to this protease.Finally by this work we present a method on the Computational Prediction of Protein Structure Associated with COVID-19 Based Ligand Design and Molecular Modeling.By this investigation,auto dock software(iGEM-DOCK)has been used and via this tool,the suitable receptors can be distinguished in whole COVID-19 component structures for forming a complex.“iGEMDOCK”is suitable to define the binding site quickly.With docking simulation and NMR inves-tigation,we have demonstrated these compounds exhibit a suitable binding energy around 9 Kcal/mol with various ligand proteins modes in the bind-ing to COVID-19 viruses.However,these data need further evaluation for repurposing these drugs against COVID-19 viruses,in both vivo&vitro.

Concentration-and flux-based dose-responses of isoprene emission from poplar leaves and plants exposed to an ozone concentration gradient

Supported by the National Key Research and Development Program of China,Key Research Program of Frontier Sciences,CAS,the Hundred Talents Program,Chinese Academy of Sciences(CAS),and National Natural Science Foundation of China,a cooperative study by the research groups led by Prof.

Interfacial Effects of Superhydrophobic Plant Surfaces： A Review

Nature is a huge gallery of art involving nearly perfect structures and properties over the millions of years of development. Many plants and animals show water-repellent properties with fine micro-structures, such as lotus leaf, water skipper and wings of butterfly. Inspired by these special surfaces, the artificial superhydrophobic surfaces have attracted wide attention in both basic research and industrial applications. The wetting properties of superhydrophobic surfaces in nature are affected by the chemical compositions and the surface topographies. So it is possible to realize the biomimetic superhydrophobic surfaces by tuning their surface roughness and surface free energy correspondingly. This review briefly introduces the physical-chemical basis of superhydrophobic plant surfaces in nature to explain how the superhydrophobicity of plant surfaces can be applied to different biomimetic functional materials with relevance to technological applications. Then, three classical effects of natural surfaces are classified： lotus effect, salvinia effect, and petal effect, and the promising strategies to fabricate biomimetic su- perhydrophobic materials are highlighted. Finally, the prospects and challenges of this area in the future are proposed.

The aliphatic hydrocarbon distributions of terrestrial plants around an alpine lake： a pilot study from Lake Ximencuo, Eastern Qinghai-Tibet Plateau

As part of an investigation of the sources of aliphatic hydrocarbons to the sediments of alpine Lake Ximencuo, leaves of the eight dominant vascular plants were collected and their hydrocarbon contents were analyzed. A series of unsaturated aliphatic hydrocarbons were identified in the plant leaves; in particular, Festuca sp. contain a series of n-alkadienes that have rarely been reported in previous studies. The comparison of n-alkane proxies （ACL27 33, ACLT, Paq, and CPI） and δ13Corg among plant leaves, surface soils, and lake sediments suggests that organic proxies have been altered to varying degrees during the transport and burial process of organic materials. It is believed that microbial reworking and source changes have great impacts on organic proxies in the alpine lake system. In addition, the cluster analysis for plant leaves depending on n-alkane compositions and the ACLT proxy generates similar results. Accordingly, we postulate that the average chain length of plant waxes might be a potential indicator of plant classification in regions such as the Qinghai-Tibet Plateau.

Green Plant Leaf-inspired Smart Camouflage Fabrics for Visible Light and Near-infrared Stealth

Due to Visible light and Near-Infrared(Vis–NIR)stealth play an important role in the commercial,military,and scientific fields,camouflage materials related to it attracted increasing attention in decades.Green plant leaves,as the most extensive background materials on the earth,were widely simulated in the camouflage materials.However,difficult full-spectrum simulation(380–2500 nm),low-similarity simulation and the complex preparation have been great challenges for Vis–NIR Camouflage Materials(Vis–NIR-CMs).Herein,basing on the color-matching principle,two novel Vis–NIR-CMs including Dark Green Materials and Light Green Materials(DGM and LGM)were facilely fabricated by simple printing organic disperse dyes including C.I.Disperse Blue 291,C.I.Disperse Yellow 114,and C.I.Disperse Orange 30(B-291,Y-114 and O-30),and titanium dioxide(TiO_(2))on the viscose fabrics.Based on the excellent red edge property of B-291 and high scattering ability of TiO2,DGM and LGM exhibited generally high spectral correlation coefficients r_(m)(>0.95)with green plant leaves.Moreover,with the great color performance,excellent objects covering performance,low areal density(<146.3 g cm^(−2)),high tensile strength(>7.7 MPa),high softness(>81.27),high air permeability(>45.848 mm s^(−1)),DGM and LGM showed good simulation performance and wearing comfort to satisfy the application needs.This work presents a high-similarity Vis–NIR-CMs as a reference for full-spectrum camouflage materials,as well as low-cost and efficient preparation method is beneficial to the development of camouflage field.

Adsorption characteristics of droplets applied on non-smooth leaf surface of typical crops

To further understand the adsorption characteristics of different-type leaf surfaces adsorbing pesticide droplets and reveal the adsorption mechanism of pesticide droplets on non-smooth leaves,non-smooth leaves of 12 kinds of typical target plants were investigated in this study.The parameters of surface morphological characteristics were measured,which include contact angle between leaves and water droplets,water holding capacity surface tension,polar component,dispersion component and other quantitative range of indicators and variation by modern means.The relationships between the indicators and water holding capacity were investigated respectively.The experimental results show that the number of trichomes,epidermal wax,morphology and distribution characteristics have influences on adsorption characteristics of the water droplets.There is a negative correlation between free energy of obverse side and the water holding capacity(R=−0.447)while the free energy of reverse side and the water holding capacity show a positive correlation(R=0.212).Also,there is a negative correlation between polar component of obverse side and the water holding capacity(R=−0.357)while the polar component of reverse side and the water holding capacity in plant leaves show a positive correlation(R=0.149).The research can provide a scientific theory for reasonable spraying of pesticide in the agricultural production,and can be a reference for the development of pesticide adjuvants and bionic pesticides.

An application of blended amendments in monsoon rice field

Introduction:Rice is the main food crop of the world,and the cultivation of rice crop during the monsoon season is hard due to the rain-induced waterlogging.Apart from this,farmers in north-eastern regions of India often implement improper crop management leading to poor yields.Thus,the development of suitable management practices under improved varieties of rice become essential for increasing rice productivity,improving soil quality status and reducing methane emission.Methods:The aim of the study was to investigate the variation in soil properties,crop growth and methane emission under the application of an inorganic fertiliser as well as its mixtures with both inorganic and plant materials.In such an attempt,a field-based experiment was conducted with the rice variety Chandrama during 2015 in slightly acidic soil having sandy loam texture.Five amendments,i.e.NPK and NPK,blended separately with magnesium sulphate,fresh neem(Azadirechta indica)leaves,used tea(Camellia sinensis var.assamica)leaves,and fresh karanj(Pongamia glabra)leaves were used for the study with four replications each.Results:Application of NPK separately with the leaves of neem,tea and karanj separately at the onset of monsoon season markedly affected the soil porosity and the water-holding capacity of the soil.However,in comparison with sole NPK fertilisation,a significance increase in soil organic matter accumulation(2.48±0.10%)was seen only for karanjblended NPK while magnesium sulphate-blended NPK showed the lowest methane emission(0.30±0.01 mg/m2/h).The rice plants grown on karanj-blended NPK soil showed the highest yield(0.560±0.01 kg/m2)among the five amendments.Conclusions:It was found that only the karanj leaves blended NPK could significantly improve the soil organic matter and increase rice yield without intensifying methane emission,while magnesium sulphate blended with NPK could significantly reduce methane emission in the flooded rice paddy soil at 0.5 t/ha application level but exhibit lower rice yield.