The silver nanoparticles (AgNPs) exhibit unique and tunable plasmonic properties. The size and shape of these particles can manipulate their localized surface plasmon resonance (LSPR) property and their response to the local environment. The LSPR property of nanoparticles is exploited by their optical, chemical, and biological sensing. This is an interdisciplinary area that involves chemistry, biology, and materials science. In this paper, a polymer system is used with the optimization technique of blending two polymers. The two polymer composites polystyrene/poly (4-vinylpyridine) (PS/P4VP) (50:50) and (75:25) were used as found suitable by their previous morphological studies. The results of 50, 95, and 50, 150 nm thicknesses of silver nanoparticles deposited on PS/P4VP (50:50) and (75:25) were explored to observe their optical sensitivity. The nature of the polymer composite embedded with silver nanoparticles affects the size of the nanoparticle and its distribution in the matrix. The polymer composites used are found to have a uniform distribution of nanoparticles of various sizes. The optical properties of Ag nanoparticles embedded in suitable polymer composites for the development of the latest plasmonic applications, owing to their unique properties, were explored. The sensing capability of a particular polymer composite is found to depend on the size of the nanoparticle embedded in it. The optimum result has been found for silver nanoparticles of 150 nm thickness deposited on PS/P4VP (75:25).

Metamaterial perfect absorber is very important in the study of refractive index sensor. The time domain finite difference method is used to simulate the surface plasmon structure. The double nanorod periodic structure is designed, and the parameters of the top layer structure are optimized according to the impedance matching principle, and the absorption rate of the structure to the light wave reaches 99.6% when the wavelength is about 12 mm. The absorption spectroscopy of the structure is studied with the change of the refractive index of the spatial medium around the structure, and the sensitivity of the double nanorod structure is 4,008 nm/RIU, which can be used to measure the refractive index of the gas.

Rambutan (Nephelium lappaceum L.) was introduced to Mexico in 1959. Currently there is an estimated planted area of 835.96 ha and a production of 8,730.27 tons. The fruit is mainly consumed fresh, but quickly loses its external appearance due to dehydration and browning, which limits its commercialization, an alternative may be minimal processing and adjuvant treatments that extend the shelf life. The objective of this work was to evaluate the effect of coating with cactus mucilage (Opuntia ficus-indica), in the preservation of minimally processed rambutan stored at 5 °C, in two types of packaging. The rambutan was sanitized with chlorinated water (80 ppm), the epicarp was removed and batches were formed for each treatment. The factors were type of container (polyethylene bag and polystyrene container), coating (with and without coating) and time (0, 3, 6, 6, 10 and 12 d). The coating consisted of mucilage obtained from developing cladodes (15–21 cm), applied by dipping. All treatments were stored at 5 ℃. Total soluble solids (TSS), firmness (N) and color (L*, a*, b*, chroma and hue angle) were evaluated at each storage period. Also, 40 untrained judges (47% male and 53% female) evaluated sensory acceptability, consumption intention and acceptance/rejection. The results showed significant effect (p ≤ 0.05) of package type on firmness, chroma and hue angle. Coating had an effect on L* value and product acceptability. Consumption intention was higher, and was maintained for 10 days, in fruits with coating and packaged in polyethylene bags, stored at 5 ℃.

Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.

Metal organic framework is a class of hybrid network of supramolecular solid materials comprised of a large number of inorganic and organic linkers all bounded to metal ions in a well-organized fashion. This type of compounds possess a greater surface area with an advantage of changing pore sizes, diversified and beautiful structure which withdrew an intense interest in this field. In the present review articles, the structural aspects, classification, methods of synthesis, various factors affecting the synthesis and stability, properties and applications have been discussed. Recent advances in the field and new directions to explore the future scope and applications of MOFs have been incorporated in this article to provide current status of the field.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.