Attempts were made in the present study to design and develop skeletally modified ether linked tetraglycidyl epoxy resin (TGBAPSB), which is subsequently reinforced with different weight percentages of amine functionalized mullite fiber (F-MF). The F-MF was synthesized by reacting mullite fiber with 3-aminopropyltriethoxysilane (APTES) as coupling agent and the F-MF structure was confirmed by FT-IR. TGBAPSB reinforced with F-MF formulation was cured with 4,4’-diamino diphenyl methane (DDM) to obtain nanocomposite. The surface morphology of TGBAPSB-F-MF epoxy nanocomposites was investigated by XRD, SEM and AFM studies. From the study, it follows that these nanocomposite materials offer enhancement in mechanical, thermal, thermo-mechanical, dielectric properties compared to neat (TGBAPSB) epoxy matrix. Hence we recommend these nanocomposites for a possible use in advanced engineering applications that require both toughness and stiffness.

Control of key technological and benchmark flows of polymer fluids poses a number of challenges. Some of them are nowadays under active investigation and rather far from complete under­stan­ding. This review considers such phenomena as both practically important and governed by funda­mental laws of rheology and non-linear fluid mechanics. We observe, shear bands in polymeric and other complex structured fluids (like wormlike micellar solutions or soft glassy materials), birefrigerent strands, peculiarities of stress and pressure losses in fluids moving through com­plex shape domains. These and other processes involve in­ho­mo­geneity, in­stabilities and tran­sient modes creeping in flow fields. In practical aspect this is of interest in such industrial process as polymer flooding for Enhanced Oil Recovery (EOR), where a flow inhomogeneity affects a poly­mer solution injectivity and residual oil saturation. The value of viscoelasticity in the polymer flooding is estimated. The obser­va­tion is con­clu­ded by some new results on relation between polymer concentration in solutions and viscoelastic traits of benchmark flows.

To analyze the effect of an increase in the quantity or quality of public investment on growth, this paper extends the World Bank’s Long-Term Growth Model (LTGM), by separating the total capital stock into public and private portions, with the former adjusted for its quality. The paper presents the LTGM public capital extension and accompanying freely downloadable Excel-based tool. It also constructs a new infrastructure efficiency index, by combining quality indicators for power, roads, and water as a cardinal measure of the quality of public capital in each country. In the model, public investment generates a larger boost to growth if existing stocks of public capital are low, or if public capital is particularly important in the production function. Through the lens of the model and utilizing newly-collated cross-country data, the paper presents three stylized facts and some related policy implications. First, the measured public capital stock is roughly constant as a share of gross domestic product (GDP) across income groups, which implies that the returns to new public investment, and its effect on growth, are roughly constant across development levels. Second, developing countries are relatively short of private capital, which means that private investment provides the largest boost to growth in low-income countries. Third, low-income countries have the lowest quality of public capital and the lowest efficient public capital stock as a share of GDP. Although this does not affect the returns to public investment, it means that improving the efficiency of public investment has a sizable effect on growth in low-income countries. Quantitatively, a permanent 1 ppt GDP increase in public investment boosts growth by around 0.1–0.2 ppts over the following few years (depending on the parameters), with the effect declining over time.

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.

Fire is one of the most serious hazards, which causes many economic, social, ecological, and human damages every year in the world. Fire in forests and natural ecosystems destroys wood, regeneration, forest vegetation, as well as soil erosion and forest regeneration problems (due to the dryness of the weather and the weakness of the soil). Awareness of the extent of the zones that have been fired is important for forest management. On the other hand, the difficulty of fieldwork due to the high cost and inaccessible roads, etc. reveals the need for using remote sensing science to solve this problem. In this research, MODIS satellite images were used to detect and determine the fire extent of Golestan province forests in northern Iran. MID13q1 and MOD13q1 images were used to detect the normal conditions of the environment. The 15-year time series data were provided for the NDVI and NDMI indicators in 2000-2015. Then, the behavior of indicators in the fire zone was studied on the day after the fire. The burned zones by the fire were specified by determining the appropriate threshold and then, they were compared to long-term normals. In the NDMI and NDVI indicators, the mean of the numeric value threshold limit for determining the burnt pixels was respectively 1.865 and 0.743 of the reduction in their normal long-term period, which are selected as fire pixels. The results showed that the NDMI index could determine the extent of the burned zone with the accuracy of 95.15%.