NANOSCALE DEVICES CONSISTING OF HETEROSTRUCTURES OF CARBON NANOTUBES AND TWO-DIMENSIONAL LAYERED MATERIALS

One dimensional carbon nanotubes (CNTs) and two-dimensional layered materials like graphene, MoS2, hexagonal boron nitride (hBN), etc. with different electrical and mechanical properties are great candidates for many applications in the future. In this study the synthesis and growth of carbon nanotubes on both conducting graphene and graphite substrates as well as insulating hBN substrate with precise crystallographic orientation is achieved. We show that the nanotubes have a clear preference to align to specific crystal directions of the underlying graphene or hBN substrate. On thicker flakes of graphite, the edges of these 2D materials can control the orientation of these carbon nanotubes. This integrated aligned growth of materials with similar lattices provides a promising route to achieving intricate nanoscale electrical circuits. Furthermore, short channel nanoscale devices consisting of the heterostructure of 1D and 2D materials are fabricated. In these nanoscale devices the nanogap is created due to etching of few layer graphene flake through hydrogenation and the channel is either carbon nanotubes or 2D materials like graphene and MoS2. Finally the transport properties of these nanoscale devices is studied

Biodegradation of polycyclic aromatic hydrocarbons (PAHs) in petroleum contaminated soils

Polycyclic aromatic hydrocarbons are a class of potentially hazardous chemicals of environmental and health concern. PAHs are one of the most prevalent groups of contaminants found in soil. Biodegradation of complex hydrocarbon usually requires the cooperation of more than single specie. In this research biotreatment of PAH (phenanthrene) was studied in a solidphase reactor using indigenous bacteria isolated from two petroleum contaminated sites in Iran, (i.e., Tehran refinery site with clayey-sand soil composition and Bushehr oil zone with silty-sand soil composotion). Phenanthrene (C14H10) was made in three rates (100, 500, and 1000 mg/kg of soil) synthetically and was conducted with two bacterial mixed cultures for a period of 20 weeks. Highest removal (more than 85 ) of phenanthrene with rates of 100, 500 and 1000 mg/kg in clayey-sand soil with BMTRS (Bacterial Mix of Tehran Refinery Site) consortium was achieved within 3, 5 and 14 weeks, respectively as for silty-sand soil composition with BMBOZ (Bacterial Mix of Bushehr Oil Zone) consortium was achieved within 10, 17, and 19 weeks, respectively. Results for phenanthrene biotreatment in solid phase reactor revealed a significance relationship between concentration and type of microbial consortium with the removal efficiency of phenanthrene over the time (P value<0.001). Furthermore, there was a significant relationship between soil type with removal efficiency of phenanthrene over the time (P value=0.022). That means the bioremediation of the lower concentrations of phenanthrene needs shorter time compared with the higher concentrations. Microbial analysis using confirmative series tests and analytical profile index (API) kit tests showed the Pseudomonas fluorescence, Serratia liquefaciens, Bacillus and Micrococcus strains as dominant bacteria in the mixed cultures

Droughts and the Impacts of Dry Spells in North of Iraq

Different sets of dry spell length such as complete series, monthly maximum, seasonal maximum, and annual maximum are applied and modeled with different probability distribution functions (such as Gumbel Max, generalized extreme value, Log-Logistic, generalized logistic, inverse Gaussian, Log-Pearson 3, generalized Pareto) to recognize in which duration, dry spells cause drought. The drought situation and temporal analysis in the North of Iraq region were done using the SPI index and by software of DrinC at a time scale of 3.6 and 12 months. Because of applicability, availability of data and the aim of the study, SPI is selected to analyze the dry spells in this study. Based on the maximum length of the available statistical period, the statistics for the years 1980 to 2019 were used from nine meteorological stations for analysis. The results of the study showed the severity of drought during the study period which related to dry spells. The results of this research confirm the variation of drought occurrence with varying degrees in different time and different dry spells condition in Iraq

Graphene Used as a Lateral Force Microscopy Calibration Material in the Low-Load Non-Linear Regime

A lateral force microscopy (LFM) calibration technique utilizing a random low-profile surface is proposed that is successfully employed in the low-load non-linear frictional regime using a single layer of graphene on a supporting oxide substrate. This calibration at low loads and on low friction surfaces like graphene has the benefit of helping to limit the wear of the LFM tip during the calibration procedure. Moreover, the low-profiles of the calibration surface characteristic of these layered 2D materials, on standard polished oxide substrates, result in a nearly constant frictional, adhesive, and elastic response as the tip slides over the surface, making the determination of the calibration coefficient robust. Through a detailed calibration analysis that takes into account non-linear frictional response, it is found that the adhesion is best described by a nearly constant vertical orientation, rather than the more commonly encountered normally directed adhesion, as the single asperity passes over the low-profile graphene-coated oxide surface

Incisional hernia following colorectal cancer surgery according to suture technique: Hughes Abdominal Repair Randomized Trial (HART).

BACKGROUND: Incisional hernias cause morbidity and may require further surgery. HART (Hughes Abdominal Repair Trial) assessed the effect of an alternative suture method on the incidence of incisional hernia following colorectal cancer surgery. METHODS: A pragmatic multicentre single-blind RCT allocated patients undergoing midline incision for colorectal cancer to either Hughes closure (double far-near-near-far sutures of 1 nylon suture at 2-cm intervals along the fascia combined with conventional mass closure) or the surgeon's standard closure. The primary outcome was the incidence of incisional hernia at 1 year assessed by clinical examination. An intention-to-treat analysis was performed. RESULTS: Between August 2014 and February 2018, 802 patients were randomized to either Hughes closure (401) or the standard mass closure group (401). At 1 year after surgery, 672 patients (83.7 per cent) were included in the primary outcome analysis; 50 of 339 patients (14.8 per cent) in the Hughes group and 57 of 333 (17.1 per cent) in the standard closure group had incisional hernia (OR 0.84, 95 per cent c.i. 0.55 to 1.27; P = 0.402). At 2 years, 78 patients (28.7 per cent) in the Hughes repair group and 84 (31.8 per cent) in the standard closure group had incisional hernia (OR 0.86, 0.59 to 1.25; P = 0.429). Adverse events were similar in the two groups, apart from the rate of surgical-site infection, which was higher in the Hughes group (13.2 versus 7.7 per cent; OR 1.82, 1.14 to 2.91; P = 0.011). CONCLUSION: The incidence of incisional hernia after colorectal cancer surgery is high. There was no statistical difference in incidence between Hughes closure and mass closure at 1 or 2 years. REGISTRATION NUMBER: ISRCTN25616490 (http://www.controlled-trials.com)

Mid-term Prediction of Meteorological Drought Using Fuzzy Inference Systems

Forecasting and monitoring droughts are important elements of optimum water resources management specifically in the metropolitan areas. Tehranas the biggest city of Iranand its five dams (Amirkabir, Lar, Latyan, Mamloo and Taleghan) are also exposed to drought hazards. In the current article, monthly meteorological data in the geographic area covering [0˚, 60˚] Northern latitudes and [0˚, 90˚] Eastern longitudes with 10×10 degree resolution including air temperature and geopotential height at 1000, 850, 700, 500 and 300 mbar levels are used as the model predictors. These data recorded in the period of 1948 to 2008 have been used to develop a model for forecasting SPI (Standardized Precipitation Index) values in Winter and Winter-Spring seasons with 2.5 and 4.5 months leadtime. This model has been calibrated using 31 years of data. Mutual Information (MI) index has been used to select the inputs (predictors) for each basin in each season. Fuzzy Inference System (FIS) has been used to formulate the model. The fuzzy membership functions have been selected based on sensitivity analysis and engineering judgment. The results of the study have shown that geopotential height in 850 and 300 mbar levels are the best predictors for forecasting SPI values in the selected seasons. The model results have had enough accuracy to be used for forecasting SPI values in Winter and Spring seasons inKaraj and Taleghan basins and SPI values in the Winter season in Mamloo, Latyan, and Lar basins

Assessing the economic effects of drought using Positive Mathematical Planning model under climate change scenarios

In recent decades, regions all around the world have experienced severe droughts adversely affecting their agricultural production. Climate change, along with limited access to water will alter future production and agricultural development. The purpose of this study is to provide a perspective for the future cultivation regime in the Divandarre region in the Sepidrood catchment in Iran, using historical climatic, agricultural, and economic information. Future precipitation values are determined for three climate scenarios, then downscaled and converted to pixel-based precipitation maps using the Moving Least Squares method. Future droughts are identified using the Standardized Precipitation Index at 3, 6, and 9-month intervals based on precipitation values and the relationship between different types of droughts (meteorological, agricultural and hydrological). We introduce a new coefficient, the water cost coefficient, derived from drought characteristics that captures the added irrigation cost in drought years because of increased water price. Using the Positive Mathematical Planning method and considering limited land and water, predicted future prices and costs based on a linear regression of supply-demand, and the annual water cost coefficient values, an agroeconomic model is built. After prediction of future price and cost based on historical data from 2005 to 2018, we run future scenarios based on various price and cost values to determine the optimal annual cultivation area for each crop from 2020 to 2040. All scenarios indicate a decline in cultivation area for all crops making agriculture less beneficial in the future. The cultivation regime moves away from more water-consuming products with less economic value (e.g. watermelon) toward less water-consuming, more expensive products (e.g. lentils). The findings of this model along with expert economic judgments help determine the economic effects of climate change on irrigation, farmers' decisions, and water policies, including water markets, and improving irrigation efficiency. Authorities and farmers could adapt to drought shocks and changes in the market while experiencing less revenue loss

Seasonal Meteorological Drought Prediction Using Support Vector Machine

In various researches, implementation of meteorological parameters in drought prediction is studied. In the current work, meteorological drought classes based on Standardized Precipitation Index (SPI) for six seasonal scenarios (autumn, winter, spring, autumn + winter, winter +spring, and autumn + winter + spring) and meteorological predictors contained ground and sea surface temperature, weather temperature (at 300, 500, 700 and 850 mi bar) and geopotential height (at 300, 500, 700 and 850 mi bar) wide of North (0, 60) and East (0, 90) was applied in prediction models based on data from 1975 to 2005. In these models, temporal range of meteorological predictors is between October to April month on the same predicted SPI. SPI was calculated based on mean precipitation at seasonal time scale in the main watershed of Tehran (Taleghan, Mamloo) by Inverse Weighted Distance method. The well known statistical supervised machine learning method, support vector machine (SVM), is applied to predict SPI. Regarding to selected data points, the effective regions on Tehran precipitation are southern, southwestern and northwestern of Iran in spring, northern and northwestern in autumn and northwestern and western in winter. SVM depicted accurate results in prediction of SPI, spatially prediction of SPI in all scenarios, and it can be proposed as a very suitable statistical learning method in investigating of nonlinear behavior of meteorological phenomena with a short samples. The predicted SPI in spring and autumn are more accurate than the other scenarios

Decontamination of Petroleum Hydrocarbon Contaminated Soils using Bioventing Technique

The fate of petroleum hydrocarbons in nature is of great environmental concern due to their toxic, mutagenic, and carcinogenic properties. A major decomposition process of petroleum hydrocarbons in the environment is microbial degradation. Polycyclic aromatic hydrocarbons (PAHs) are one of the most prevalent groups of contaminants found in soil. This research was carried out on phenanthrene (a 3-ring PAH) polluted soils decontamination in a solid phase reactor using synthetic contaminated soils with attribution of indigenous bacteria isolated from petroleum contaminated sites in Iran. Polluted samples was made of phenanthrene with three rates (100, 500, and 1000 mg/kg of soil) synthetically and was conducted with two bacterial consortium for a period of around twenty weeks. Ultrasonic machine and HPLC was applied for extraction and analysis of phenanthrene from contaminated soil samples. Microbial analyses were carried out using confirmative series tests, analytical profile index (API) kit tests and PCR. Results for phenanthrene biotreatment in solid phase revealed a significance relationship between concentration of phenanthrene and type of microbial consortium and type of soil with the removal efficiency over time of bioremediation (P value<0.001). According to the microbial analysis using complete amplified PCR and DNA extraction, among of Pseudomonas fluorescence, Serratia liquefaciens, Bacillus and Micrococcus strains that were as dominant bacterial consortiums in the contaminated soil samples, Pseudomonas fluorescence (pudita) was responsible to higher degree degradation of phenanthrene. Results showed that the microbial decomposition of the lower concentrations of phenanthrene needs shorter time compared with the higher concentrations. We can concluded that, the microbial treatment of oil hydrocarbons contaminated soils may considered as a feasible option in petroleum polluted sites in Iran

Recognition and Spatial Mapping of Multivariate Groundwater Quality Index using Combined Fuzzy Method

Methods for evaluatingthe quality of groundwater resources and recognition of appropriate locations for urban and agricultural water demand has been known as an important item in water resources planning. The main focus of this paper has been addressed a new water quality mapping based on coupling of fuzzy approximation and water quality indexing. In this paper, after indexing water quality in each monitoring well, based on fuzzy reasoning a new global fuzzy indexing has been presented. In this regard, 12 water quality parameters for 217 monitoring wells in the province of Ghazvin in the north have been used. In the final step, map of fuzzy evaluation over the area of interest has been provided based on an optimized new spatial approximation via Genetic Algorithm (GA). The results showed the capability of the proposed methodology for groundwater quality mapping. The most important contribution of this paper is successful combination of fuzzy reasoning and water quality indexing as a continuous function for evaluating groundwater quality mapping