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1.
Screening bioactive natural products from bacteria is a determinative step in the drug discovery programs. The present study aim to isolate actinobacteria from the Oman Sea sediments for determining the effects of different culture media and treatments on the yield of the isolation process, and measure the DPPH radical scavenging and Artemia cytotoxic activity of culture extracts of the actinobacterial isolates. A total of 290 actinobacterial isolates were collected from 14 sediment samples. Heat treatment(40.68%) and M_4 medium(29.31%) exhibited the maximum isolation rates of actinobacteria. Streptomyces isolates were dominantly distributed in all of the investigated stations according to 16 S rRNA gene sequencing. The distribution pattern of Streptomyces followed a depth-dependent frequency trend, whereas the members of rare genera including Micromonospora, Nocardia Actinoplanes, Nocardiopsis, Saccharopolyspora and Crossiella were distributed in deeper stations. Approximately,25% of the examined isolates could scavenge 90% of 10~(–4) mol/L DPPH solutions at 1 250 μg/mL final concentration of their ethyl acetate culture extracts. Furthermore, the most potent extracts could scavenge DPPH radicals with IC50 ranges from 356.8 to 566.4 μg/mL. Brine shrimp cytotoxicity tests showed that 38.88% of the examined culture extracts exhibited LC_(50) lower than 1 000 μg/mL against the Artemia cells. Moreover, the most potent culture extracts exhibited LC_(50) range from 335.4 to 534.4 μg/mL. Phylogenetic analysis by 16 S rRNA gene sequence revealed that the OS 005, OS 263 and OS 157 closely related to Streptomyces djakartensis, Streptomyces olivaceus and Nocardiopsis dassonvillei respectively. These results suggested the widespread distribution of the antioxidant and cytotoxic producing actinobacteria in the Oman Sea sediments, which could be considered as promising candidates for the discovery of microbial bioactive compounds.  相似文献   
2.
Rapid population growth, industrialization, and agricultural expansion in the Khoy area (northwestern Iran) have led to its dependence on groundwater and degradation of groundwater quality. This study attempts to decipher the major processes and factors that degrade the groundwater quality of the Khoy plain. For this purpose, 54 groundwater samples from unconfined and confined aquifers of the plain were collected in July 2017 and analyzed for major cations and anions (Na, K, Ca, Mg, HCO3, SO4, and Cl), minor ions (NO3 and F), and Al. Magnesium and bicarbonate were identified as the dominant cation and anion, respectively. Several ionic ratios and geochemical modeling using PHREEQC indicated that the most important hydrogeochemical processes to affect groundwater quality in the plain were weathering and dissolution of evaporitic and silicate minerals, mixing, and ion exchange. There were smaller effects from evaporation and anthropogenic factors (e.g., industries). Results showed that the high salinity of the groundwater in the northeast area of the plain was due to the high solubility of the evaporitic minerals, e.g., halite and gypsum. Reverse ion exchange and the contribution of mineral dissolution were more significant than ion exchange in the northeastern part of the plain. Elevated salinity of the groundwater in the southeast was attributed mostly to reverse ion exchange and somewhat to evaporation.  相似文献   
3.
One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7%from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4%from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.  相似文献   
4.
Acta Geotechnica - In this study, an analytical model is developed to establish a framework for predicting the coefficient of lateral soil pressure in unsaturated soils. To this end, the disturbed...  相似文献   
5.
Mangroves are coastal ecosystems, found in tropical and subtropical regions around the world. They are found in the transitional zones between land, sea, and rivers. Petroleum hydrocarbons are the most common environmental pollutants, and oil spills pose a great hazard to mangroves forests. This research was focused on the isolation and characterization of crude oil‐degrading bacteria from mangrove ecosystems at the Persian Gulf. Sixty‐one crude oil‐degrading bacteria were isolated from mangrove samples (plant, sediment, and seawater) that enriched in ONR7a medium with crude oil as only carbon source. Some screening tests such as growth at high concentration of crude oil, bioemulsifier production, and surface hydrophobicity were done to select the most efficient strains for crude oil degradation. Molecular identification of strains was carried out by amplification of the 16S rRNA gene by PCR. The results of this study were indicated that the quantity of crude oil‐degrading bacteria was higher in the root of mangrove plants compare to other mangrove samples (sediment and seawater). Also, identification results confirmed that these isolated strains belong to Vibrio sp. strain NW4, Idiomarina sp. strain BW32, Kangiella sp. strain DP40, Marinobacter sp. strain DW44, Halomonas sp. strain BS53, and Vibrio sp. strain DS35. The application of bioremediation strategies with these bacteria can reduce crude oil pollution in this important marine environment.  相似文献   
6.
The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.  相似文献   
7.
8.
In this study, new empirical equations were developed to predict the soil deformation moduli utilizing a hybrid method coupling genetic programming and simulated annealing, called GP/SA. The proposed models relate secant (Es), unloading (Eu) and reloading (Er) moduli obtained from plate load–settlement curves to the basic soil physical properties. Several models with different combinations of the influencing parameters were developed and checked to select the best GP/SA models. The database used for developing the models was established upon a series of plate load tests (PLT) conducted on different soil types at various depths. The validity of the models was tested using parts of the test results that were not included in the analysis. The validation of the models was further verified using several statistical criteria. A traditional GP analysis was performed to benchmark the GP/SA models. The contributions of the parameters affecting Es, Eu and Er were analyzed through a sensitivity analysis. The proposed models are able to estimate the soil deformation moduli with an acceptable degree of accuracy. The Es prediction model has a remarkably better performance than the models developed for predicting Eu and Er. The simplified formulations for Es, Eu and Er provide significantly better results than the GP-based models and empirical models found in the literature.  相似文献   
9.
New empirical models were developed to predict the soil deformation moduli using gene expression programming (GEP). The principal soil deformation parameters formulated were secant (Es) and reloading (Er) moduli. The proposed models relate Es and Er obtained from plate load-settlement curves to the basic soil physical properties. The best GEP models were selected after developing and controlling several models with different combinations of the influencing parameters. The experimental database used for developing the models was established upon a series of plate load tests conducted on different soil types at depths of 1–24 m. To verify the applicability of the derived models, they were employed to estimate the soil moduli of a part of test results that were not included in the analysis. The external validation of the models was further verified using several statistical criteria recommended by researchers. A sensitivity analysis was carried out to determine the contributions of the parameters affecting Es and Er. The proposed models give precise estimates of the soil deformation moduli. The Es prediction model provides considerably better results in comparison with the model developed for Er. The simplified formulation for Es significantly outperforms the empirical equations found in the literature. The derived models can reliably be employed for pre-design purposes.  相似文献   
10.
Abstract

The impact of the two phases of El Niño‐Southern Oscillation (ENSO), namely El Niño and La Niña, on the surface and lower tropospheric temperature fields over Canada is documented. Gridded surface temperature data for 91 years (1900–1990) and 500–1000 hPa thickness data for 49 years (1946–1994) have been analyzed statistically in the context of El Niño, La Niña and normal years.

Using a composite analysis, the present study conclusively demonstrates that significant positive surface temperature anomalies spread eastward from the west coast of Canada to the Labrador coast from the late fall to early spring (November through May) following the onset of El Niño episodes. The accompanying temperatures in the lower troposphere show a transition from the Pacific/North American (PNA) pattern to the Tropical/Northern Hemisphere (TNH) pattern over the North American sector during the same period. Conversely, significant negative surface temperature anomalies spread southeastward from the Yukon and extend into the upper Great Lakes region by the winter season following the onset of La Niña episodes. Furthermore, the lower tropospheric temperatures show a negatively‐phased PNA‐like pattern in early winter which weakens considerably by May of the following year. Thus, while western Canadian surface temperatures are influenced during both phases of ENSO, eastern Canadian surface temperature effects are found during the El Niño phase only. The impact of ENSO on the Canadian surface temperatures is the strongest during the winter season and nearly disappears by spring (April and May). The largest positive (negative) anomalies are found to be centred over two separate regions, one over the Yukon and the other just west of Hudson Bay in the El Niño (La Niña) years. Over western Canada, mean wintertime temperature distribution of the El Niño (La Niña) years is found to be shifted towards warmer (colder) values relative to the distribution of the normal years.

This study suggests the possibility of developing a long‐range forecasting technique for Canada using ENSO related indices.  相似文献   
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