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Zohreh Karimi,1 Zhila Fereidouni,2 Mohammad Behnammoghadam,3,4 Nasrollah Alimohammadi,5 Ali Mousavizadeh,6 Tahmine Salehi,7 Mohammad Saeed Mirzaee,8 Sobhan Mirzaee9 1Department of Operating Room, School of Paramedicine, Yasuj University of Medical Sciences, Yasuj, Iran; 2Department of Medical Surgical Nursing, Nursing School, Fasa University of Medical Sciences, Fasa, Fars, Iran; 3School of Nursing, Yasuj University of Medical Sciences, Yasuj, Iran; 4School of Nursing and Midwifery, Isfahan University of Medical Sciences, Isfahan, Iran; 5Critical Care Nursing Department, Faculty of Nursing and Midwifery, Isfahan University of Medical Sciences, Isfahan, Iran; 6Department of Biostatistics and Epidemiology, School of Health, Yasuj University of Medical Sciences, Yasuj, Iran; 7Nursing Care Research Center (NCRC), School of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran; 8School of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran; 9Student Research Committee, Yasuj University of Medical Sciences, Yasuj, IranCorrespondence: Mohammad Behnammoghadam School of Nursing and MidwiferyIsfahan University of Medical Sciences, Isfahan, IranEmail mbehnam1363@gmail.comMohammad Saeed Mirzaee School of Nursing and MidwiferyIran University of Medical Sciences, Tehran, IranEmail Saeedmirzaee75@gmail.comObjective: This study aimed to explore the lived experiences of nurses caring for patients with COVID-19 in Iran.Methods: This study was a descriptive phenomenology. Sampling was purposefully performed, and participants were selected in terms of the inclusion criteria. Data were collected through semi-structured interviews using the WhatsApp mobile messaging application. Colaizzi’s method was used to analyse the data. The criteria introduced by Lincoln and Guba were used for the study rigour.Results: The data were obtained from 12 nurses caring for patients with COVID-19. The mean age of the participants was 29.41 years (SD = 2.72) with a mean work experience of 6.75 years (SD = 2.52). Three main themes and six subthemes were identified: mental condition (subthemes included “anxiety and stress” and “fear”), emotional condition (subthemes included “suffering and affliction” and “waiting for death”), and care context (subthemes included “turmoil” and “lack of support and equipment”).Conclusion: The results of this study show that nurses working in the wards and care centres designated for patients with COVID-19 are experiencing mental and emotional distress and are working in inadequate professional conditions.Keywords: nurse experience, nursing care, COVID-19, phenomenology

A halo-tolerant bacterial strain Paenibacillus glucanolyticus sp. strain T7-AHV isolated from marine environment was used for bioremediation of n-hexadecane-contaminated soil. Soil/water ratio, initial inoculums volume, surfactant addition, n-hexadecane concentration, and salinity were investigated. The possibility of biosurfactant production by isolated strain was also studied, and the results demonstrated that it was not a biosurfactant producer, based on measurement of the surface tension of culture broth. Both tween 80 and rhamnolipid enhanced the biodegradation of n-hexadecane significantly up to 44 and 46%, respectively. A biodegradation rate of 39.7% was observed at salinity level of up to 2%, and the biodegradation efficiency decreased significantly at higher salinity concentrations. A natural hydrocarbon-contaminated soil sample with total petroleum hydrocarbon (TPH) concentration of 1437 mg kg-1 was subjected to bioremediation using the selected conditions of operational parameters, and a biodegradation rate of 22.1% was obtained. [ABSTRACT FROM AUTHOR]

Rill erosion plays an important role in the amount of soil detachment and the transport sediment load on hillslope. Quantification of the soil erosion requires a more precise understanding of the processes and development of rill erosion models. The objective of this study was to derive and evaluate hydraulics and detachment models of rill erosion in calcareous soils of northwestern Iran. Rill erosion experiments were carried out at 55 locations with three replications under field conditions. At each point, the rill plots were created with a 0.2 m width and 4 m length on agricultural soils. The inflow rates were 4, 12, 20 and 30 l min −1 with varying slope from 4 to 25.5%. The results indicated that all conditions of flow regimes including sub- and super-critical (laminar and turbulent) were observed in created rills by overland flow. The mean flow velocity and rill depth have been described well by flow rate and slope gradient, while rill width and flow depth have been explained well by flow rate. The prediction detachment rate by rill flow based on stream power model by non-linear regression yielded the best results (R 2  = 0.545 and RMSE = 0.00213 kg m −2  s −1 ) for all combinations of slope classes. However, there are no significant differences between prediction accuracy of linear and non-linear models, when individual slope classes were considered. [ABSTRACT FROM AUTHOR]

Cobalt ferrite nanoparticles (NPs) have been synthesized by the modified co-precipitation technique in the presence of the polyvinyl alcohol (PVA) matrix. The structural and magnetic properties of NPs are tunable by means of interaction between the polymer and the surface of NPs. Magnetic properties of NPs were simulated using the accurate Monte Carlo (MC) method. In addition, the magnetic anisotropy constant has been obtained by means of the law of approach to saturation magnetization (LAS). The experimental and theoretical results are in good agreement with each other and show that the as-synthesized NPs are single domain and approximately non-interacting. The anisotropy constant and size of the NPs increase by increasing the concentration of precursors in the reaction medium. Nanocomposites have been characterized by X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR). Hysteresis loops were investigated at room temperature using a vibrating sample magnetometer (VSM). The crystallite size of single-domain NPs is lower than 20 nm, and the obtained results from FT-IR confirmed the interaction between PVA and the surface of the particles. These approximately non-interacting NPs are useful for magnetic data storage. [ABSTRACT FROM AUTHOR]

Masouleh is one of the ancient cities located in a high mountainous area in Gilan province of northern Iran. The region is threatened by a hazardous landslide, which was last activated in 1998, causing 32 dead and 45 injured. Significant temporal decorrelation caused by dense vegetation coverage within the landslide area makes the use of Synthetic Aperture Radar Interferometry (InSAR) for monitoring landslide movement very challenging. In this paper, we investigate the capability of three InSAR time-series techniques for evaluating creep motion on Masouleh landslide. The techniques are Persistent Scatterer Interferometry (PSI), Small BAseline Subset (SBAS) and SqueeSAR. The analysis is done using a dataset of 33 TerraSAR-X images in SpotLight (SL) mode covering a period of 15 months between June 2015 and September 2016. Results show the distinguished capability of SqueeSAR method in comparison to 2 other techniques for assessing landslide movement. The final number of scatterers in the landslide body detected by PSI and SBAS are about 70 and 120 respectively while this increases to about 345 in SqueeSAR. The coherence of interferograms improved by about 37% for SqueeSAR as compared to SBAS. The same rate of displacement was observed in those regions where all the methods were able to detect scatterers. Maximum rates of displacement detected by SqueeSAR technique in the northern edge, older and younger part of the landslide body are about -39, -65 and -22 mm/y, respectively. [ABSTRACT FROM AUTHOR]

Shabkola is a village located in Mazandaran province of northern Iran that suffers from the mass movement happening in the upstream. Deforestation and changes to land use are the main reasons for the soil instability in this region, which together with steep slope, relatively high precipitation rate and natural erosion has led to such a condition. The area of mass movement is approximately 90 hectares which is a big threat for people living in the region. In this study, we have utilized two different geodetic techniques including InSAR time-series analysis and GPS measurements to assess slope stability in Shabkola. The SAR dataset includes 19 ALOS/PALSAR images spanning from July 2007 to February 2011 while GPS observations are collected in 5 campaigns from September 2011 to May 2014. Displacement as much as approximately 11.7 m in slope direction was detected by GPS observations for the 2011-2014 time period. Most of the slope geometry is in north-south direction, for which the sensitivity of InSAR for displacement detection is low. However, ALOS PALSAR data analysis revealed a previously unknown landslide, covered by dense vegetation in the northern part of main Shabkola landslide, showing line-of-sight velocity of approximately 2cm/year in the time period 2007-2011. [ABSTRACT FROM AUTHOR]

Estimation of soil organic matter (SOM) at unsampled locations is crucial in agronomical and environmental studies. In this study, the ability of geostatistical methods such as ordinary kriging (OK), simple kriging (SK) and cokriging (CK) and hybrid geostatistical methods such as regression-simple kriging (RSK)/-ordinary kriging (ROK) and artificial neural network-simple kriging (ANNSK)/-ordinary kriging (ANNOK) was evaluated to predict SOM content. To this end, a set of 100 soil samples were collected from 0 to 15 cm depth of agricultural soils in Selin plain, northwest of Iran. The organic carbon was measured using Walkley–Black method. An auxiliary variable was provided by remote sensing data (Landsat 7 ETM +). Three performance criteria including mean error (ME), root mean square error (RMSE) and coefficient of determination (R 2 ) were used to evaluate the performance of the derived models. The results showed that the ANN model that used principal components (PCs) as input variables, performed better than the multiple linear regression (MLR) model. The hybrid geostatistical methods, which include ANNOK, ANNSK, ROK and RSK provided more reliable predictions than the geostatistical methods, which include SK, OK and CK. In general, the best prediction method for the estimation of SOM spatial distribution was the ANNOK model, which had the smallest RMSE (0.271%) and the highest R 2 (0.633). It was concluded that information from Landsat ETM + imagery is potential auxiliary variables for improving spatial prediction, monitoring SOM and development of high quality SOM maps, which is the primary step in site-specific soil management. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the effect of various Global Digital Elevation Models (GDEMs) in producing high-resolution topography model using TanDEM-X (TDX) Coregistered Single Look Slant Range Complex (CoSSC) images. We selected an image acquired on Jun 12th, 2012 over Doroud region in Lorestan, west of Iran and used 4 external digital elevation models in our processing including DLR/ASI X-SAR DEM (SRTM-X, 30m resolution), ASTER GDEM Version 2 (ASTER-GDEMV2, 30m resolution), NASA SRTM Version 4 (SRTM-V4, 90m resolution), and a local photogrammetry-based DEM prepared by National Cartographic Center (NCC DEM, 10m resolution) of Iran. InSAR procedure for DEM generation was repeated four times with each of the four external height references. The quality of each external DEM was initially assessed using ICESat filtered points. Then, the quality of, each TDX-based DEM was assessed using the more precise external DEM selected in the previous step. Results showed that both local (NCC) DEM and SRTM X-band performed the best (RMSE< 9m) for TDX-DEM generation. In contrast, ASTER GDEM v2 and SRTM C-band v4 showed poorer quality. [ABSTRACT FROM AUTHOR]

Remote sensing plays a key role in monitoring and assessing environmental changes. Because of its special imaging characteristics such as high-resolution, capabilities to obtain data in all weather conditions and sensitivity to geometrical and dielectric properties of the features, Synthetic Aperture Radar (SAR) technology has become a powerful technique to detect small scale changes related to earth surface.SAR images contain the information of both phase and intensity in different modes like single, dual and full polarimetric states which are important in order to extract information about various targets. In this study we investigate phenological changes in an agricultural region using high-resolution X-band SAR data. The case study is located in Doroud region of Lorestan province, west of Iran. The purpose is to investigate the ability of copolar and interferometric coherence extracted from TanDEM-X dual polarimetry (HH/VV) in bistatic StripMap mode for tracking the phenological changes of crops during growing season. The data include 11 images acquired between 12.06.2012 and 02.11.2012 and 6 images acquired between 30.05.2013 and 04.08.2013 in the CoSSC format. Results show that copolar coherence is almost able to follow phenological changes but interferometric coherence has a near constant behaviour with fluctuations mainly related to baseline variations. [ABSTRACT FROM AUTHOR]

The objective of this research was to determine the best model and compare performances in terms of producing land use maps from six supervised classification algorithms. As a result, different algorithms such as the minimum distance of mean (MDM), Mahalanobis distance (MD), maximum likelihood (ML), artificial neural network (ANN), spectral angle mapper (SAM), and support vector machine (SVM) were considered in three areas of Iran's dry climate. The selected study areas for dry climates were Shahreza, Taft and Zarand in Isfahan, Yazd, and Kerman Provinces, respectively. Three Landsat ETM+ images and topographical maps of 1:25,000-scale were used in the present study. In addition, training samples for each land use were constructed using GPS and extensive field surveys. The training sites were divided into two categories; one category was used for image classification and the other for classification accuracy assessment. Results show that for the dry climate areas, Maximum Likelihood and Support Vector Machine algorithms with averages of 0.9409 and 0.9315 Kappa coefficients are the best algorithms for land use mapping. The ANOVA test was performed on Kappa coefficients, and the result shows that there are significant differences at the 1% level, between the different algorithms for the dry climate zones. These results can be used for land use planning, as well as environmental and natural resources purposes in study areas. [ABSTRACT FROM AUTHOR]

Due to its special imaging characteristics, Synthetic Aperture Radar (SAR) has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM) classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient. [ABSTRACT FROM AUTHOR]

Bending is one of the processes frequently used during manufacturing of sheet-metal components. Spring-back in bending operations is an important issue when producing precision parts. This issue becomes even more important when the component has any kind of hole on the bending surface. Such components are the focus of study in this paper. Many parameters affect spring-back in the bending process; in the present work, perforated components with an oblong cut are selected, and the influence of cut size, die radius, clearance, and component material on the value of the spring-back in a wipe-bending process are studied. Four different hole sizes, three die radii and clearance, and two different steel materials (high-strength low-alloy steel and low-carbon steel) are used in experiments and finite-element simulations. Results show these parameters have effect on the amount of spring-back in the wipe-bending process. [ABSTRACT FROM AUTHOR]

The enhancement of the antibacterial activity of ampicillin by different extracts of Berberis integerrima fruits was evaluated against Staphylococcus aureus. Disk diffusion and agar dilution methods were used to determine the antibacterial activity of ampicillin in the absence and presence of different plant extracts or various fractions eluted by column chromatography. A clinical isolate of S. aureus was used as a test strain. The active component of B. integerrima fruits involved in the enhancement of ampicillin activity was purified and identified as 1-methyl malate using different spectroscopic methods. Both the ethanol extract of B. integerrima fruits and 1-methyl malate enhanced the antibacterial activity of ampicillin. The total extract as well as 1-methyl malate increased the antibacterial activity of ampicillin against the test strain. The potency of ampicillin against the test strain was increased 64-fold when tested with a sub-toxic concentration of total extract of B. integerrima fruits. Also, 1-methyl malate increased the bactericidal activity of ampicillin. In the presence of 2 mg/mL of 1-methyl malate the MIC of ampicillin for S. aureus decreased from 128 to 1 µg/mL (128-fold). Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Activation of nucleoside analogues is dependent on kinases and 5′-nucleotidases and the balance between the activity of these enzymes. The purpose of this study was to analyze deoxycytidine kinase, deoxyguanosine kinase, and 4 different 5′-nucleotidases during cell cycle progression in MOLT-4 cells. The activity of both kinases was cell cycle dependent and increased during proliferation while the activity of cytosolic 5′-nucleotidase I decreased. We could show that the kinase activity was higher than the total nucleotidase activity, which was unchanged or decreased during cell cycle progression. These data may be important in designing modern combination therapy with nucleoside analogues. [ABSTRACT FROM AUTHOR]

• K ib , K rb and τ cb were predicted by aspatial (MLR and ANN models) and spatial methods. • Type I data developed with measured soil properties and auxiliary data. • Type II data developed using principal components. • Type I ANN models were the best aspatial model to predict K ib and K rb. • Type II ANN models were the best aspatial model to predict τ cb. • ANN-Kriging was the best spatial model to predict soil sensitivity to erosion. Soil erosion prediction and conservation planning require detailed soil data under different environmental conditions. When such data are needed at the field scale, aspatial and spatial models could be used to predict soil erosion processes. This study was conducted to develop spatial models including geostatistical models (i.e. ordinary kriging (OK) and cokriging (CK)) and hybrid geostatistical models (i.e. multiple linear regression-kriging (MLRK) and artificial neural network-kriging (ANNK)) for estimating WEPP baseline soil sensitivity to erosion parameters for calcareous agricultural soils in northwest Iran. Inter-rill and rill erosion simulation experiments were carried out at 100 locations at the field scale with 3 replications. At each location, the soil properties (organic matter, calcium carbonate equivalent, sand, silt, clay, base infiltration rate) were measured and auxiliary data obtained from attributes derived from digital elevation models (elevation, slope, stream power index, wetness index and sediment transport index) and remote sensing data (three visible bands, NIR, SWIR (5 and 7 bands), NDVI indices). The MLR and ANN models were used to estimate baseline inter-rill soil sensitivity to erosion (K ib) and rill soil sensitivity to erosion (K rb and τ cb) using two types of input data. For the first type of prediction models (type I), the measured soil properties and auxiliary data were used, whereas for the second type of models (type II), principal components (PCs) based on the soil and auxiliary data were used. In comparison to the models that were developed here, the WEPP inter-rill and rill soil sensitivity to erosion models showed a relatively poor performance. The ANN models developed here predicted K ib , K rb and τ cb parameters better than the MLR models using both types of data (type I and II). Moreover, the results indicated that the ANNK model was the most appropriate spatial or hybrid model for predicting soil sensitivity to erosion parameters. [ABSTRACT FROM AUTHOR]