Investigation of Land Use Changes in North of Iran Using Remote Sensing and Geographical Information System (1986-2015)

Deforestation in Iran has been more rapid in the past 50 years than at any time in Iran’s history, and Neka basin located in the north of Iran has been subjected to severe deforestation problems. Detection of ecosystem changes may help decision makers and planners to understand the factors in land use and land cover changes in order to take effective and useful measures. Using remote sensing and GIS technologies are used as efficient tools for monitoring and evaluation land use change. In recent years, a considerable land use changes have occurred in in the Neka basin. This paper presents findings of an evaluation study that focused on the changes in land use changes in a great basin of Neka. The study was based on a spatial analysis of historical Landsat images (1986–2015) and several field measurements and observations. First, geometric correction and contrast stretch are applied. In order to detect and evaluate land use changes, image differencing, vegetation change analysis, principal component analysis and classification comparison have been applied. Finally, the results of land cover classification for three different times are compared to reveal land use changes. Relatively, agriculture, range and urban developed areas increased, respectively 84.70, 31.88 and 54.52 % from 1986 to 2015, while forest decreased 44.35%. With the greatest decrease occurring from 1991 to 1999. The overly analysis of the four land cover maps revealed that there is an imbalance in the spatial distribution of deforestation areas. The west and central part of the study area has mostly changed and deforestrated.From 1986 to 2015, forest, which covered 1245.53 km2 (47.79%) of the total area in 1986 had decreased to 693.60 (25.60.7%) in 2015. However, the rangelands increased from 1120.42 ha in 1986 to 1477.69 km2 in 20015. 

Abort inom den islamiska rättstraditionen

Den svenska patientpopulationens stora heterogenitet, exempelvis med hänsyn till etnicitet, kultur, religion och nationell härkomst, kan på olika sätt påverka hur patienter uppfattar vad som utgör god vård. Islam och muslimer utgör idag en del av det svenska samhället och representerar en beaktansvärd del av dem som vänder sig till hälso- och sjukvården. Forskning om islam och frågor rörande hälso- och sjukvård i den svenska kontexten är dock begränsad. Inte minst gäller det synen på abort inom islam. Syftet med denna artikel är att delvis fylla denna lucka genom att beskriva hur abort behandlats inom den islamiska rättstraditionen samt presentera två abortlagstiftningar från islamiskt färgade rättsordningar (Iran och Tunisien). Kunskap om andra normsystem än det ”svenska” utgör en viktig grund för en god kommunikation. Behovet av kommunikation och försök till förståelse torde öka när en åtgärd inom hälsooch sjukvården, såsom abort, aktualiserar frågor som individen kan förknippa med svåra etiska ställningstaganden. Eftersom religionen för vissa utgör en referensram när de brottas med ställningstaganden som de upplever vara som religiöst, etiskt och psykologiskt känsliga, kan en ökad kunskap om synen på abort i islamisk rätt i bästa fall ge en insikt om hur muslimska abortpatienter har präglats i sina ställningstaganden

Abort inom den islamiska rättstraditionen

Den svenska patientpopulationens stora heterogenitet, exempelvis med hänsyn till etnicitet, kultur, religion och nationell härkomst, kan på olika sätt påverka hur patienter uppfattar vad som utgör god vård. Islam och muslimer utgör idag en del av det svenska samhället och representerar en beaktansvärd del av dem som vänder sig till hälso- och sjukvården. Forskning om islam och frågor rörande hälso- och sjukvård i den svenska kontexten är dock begränsad. Inte minst gäller det synen på abort inom islam. Syftet med denna artikel är att delvis fylla denna lucka genom att beskriva hur abort behandlats inom den islamiska rättstraditionen samt presentera två abortlagstiftningar från islamiskt färgade rättsordningar (Iran och Tunisien). Kunskap om andra normsystem än det ”svenska” utgör en viktig grund för en god kommunikation. Behovet av kommunikation och försök till förståelse torde öka när en åtgärd inom hälsooch sjukvården, såsom abort, aktualiserar frågor som individen kan förknippa med svåra etiska ställningstaganden. Eftersom religionen för vissa utgör en referensram när de brottas med ställningstaganden som de upplever vara som religiöst, etiskt och psykologiskt känsliga, kan en ökad kunskap om synen på abort i islamisk rätt i bästa fall ge en insikt om hur muslimska abortpatienter har präglats i sina ställningstaganden

Abort inom den islamiska rättstraditionen

Den svenska patientpopulationens stora heterogenitet, exempelvis med hänsyn till etnicitet, kultur, religion och nationell härkomst, kan på olika sätt påverka hur patienter uppfattar vad som utgör god vård. Islam och muslimer utgör idag en del av det svenska samhället och representerar en beaktansvärd del av dem som vänder sig till hälso- och sjukvården. Forskning om islam och frågor rörande hälso- och sjukvård i den svenska kontexten är dock begränsad. Inte minst gäller det synen på abort inom islam. Syftet med denna artikel är att delvis fylla denna lucka genom att beskriva hur abort behandlats inom den islamiska rättstraditionen samt presentera två abortlagstiftningar från islamiskt färgade rättsordningar (Iran och Tunisien). Kunskap om andra normsystem än det ”svenska” utgör en viktig grund för en god kommunikation. Behovet av kommunikation och försök till förståelse torde öka när en åtgärd inom hälsooch sjukvården, såsom abort, aktualiserar frågor som individen kan förknippa med svåra etiska ställningstaganden. Eftersom religionen för vissa utgör en referensram när de brottas med ställningstaganden som de upplever vara som religiöst, etiskt och psykologiskt känsliga, kan en ökad kunskap om synen på abort i islamisk rätt i bästa fall ge en insikt om hur muslimska abortpatienter har präglats i sina ställningstaganden

COMPARATIVE INVESTIGATION ON THE ANATOMICAL, PHYSICAL AND CHEMICAL CHARACTERISTICS OF ZIZIPHUS SPINA - CHRISTI (L.) WILD FROM TWO REGION IN IRAN

Ziziphus spina- christi of the family Rhamnaceae is widely distributed especially in the southern region of Iran and considered as one of the most drought - resistant sub species of the country. This investigation is the first attempt to study wood properties of this species, in order to contribute to a better understanding of it. It seems necessary to recognize the best utilization of this wood that are potentially available and easy to caltivate in Iran.The results of this study revealed that Ziziphus spina - christi is a diffuse - porous with pores round to oval, dense, hard and fine - textured wood. The length of vessel elements is medium, and the diameter relative high, few vessels per unit area and the type of perforation plates is simple. Parenchyma scanty paratracheal, vasicentric and rarely aliform. Libriform fibers length medium, thin to thick - walled. Rays 1-2 cells wide with medium length and not visible with nakedeye, crystals are common in most rays. In this species also percentages of cellulose and lignin are high but ash and extractive soluble in acetone content was found to be low

COMPARATIVE INVESTIGATION ON THE ANATOMICAL, PHYSICAL AND CHEMICAL CHARACTERISTICS OF ZIZIPHUS LOTUS (L.) LAM. FROM TWO REGION IN IRAN

Ziziphus lotus of the family Rhamnaceae is distributed in the southern region of Iran and considered as one of drought - resistant tree species of the country. This investigation is the first attempt to study wood properties of this species, in order to contribute to a better understanding of it. The results of this study revealed that Ziziphus lotus is a diffuse – porous with basic specific gravity medium and medium - textured wood. The length of vessel elements are medium, the diameter of vessel elements is small, porous with pores round to oval, intervessel pilting, opposite and intermediate, 20 vessels per square millimeter, simple perforation plates, vessel - ray pits similar to intervessel pits in size and shape and half  bordered; Vascular tracheids present, there are rarely tyloses and Gums in vessels. Fibers with simple to minutely bordered pits, thin - to thick – walled and fiber lengths short; Parenchyma scanty paratracheal, vasicentric and rarely aliform; Ray uniseriate and sometimes biseriate, ray height is short, rays with procumbent, Square and upright cells mixed throughout the ray and one Prismatic crystals in chambered upright and square ray cells, rays 12 per mm, silica bodies in ray cells; There are 7-10 Schizogenous canals in pith.In this species also percentages of cellulose are high but ash and extractive soluble in acetone content was found to be low

Double Coating as a Novel Technology for Controlling Urea Dissolution in Soil: A Step toward Improving the Sustainability of Nitrogen Fertilization Approaches

This research introduces a novel technology for reducing ordinary urea (OU) dissolution by developing double-coated urea (DCU) using phosphate rock (PR) as an outer layer to reduce its hydrolysis and sodium thiosulfate (STS) as an inner layer to inhibit the urease enzyme and nitrification process. Due to the double coating, the nitrogen content of DCU was lower than that of the OU (36.7% vs. 46.5%). The ultramorphological analysis using scanning electron microscopy (SEM) indicated that the controlled coating of urea, resulting from the outer layer of PR, was due to the adhesive effect of urea formaldehyde (UF), which was used as a glue. In addition, the transmission electron microscopy (TEM) analysis of the DCU revealed its high degree of agglomeration. The mechanical hardness of DCU was higher compared to that of OU (1.38 vs. 1.08 kgf). The seven-day dissolution rate test showed that OU reached 100% dissolution on the fifth day. The rate of DCU, however, was significantly lower (32% dissolution in the seventh day). Cumulative NO3− and NH4+ losses from a clay soil sample reached 68.3% and 7.6%, respectively, with OU measuring 40.5% compared to 4.9% for DCU 70 days after application. Field experiments showed a significant improvement in the marketable yield and agronomic nitrogen efficiency (ANE) of maize grains and zucchini fruits fertilized with DCU. Furthermore, the macro and micronutrient concentrations in maize grains and zucchini fruits showed an increase in the plants fertilized with DCU. In summary, double coating can be introduced as a novel technique to control urea dissolution in soil

Coupling Process-Based Models and Machine Learning Algorithms for Predicting Yield and Evapotranspiration of Maize in Arid Environments

Crop yield prediction is critical for investigating the yield gap and potential adaptations to environmental and management factors in arid regions. Crop models (CMs) are powerful tools for predicting yield and water use, but they still have some limitations and uncertainties; therefore, combining them with machine learning algorithms (MLs) could improve predictions and reduce uncertainty. To that end, the DSSAT-CERES-maize model was calibrated in one location and validated in others across Egypt with varying agro-climatic zones. Following that, the dynamic model (CERES-Maize) was used for long-term simulation (1990–2020) of maize grain yield (GY) and evapotranspiration (ET) under a wide range of management and environmental factors. Detailed outputs from three growing seasons of field experiments in Egypt, as well as CERES-maize outputs, were used to train and test six machine learning algorithms (linear regression, ridge regression, lasso regression, K-nearest neighbors, random forest, and XGBoost), resulting in more than 1.5 million simulated yield and evapotranspiration scenarios. Seven warming years (i.e., 1991, 1998, 2002, 2005, 2010, 2013, and 2020) were chosen from a 31-year dataset to test MLs, while the remaining 23 years were used to train the models. The Ensemble model (super learner) and XGBoost outperform other models in predicting GY and ET for maize, as evidenced by R2 values greater than 0.82 and RRMSE less than 9%. The broad range of management practices, when averaged across all locations and 31 years of simulation, not only reduced the hazard impact of environmental factors but also increased GY and reduced ET. Moving beyond prediction and interpreting the outputs from Lasso and XGBoost, and using global and local SHAP values, we found that the most important features for predicting GY and ET are maximum temperatures, minimum temperature, available water content, soil organic carbon, irrigation, cultivars, soil texture, solar radiation, and planting date. Determining the most important features is critical for assisting farmers and agronomists in prioritizing such features over other factors in order to increase yield and resource efficiency values. The combination of CMs and ML algorithms is a powerful tool for predicting yield and water use in arid regions, which are particularly vulnerable to climate change and water scarcity

Coupling Process-Based Models and Machine Learning Algorithms for Predicting Yield and Evapotranspiration of Maize in Arid Environments

Crop yield prediction is critical for investigating the yield gap and potential adaptations to environmental and management factors in arid regions. Crop models (CMs) are powerful tools for predicting yield and water use, but they still have some limitations and uncertainties; therefore, combining them with machine learning algorithms (MLs) could improve predictions and reduce uncertainty. To that end, the DSSAT-CERES-maize model was calibrated in one location and validated in others across Egypt with varying agro-climatic zones. Following that, the dynamic model (CERES-Maize) was used for long-term simulation (1990–2020) of maize grain yield (GY) and evapotranspiration (ET) under a wide range of management and environmental factors. Detailed outputs from three growing seasons of field experiments in Egypt, as well as CERES-maize outputs, were used to train and test six machine learning algorithms (linear regression, ridge regression, lasso regression, K-nearest neighbors, random forest, and XGBoost), resulting in more than 1.5 million simulated yield and evapotranspiration scenarios. Seven warming years (i.e., 1991, 1998, 2002, 2005, 2010, 2013, and 2020) were chosen from a 31-year dataset to test MLs, while the remaining 23 years were used to train the models. The Ensemble model (super learner) and XGBoost outperform other models in predicting GY and ET for maize, as evidenced by R2 values greater than 0.82 and RRMSE less than 9%. The broad range of management practices, when averaged across all locations and 31 years of simulation, not only reduced the hazard impact of environmental factors but also increased GY and reduced ET. Moving beyond prediction and interpreting the outputs from Lasso and XGBoost, and using global and local SHAP values, we found that the most important features for predicting GY and ET are maximum temperatures, minimum temperature, available water content, soil organic carbon, irrigation, cultivars, soil texture, solar radiation, and planting date. Determining the most important features is critical for assisting farmers and agronomists in prioritizing such features over other factors in order to increase yield and resource efficiency values. The combination of CMs and ML algorithms is a powerful tool for predicting yield and water use in arid regions, which are particularly vulnerable to climate change and water scarcity

Laboratory and Pilot-Plant Scale Photocatalytic Degradation of Polychlorinated Biphenyls in Seawater Using CM-n-TiO2 Nanoparticles

Photocatalytic degradation of polychlorinated biphenyls (PCBs) in seawater was successfully achieved at laboratory level with UV light and at pilot-plant scale under natural solar radiation using carbon-modified titanium oxide (CM-n-TiO2) nanoparticles. The photocatalytic performance of CM-n-TiO2 was comparatively evaluated with reference n-TiO2 under identical conditions. As a result of carbon incorporation, significant enhancement of photodegradation efficiency using CM-n-TiO2 was clearly observed. To optimize the operating parameters, the effects of catalyst loading and pH of the solution on the photodegradation rate of PCBs were investigated. The best degradation rate was obtained at pH 5 and CM-n-TiO2 loading of 0.5 g L−1. The photodegradation results fitted the Langmuir-Hinshelwood model and obeyed pseudo-first-order reaction kinetics