m rahmati

Ethics codes for urban management based on sustainable development are essential to enhance responsible decision-making, transparency, environmental protection, social equality, cooperation, and trust. They provide a guiding framework for urban managers to overcome the complex challenges of urban development while ensuring the long-term welfare of communities and the environment. The primary aim of the current research is to design a qualitative model for developing ethics codes for urban management based on sustainable development.

The research method in this study is qualitative, employing content analysis. The research population includes city mayors, experts in urban management, academic professors who have conducted research in ethics, and managers of institutions and organizations affiliated with municipalities. The sampling method is snowball, with 15 individuals interviewed. The data collection tool was unstructured open interviews, and the qualitative analysis was conducted using MAXQDA software.

The research findings indicated that the development of ethics codes for urban management based on sustainable development includes 58 indicators, 14 core codes, and 5 elective codes.

The development of ethics codes for urban management based on sustainable development encompasses urban sustainability, organization-based procedures for sustainable development, ethics codes of urban management based on sustainable development, strategy for expanding ethics codes based on sustainable development, and executive levels of ethics codes based on sustainable development.

Traffic accidents are a major public health concern worldwide, causing significant loss of life and property damage. To reduce the number of traffic accidents, it is crucial to identify where and when recurrent accidents occur. These accidents often follow specific spatial and temporal patterns and may form clusters, representing areas of concentrated accidents within a geographical space. Therefore, analyzing traffic accidents in both spatial and temporal dimensions is essential for determining the most effective and sustainable solutions. Isfahan province is among the provinces in the country with high accident rates in Suburban areas. Previous research conducted in Isfahan province has predominantly relied on statistical methods and has not adequately addressed the spatial and temporal aspects of accidents.This study aims to address the gaps in previous research by determining the spatial and temporal patterns of urban traffic accidents in Isfahan province and visualizing these patterns using spatial statistical methods in a GIS environment. The novel aspect of this research lies in utilizing spatial statistical techniques to identify and analyze the spatiotemporal patterns of urban accidents in Isfahan province at different time intervals and intensity levels.

The spatial and temporal patterns of traffic accidents in Isfahan Province were investigated using suburban traffic accident data from March 2017 to March 2019. After collecting the relevant data, performing necessary preprocessing, and preparing the data, the spatial and temporal patterns of traffic accidents occurring on the main roads, highways, and freeways of the study area were analyzed and identified using spatial statistical methods such as the Average Nearest Neighbor test, Spatial Autocorrelation (Global Moran's I), and Optimized Hot Spot Analysis (Getis-Ord Gi* technique) at different levels in a GIS environment.

Since the aim of this study is to identify the spatial-temporal patterns of suburban traffic accidents in Isfahan Province, the spatial distribution pattern of accident events was first examined using the Average Nearest Neighbor and Spatial Autocorrelation (Global Moran's I) methods. The results indicated the presence of a strong clustering pattern in the traffic accident data during the study years in Isfahan Province. Then, an optimized Hot Spot Analysis was performed on the entire dataset of accidents using the Getis-Ord Gi* method. Subsequently, the analysis was conducted on the dataset of each level separately, considering different levels such as time of day, day of week, month, year, and accident severity level. The results of the Getis-Ord Gi* analysis at different levels showed that the majority of hot spots with a 99% confidence level are located on the routes leading to the provincial center, namely Isfahan City, as well as the neighboring populous cities. These areas experience the highest volume of traffic and congestion, and the accident density decreases significantly with increasing distance from the provincial center.

Based on the results of the Spatial Autocorrelation analysis of accidents and the hot spot maps at the studied levels, the results showed that accidents are clustered in some areas of Isfahan Province. Proximity to the provincial center and major populated cities has a significant impact on the concentration of traffic accidents in this region. The frequency of accidents decreases with distance from major urban centers. The results of this study and the insights gained about the spatial and temporal patterns of traffic accidents can be used to develop new strategies, guide transportation managers and stakeholders, make decisions, and take suitable proceedings to effectively improve the safety of accident-prone areas.

This study aims to investigate the content, geochemical speciation and mobility of heavy metals as well as mineralogical characteristics of wastes in a coal washing plant (Alborz-e-Sharghi Company). The obtained results revealed that coal wastes as compared to world coal mean are normal to enriched in terms of Pb, Cu, Ni, Cr and As while are depleted with respect to Cd and Zn. XRD analysis indicated that quartz, kaolinite, illite, calcite, calcite, siderite, gypsum and pyrite are present in the studied samples. The results obtained from speciation analysis showed that Pb, As, Cu, Ni and Cr were mainly associated with phases 6 and 5 (sulfide and silicate bound fractions) while Zn and Cd were mostly retrieved from phase 1 (water soluble fraction). The mobility factors also confirms that Zn and Cd with 53.32 and 44.12 % are the most mobilizable elements. This is particularly prominent for 30 years aged coal wastes. This study generally concludes that most mobilized metals such as Zn and Cd have the high potential to find their ways into the surrounding environments and this should be considered in future assessments and management of coal waste produced in the study area.

Considering the adverse effect of changing climate, it is necssary to introduce new commercial high-yielding and marketable almond cultivars with different chilling and heat requirements, flowering time, which can adapt to various regions. Therefore, almond trees of three recently registered cultivars named; Aria, Bardia and Zeighami and two control cultivars grafted on bitter almond seedlings were compared using randomized complete block design with five replications from 2018-21 in an almond orchard in Neyriz of Fars province in Iran. Chilling and heat requirements, tree growth vigor, yield related traits, and relationships between different pomological and morphological characteristics were measured and evaluated. The results showed that cv. Aria was superior to the other cultivars due to its higher trunk cross-sectional area (TCSA) (325 cm2) and production and yield efficiency (100.26 g nut and 25.36 g kernel per cm2 TCSA). The proportion of double kernels and kernels in the Zeighami and Bardia cultivars, respectively, was below the standard classification for almonds. Cv. Aria and cv. Bardia had the lowest chilling requirements (296 CU) and cv. Ferraduel the highest (515 CU). The heat requirement of the newly registered almond cultivars was also lower than control cultivars. Aria and Bardia cultivars flowered two weeks earlier than control cultivars. In conclusion, cv. Aria is a suitable commercial almond cultivar for being grown in regions with no of spring frost risk.

Evaluation of the Dickson quality index (DQI) is an efficient but destructive and time-consuming method for prediction of the quality of different seedlings. Fast and low-cost prediction of the quality and vigor of fruit tree seedlings at harvest time using DQI which has shown to be highly correlated with morphological characteristics, is necessary. In this study, grafted sour cherry and sweet cherry bare-root seedlings of 17 commercial cultivars with three replications from 10 nurseries in four provinces in Iran were harvested during the transplanting seasons of 2020 and 2021. The seedlings were selected from two types of certified and non-certified grafted sour cherry and sweet cherry on the seedling and clonal rootstocks, respectively. Seedling height, diameter above grafting line (DAGL), root length, number of roots and branches, fresh and dry weight, height to diameter ratio, and DQI were assessed, and simple correlation coefficients between them were calculated. Path analysis method employed to estimate direct and indirect effects of variables. The results showed that the average DQI for non-certified seedlings was 15.6. The higher values of DQI were observed in areas with more than 3400 accumulated growing degree-days. For certified seedlings, DQI decreased to 12 which is likely to be the effect of using SL64 semi-dwarf rootstock. Based on the results of the path analysis for DQI, the highest direct effect was related to DAGL. DAGL was determined as the most efficient morphological characteristic for characterization of quality categories of grafted sour cherry and sweet cherry seedlings due mainly to its highest correlation with the DQI and most of the other morphological characteristics.

 Balanced and fair availability of human resources, equipment, and services is a necessary condition in the health and treatment sector in different geographical areas to increase the level of human health, which will lead to the creation of a healthy society. On the other hand, the insufficient and unequal distribution of health services and facilities imposes high financial costs on societies, the continuation of which will cause backwardness and decrease the growth rate of the societies. Therefore, this research aims to evaluate the status and ranking of Ardabil province's cities regarding access to healthcare services and infrastructure.

This descriptive-analytical study is designed with practical purpose. The present study is descriptive-analytical in nature and applied in purpose. The required data from the statistical yearbook of 2016 was extracted. Ten questionnaires were completed by experts working in the medical centers of the province for determining the priority using the bullets and the snow sampling method. In this study, the entropy model, Kopras model, and cluster analysis method were used to weigh the indicators, rank, and level of the cities respectively using SPSS. In addition, ArcGIS software has been used to show the status of the cities.

The final results of the Kopras model indicate that the highest levels of access to healthcare services and infrastructure among the cities of Ardabil province are respectively Ardabil, Meshgin Shahr, Khalkhal, Moghan, Nemin, Pars Abad, Beile Sawar, Nair, Kausar and Sareen. And the cities of Ardabil province are located in the cluster of three developing clusters, relatively deprived of development and deprived of development.

Ardabil province is lower than the national average in terms of access to healthcare services and infrastructure, or in a relatively deprived state in terms of development. The difference in the level of enjoyment of the cities of the province also shows the lack of justice in the distribution of health and treatment indicators.

Decreased bone density, especially in women, is a health risk factor; therefore, the aim of the present study was to investigate the effect of a resistance training course with vitamin D supplementation on bone absorption markers in girls.

The participants of the present semi experimental study were 24 non-athlete girls in Boroujerd (mean age 21.6 ± 2.04 years, mean height 155 ± 5.5 cm and average weight 64.13 64 4.9 kg) who participated voluntarily and were randomly divided into four groups of six (resistance training, vitamin D intake, resistance training with vitamin D intake and control group). Resistance training consisting of eight weeks (three one-hour sessions per week) was performed in accordance with the principle of overload. The participants were given Vitamin D supplementation for eight weeks (once a week) using vitamin D tablets (8 pearl IU50000) with 300 ml of water. Blood samples were taken 48 hours before the beginning of the protocol and 48 hours after the end of the last session to measure the serum concentrations of parathyroid hormone and calcitonin. ANCOVA and Bonferroni post hoc test were used to analyze the hypotheses.

The results indicated that after eight weeks of resistance training, as well as eight weeks of resistance training with vitamin D, a significant increase in serum calcitonin concentration (p=0.001) and a decrease in serum parathyroid hormone concentration (p=0.001) Occurred.

It seems that resistance activity and vitamin D consumption increases calcitonin and decreases Parathormone in sedentary girls, which probably has a positive effect on bone mass.

Apricot (Prunus armeniaca L.) as an important fruit crop belongs to the Amygdaloideae in the Rosacea family and is grown in regions with Mediterranean climates in the world. Apricot species were classified into six eco-geographical groups including: Central Asian, East Chinese, North Chinese, Dzhungar-Zailij, Irano-Caucasian and European. Iranian genotypes which belong to the Irano-Caucasian group are mostly self-incompatible with low chill requirement. The high level of genetic diversity in Iranian apricots is due to sexual reproduction by seeds during the years. In Iran, many of apricot local varieties have been relocated between provinces and subsequently, in some cases their names, have been changed over the years. Hence, to determine the genetically different cultivars and detection of synonyms, screening of apricot germplasm seems necessary in Iran.

Thirty eight commercial genotypes of apricot with five biological replications were collected from 14 nurseries in West Azarbaijan, East Azarbaijan, Esfahan, Semnan, Alborz, and Tehran Provinces in Iran. Additionally Orang Red apricot (Porteghali) included in the study as an outgroup sample. Also DNA sample of previously registered apricots in national list were used in this study. Young and healthy leaves of each cultivar were sampled and stored at -70 °C. Samples were powdered using mortar and pestle in presence of liquid nitrogen. CTAB extraction buffer was used for nucleic acid extraction. Quantity and quality of extracted DNA were measured by spectrophotometry and agarose gel electrophoresis.Thermal cycles were done in Eppendorf thermocycler and the cycling program were set on one cycle of 94°C for 4 minute, 30 cycles of  94°C for 30 seconds, annealing temperature of each primer for 30 seconds and 72°C for 30 seconds followed by one cycle of 72°C for 5 minutes. PCR products were resolved on 10% polyacrylamide gels in 1x TBE buffer. GelRed (Biotium) was applied for gel staining and amplified bands were revealed by UV (300 nm). Eight SSR markers which showed more diversity were selected and scored. Polymorphic alleles were scored as one for presence and zero for absence. For detection of off types, samples were classified by Paired Group method and Euclidean algorithm in PAST software. Then the data of off-types were removed from the dataset and samples were reclassified by the method. Principal Coordinate Analysis (PCoA) was carried out using PAST software. Genetic diversity indices were evaluated in Popgene 32 software.   

Eight SSR loci produced 124 alleles with the average 15.5 allele per locus. Nei’s gene diversity and Shannon’s information index were 0.32 and 0.48, respectively which showed high level of diversity in this collection. Distance matrix based on Nei’s gene diversity showed that the most genetic distance (0.74) was between Askar Abadi and Zodras, Mahali Goushti Zodras and Nasiri cultivars. Clustering of samples indicated that some samples including 19 (Shahroudi), 59 (Nakhjavan), 107 (Shahroudi), 127 (Soltani), 137 (Ghavami), 144 (Tabraze) and 156 (Daneshkade) were off-types.For identification of synonyms the off-type samples were disregarded. Cluster analysis illustrated that some local cultivars with different names had same genetic backgrounds. Thus, the names of these samples should be unified in the germplasm. Depicted graph based on first and second coordinates in PCoA demonstrated that the 38 collected groups of apricots are genetically 26 distinct cultivars and there are some duplicates in the germplasm. Results showed that three loci including UDP98-021, UDP98-409 and UDP98-411 were able to distinguish all 26 genotypes. To check the genetic identity of saplings with the same name, some cultivars including Jahangiri, Askar Abadi, Shamlou, Saltanati, Shahroudi, Shams, Tabarze and Rajab Ali were collected from two different nurseries. Surprisingly, the results showed that Nasiri, Tabraze and Shahroudi which were sampled twice from distinct nurseries and provinces, despite of identical names, had different genetic backgrounds.

Detected off-types among five biological replications of local varieties propagated asexually by nurseries showed that there was not sufficient attention in the selection of propagating material in the nurseries. In this context, establishment of foundation blocks by public sector and mother orchards by private sector of economy from Iranian apricot local varieties can be an effective solution so that nursery operators can provide certified propagating material for production of certified nursery stocks. Moreover, seed and plant certification and registration institute should made inspection and testing procedures in mother orchards and nurseries to ensure that propagated trees are healthy, genetically uniform and original.

Plasma electrolytic oxidation is a novel and promising method for coating the light alloys especially magnesium alloys. Several parameters affect the coating quality and its properties, where in this study; the effects of frequency on properties of coatings produced by PEO on AZ31 Mg alloy were investigated. The coating process was performed in a silicate-based electrolyte containing KF and K2TiF6 using a soft-sparking waveforms with 30 % cathodic pulse width at 1, 2, and 3 kHz. The surface morphology of the coatings was a net-like (scaffold) containing a micro-pores network, micro-cracks, and granules of oxide compounds, in which, no noticeable change on coating morphology occurred with increasing the frequency. Also, the coatings were composed of MgO, MgF2, Mg2SiO4, SiO2 (amorphous), and TiO2 (crystalline and amorphous) phases contributed by the elements from both substrate and electrolyte in the coating process. Based on the cross-sectional images, the thickness of coatings displayed no significant increase with increasing in frequency, but the porosity percentage was increased. Also, the very small pores were presented in the inner layer with increasing frequency. Corrosion behavior of the coatings was evaluated using electrochemical impedance spectroscopy (EIS) in 3.5 wt. % NaCl until 7 days of immersion. The results of the EIS showed that with increasing frequency and porosity, the larger surface of the coating is in contact with the solution, and the presence of porosity in the more compact layer of the coating allowed the access of solution to the substrate, which reduces the barrier performance of the coating.

Object tracking in video streams is one of the issues in machine vision that has many applications. Depending on the type of the object, the number of objects and other inputs used in tracking, object tracking is divided into several different categories. Multi-object tracking in a camera network is one of the most complex types of object tracking. In this type of tracking, the goal of the algorithm is to extract the persistent trace of several objects moving simultaneously in a wide area that is monitored by a network of cameras. This type of tracking is often done in two steps. In the first step, the traces of each object in each camera is called tracklets are extracted. Then, the persistent trace of the objects are obtained by associating the extracted tracklets of all cameras in the monitored wide area. Here, we introduce a novel variational approach based on the deep features to associate the tracklets.

For this purpose a variational model with multiphase level set representation is introduced. The persistent trace of all objects are obtained by optimizing the proposed variational model. The proposed variational model is optimized by employing the Euler-Lagrange equation. CNN and deep learning are used to extract the deep features of appearance and motion of objects. Here, a ResNet50 network that is pre-trained on ImageNet and a transformer neural network which is trained with motion parameters of tracklets such as acceleration and orientation change rate are used for extracting deep features.

The results on the three well-known datasets which are real and a synthesized dataset show that the proposed model takes competitive performance, while using less extra context information of the camera network and objects, compared to the other proposed methods. The evaluations show the quality of the proposed model in solving complex problems using the minimum required initial knowledge.

The multiphase model using deep features presented in this paper provide 9% better results than the multiphase model without deep features based on TCF and FS metrics and 8% better results based on MT metric.  

Characterizing soil infiltration parameters is time consuming and costly. We carried out the current research to predict different parameters of soil infiltration using field/laboratory measured and remotely-sensed data. The investigated parameters included infiltration rates at different time intervals and the parameters of the three well-known infiltration models. We employed soil sampling and field measurements on late spring 2012 and acquired ETM+ data for the correspondent dates. We measured several soil properties as well as infiltration. Then, we developed several pedo-transfer functions (PTFs) from the collected field/laboratory measured and remotely sensed data to predict the intended infiltration parameters. Results showed that field/laboratory measured data were able to predict soil infiltration rates and parameters of the investigated models with reasonably high accuracies (E value up to 0.961). The results also revealed that, although there was no significant and robust relationship between soil surface reflectance and the investigated parameters, the developed PTFs had reasonable accuracies (E value up to 0.634) in estimating the intended infiltration parameters using soil characteristics (moisture content, soil separates, and organic carbon) which are predictable from remotely sensed data.

Alzheimer's disease is the most common form of dementia. KAT2B (Lysine Acetyltransferase 2B) is a mitochondrial protein known as mitochondria clearing control organ by mitophagy. PRDX6 (Peroxiredoxin 6) is a key regulator of mitophagy and plays a critical role in maintaining mitochondrial ROS (Reactive oxygen species) homeostasis. Therefore, the purpose of this study was to investigate the effect of swimming endurance training on expression of PRDX6 and KAT2B genes in male hippocampus model of Wistar rat after induction of Alzheimer's.

In this experimental study, 18 rats were randomly divided into 3 groups including control, Alzheimer's and exercise-Alzheimer's groups. The Alzheimer's model was created by injecting beta 42-1 amyloid into the CA1 hippocampus region, and the training group rats participated in the swimming 30 min/day for a period of 3 weeks. In order to confirm the Alzheimer's model, thioflavin staining was used, and Real Time PCR method was used to determine the expression of the desired genes. One-way ANOVA with Tukey’s post-hoc test was used for data analysis.

There was a significant difference between the amount of beta-amyloid plaques in the two groups of Alzheimer's and control (p<0.001). Alzheimer's disease significantly reduced the expression of PRDX6 and KAT2B genes in the Alzheimer's rats hippocampus (p<0.001), and also following the endurance exercise, the PRDX6 gene expression increased compared with the Alzheimer's group (p=0.027).

Endurance training can possibly maintain oxidative balance and improve mitochondrial hemostasis in Alzheimer's disease.

Indirect measurement of soil electrical conductivity (EC) has become a major data source in spatial/temporal monitoring of soil salinity. However, in many cases, the weak correlation between direct and indirect measurement of EC has reduced the accuracy and performance of the predicted maps. The objective of this research was to estimate soil EC based on a general linear model via using several soil properties. Through calibration equations, the error involved in such model-based data was calculated and employed in mapping soil EC using kriging with measurement errors (KME) method. The results were then compared with those of ordinary kriging (OK) and co-kriging (CK). Soil samples were taken from the depth of 0-20 cm in 78 points with spatial intervals of 500 m from an area of 40 km2, and they were analyzed for their electrical conductivity (EC) and certain other soil properties. Measured soil EC data (hard data) and auxiliary soil data were further used to develop the semi-variance and cross-semi-variance functions; moreover, soil salinity prediction was done on a grid of 100 m with OK and CK methods. Afterwards, the most optimal EC estimation model was developed using auxiliary soil data and GLM. As predicted values always involve uncertainty, the error involved with the predicted values was calculated and then the calibration equations were adjusted. Lastly, soil salinity was predicted using KME method. Results showed that the OK method had the lowest MSE and RMSE values, 0.65 and 0.8 dS m-1, respectively. Furthermore, among the auxiliary data, pH and silt content resulted in some of the best cross-semi-variance functions, among which, silt had a better performance regarding the spatial prediction of soil EC. The GLM model developed with the calculated error and KME resulted in predictions close to those of OK method (with MSE and RMSE of 0.74 and 0.86 dS m-1, respectively). KME method provided the possibility of merging error resulting from the use of soft data, derived from prediction equations; therefore, it successfully improved the spatial prediction of soil electrical conductivity

Tillage operations in swelling soils comprise some difficulties due to the fact that they are sticky during wet periods and hard in dry conditions. Applying soil conditioners is one of the solutions for managing these soils. In this study, a completely randomized (CRD) factorial experiment with two factors including type (Arabic gum and Chitosan) and amounts (zero, 5, and 10 grams per kilogram) of two soil conditioners with three replications was carried out to investigate the effect of these natural biopolymers on the improvement of the physical quality of these soils. Several soil characteristics were examined after three weeks of incubation time. The results showed that the use of Arabic gum and Chitosan increased saturated hydraulic conductivity (Ks) (approximately twice) and wet-aggregate stability (WAS) (approximately 3-4 times). The mean weight dimeter (MWD) index increased around twice as a result of the treatment of soil by Arabic gum and decreased around half due to soil treatment by Chitosan. Regarding soil water storage, Arabic gum retained more water in soil exposing to evaporation force. The swelling volume of the examined soils decreased around half as a result of the application of both above-mentioned biopolymers. Therefore, the above-mentioned biopolymers can be used to treat swelling soils hoping a considerable reduction in their swelling and shrinkage characteristics.

Nitrate reductase enzyme activity can be a good indicator for nitrate uptake in the presence of chloride and plant tolerance to salinity. Gene expression programming is a mathematical model between input and output variables and has the ability of choosing the effective parameters in the model. In this study, ions contents of root (chloride, sodium, nitrate and potassium) in two grape genotypes (Gharashani and GhezelUzum) as the effective parameters in the nitrate reductase activity were used in genetic programming model. The results showed that the nitrate absorption was decreased under salinity, also at higher nitrate concentration this reduction was higher in the salt sensitive genotype. It means that in grape the low affinity transport system (LATS) was more sensitive to salinity compared to the high affinity transport system (HATS). In both genotypes, the nitrate reductase activity increased with increasing the nitrate concentration in root medium. Comparing the results obtained using three function set showed that the highest correlation and lowest root mean square error were achieved for training phase by using the default function set, while for the testing phase, the main operators along with the squared root and power gave the better performance accuracy. Also, according to the suggested model, nitrate, chloride, sodium and potassium as the selected effective variables contribute with a decreasing order in the nitrate reductase activity respectively.

In this paper, we associate to each natural number n a digraph Γ(n) whose set of vertices is H = {0, 1, · · · , n − 1} and for which there is a directed edge from a ∈ H to b ∈ H if a5 ≡ b (mod n). We determine the number of the fixed points of Γ(n). We also give the structure of Γ(n) for n = 2k and n = 5k, where k is a natural number. Making use of the Carmichael’s Theorem, we present a simple condition for the existence of cycles in Γ(n). Let Γ1(n) be the subdigraph induced by the vertices which are coprime to n. We discuss when Γ1(n) is regular or semiregular.

Investigate variation of groundwater resource is very important in planning and sustainable management of water resource in each region. Quantitative and qualitative properties of ground water are changed in spatial and temporal scales; therefore it con not presumed fixed these properties. The goal of this study was investigate temporal and spatial variation ground water level in Kermanshah plain in annual، season and month in a 20 years period from 1991 to 2011 by using groundwater data of 61 piezometric wells. After was controlling of quality، accuracy and normality of data and Reconstruction of the statistical deficiencies، we used Kriging interpolation method for zoning variation of annual، season، and month، As well as Thiesson Polygon Method was used for variation of average height of piezometric level in Kermanshah plain. The diagram of height variation of piezometric level in each wells showed that preference of interpolation method compare to Thiesson Polygon Method. Assessment of results showed that average height of table groundwater during statistical period was felled 9. 9 meter (0. 49m in year)، whereas fall variation in some of wells showed fall is upper 30m.

Metal cutting can be associated with high heat generation in the tool-chip interface zone and hence، the thermal aspects of the cutting process strongly affect the accuracy of the ultra precision machining. This study presents the effect of tool edge radius and cutting speed on heat generation and balance of energy in nanomachining process using three dimensional molecular dynamics simulation with Embedded Atom Method (EAM) metal potential energy. Results show whenever tool scratches the work material، atoms velocity of surface layers is increased dramatically، which influence kinetic energy and workpiece temperature. By increasing cutting speed to 400%، cutting forces are increased between 21-27%. Although tool forces is not increased considerably by cutting speed، a big fraction of potential energy، kinetic energy and heat transfer are remained in workpiece. So، workpiece temperature and temperature gradient is increased dramatically. Increasing cutting speed form 50 m/s to 200 m/s affect on temperature increment near machined surface from 300 C to 700 C which can affect the surface roughness. In addition، tool edge radius increases in contact area between tool and workpiece when tool forc is increased especially in trust direction. Consequently، temperature gradient is raised locally in chip formation area by tool edge radius.

Field experiment was carried out at the Ferdowsi University research field, Mashhad, Iran during 2006-2007, to determine how much effective the N-fertilization is, to find out the most suitable plant density which could be used in chamomile (Matricaria chamomilla L. Asteraceae) to increase the yield of anthodium flowers and content of essential oil. The experimental design was as two factor factorial completely randomized block design having four plant densities (D1=20pl/m2, D2=25pl/m2, D3=40pl/m2 and D4=50pl/m2) as first factor and three levels of Urea™ fertilizer (%46) (N0=0g/m2, N1=10g/m2 and N2=20g/m2) as second factor, replicated thrice. During the flowering period, growth indexes such as plant height, anthodia diameter, dry flower yield, essential oil content and chamazolene were measured. The results indicate that plant density and urea do not have a significant effect on morphological characters. Plant density had significant effect on dry flower yield and essential oil yield. So, maximum yield of dry flower and oil were obtained at 50 pl/m2. In the other hand, the increasing of Urea up to 20g/m2 caused dry flower yield, essential oil content and yield and chamazolene content to be increased significantly. The significant interaction between plant density and Urea levels had been recorded in the case of yield of dry flower and essential oil of Bodegold.