amir gholami

This research aims to model the effective systematic risks of financial recovery in the insurance industry. This research is a type of applied research. The period of research is 11 years (1400-1390). For this purpose, the information on 14 systematic risks affecting the financial solvency of insurance companies was entered into dynamic, selective, and Bayesian averaging models. Based on the error rate, the Bayesian averaging model had the highest accuracy among the selected models. After estimating the model, 5 economic growth risks, inflation uncertainty, exchange rate, sanctions, and KOF index were selected; Also, based on the results of the TVPFAVAR model, it was assessed that the impact shock of the selected variables in the long-term period is stronger than the short-term period, which indicates that the elasticity of financial prosperity is greater than the changes in systematic risk variables compared to the short-term elasticity. Based on the results of economic growth and the KOF index, the positive effect and uncertainty variables of inflation, exchange rate, and sanctions hurt financial wealth in the general trend.

Virtual power plant planning (VPP) has received much attention in recent years. VPP refers to the integration of multiple power units, considered as a single power plant. In this paper, three VPPs are considered, each consisting of different power plant units and expected to supply the desired load. In addition to providing the desired load, they must maximize their profits. A decentralized optimization method was used to optimize these three VPPs. The reason for using a decentralized approach is to increase network security and eliminate the need for a central computer. However, using decentralized optimization increases the speed of problem solving. Finally, the obtained results are compared with the centralized method. Simulations show that almost the same results are achieved using different optimization methods. These results increase the trend of using decentralized methods in VPP. Another feature of decentralized methods compared to the centralized method is the reduction in the speed of problem solving, which in this article has greatly reduced the solution time. If the considered network becomes wider and the number of problem variables and its limitations increases, the use of decentralized methods will become more efficient, and in those problems, the difference in problem solving time by centralized and decentralized methods will increase.

The normal reference values for the thyroid uptake of radioactive iodine and Tc-99m pertechnetate in euthyroid patients vary by geographical location as well as the amount of iodine intake in the diet. The present study examines the normal reference values for thyroid uptake of Tc-99m pertechnetate in the North of Iran.

The participants of this study were 64 patients (all over 20 years of age) who had referred to the Nuclear Medicine Center of the Shahid Beheshti Hospital for thyroid scan over the period between March 2018 and May 2020. It is worth mentioning that relying on laboratory test results, only patients with normal thyroid function were included in this cross-sectional study.

The median, the 5th and 95th percentiles and thyroid uptake range of 99mTc-pertechnetate in euthyroid patients were 0.9, 0.6 to 1.8% and 0.54 - 1.80%, respectively.

The percentage of uptake in the thyroid gland in each geographical area varies based on race and diet content, so it is necessary to determine the percentage of uptake in each specific region and even check it periodically.

Blockchain technology is a meta-technology that integrates several technologies to form a secure platform for managing transactions . this study determine the effect of using blockchain technology on reducing costs in economic, in the period of 2019-2021. The hypothesis claims that blockchain enables us to reduce controlling, monitoring and enforcement costs. This research benefits from a pluralistic method to study the impact of applying blockchain technology in the field of economy. so, three different methods were used in order to investigate the research hypothesis including theoretical analysis, interview with experts and statistical inference. The findings confirmed the main claim of the hypothesis., the findings indicated that applying blockchain technology results in reduction of controlling, monitoring and enforcement costs. Among the well-surveyed features of the block chain technology, immutability and keeping record automatically by time- stamping reduce controlling, monitoring and enforcement costs more than other features, also confidentiality characteristics provided by encryption has the greatest impact on increasing transaction costs and in the other hand immutability of blockchain has the greatest impact on decreasing transaction costs. Moreover, blockchain can be aligned towards the goals of the resistance economy by bringing new and smart technology into the economy and reducing the costs.

The purpose of this study is a new understanding behaviour and net cash flow forecasting. The data of this research contains the daily trial balance for one year, which has been received from 48 bank branches. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root at three levels of microscopic, mesoscopic and macroscopic have been investigated and the Geometric Brownie model has been approved as the optimal model in microscopic level . The results show that Geometric Brownian Motion model can simulate the net cash flow highly accurate in accordance with the criteria of mean absolute percentage error. also forecasting net cash flow for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90 and 180 day time period accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that according to 8 different prediction accuracy criteria, By increasing the forecast hori-zon, ability of the GBM model in simulation and forecasting the net cash flow de-creases.

One of the main issues in the field of Islamic economics is to identify the role and mechanism of Islamic financial instruments on macroeconomic variables and business cycles. If it is possible to determine how and the extent of this impact based on scientific studies, it is possible to influence the control and guidance of cycles of recession and prosperity through the appropriate use of Islamic financial instruments, and this issue is very important and effective for policy makers in making economic policies and decisions. will be. Based on this, in this research, using the econometric methodology based on dynamic stochastic general equilibrium models, the role of Islamic financial instruments on Iran's business cycles during the period 2001-2021 has been investigated. To estimate the parameters, calibration and first-order vector autoregression model were used, and the effects of economic shocks were investigated through modeling in two cases, including Islamic financial instruments in the model and without Islamic financial instruments. The results of the research show that if Islamic financial instruments are considered, the effects of economic shocks are different from the case of not considering the aforementioned instruments in the model, which indicates the effect of the role of Islamic financial instruments on business cycles in Iran's economy. Also, an important achievement of this research can be considered moving towards an economic system in accordance with Islamic economic principles.

 One of the most important consequences of the sale of building density is urbanization that can influence on environmental pollution and the health of society. By adopting appropriate mechanisms in the field of environmental protection and sustainable urban planning, It can be an important step towards sustainable development. The purpose of this article is to investigate the effect of building density sales on the environment and the health of people in Iran's metropolises.

 The method of this research is descriptive-analytical and the collection of information was done in a library way. The population of this research is the Metropolises of Iran that the annual statement data from 1365 to 1398 were collected from the websites of Central Bank, Statistics Center & World Bank. Then the effect of building density on air pollution and its effect on health sector expenditures were investigated using the method of stepwise regression.

Ethical Considerations:

 In order to organize this research, while observing the authenticity of the texts, honesty and fidelity have been observed.

 The estimation of regression model results showed that the building density index (FB) with a coefficient of 0.5565014 is significant with 2% of air pollution and the emission of CO2 has a significant relationship with the health expenditures with a factor of 8.848257.

 Whatever the building density increases, the costs of the health and treatment sector increase due to the increase of the pollution caused by the reduction of environmental quality. by understanding the importance of the quality of the environment and the health of society, decisions in this area need to be reviewed by the country's policy makers and housing officials in Metropolises of Iran.

We aim to highlight the asymmetric relationship between the current account balance and variables of fundamental macroeconomic and macroeconomic stability in the nonlinear boundary test approach in Iran, for the period 1978-2020. The main focus of this research is on the intertemporal approach to the current account views the current account as the difference between domestic saving and domestic investment and focused on macroeconomic factors that determine these two variables. The primary purpose of this research is to assist in the formulation of appropriate economic policies to minimize any negative effects of the current account deficit on the economy. The nonlinear boundary test approach method is used in this article due to the possibility of long-term nonlinear relationships between the current account deficit and financial balance, inflation rate, KOF index, net foreign assets, real effective exchange rate, total investment, terms of trade and GDP per capita growth. According to the analysis findings, there is a long-term cointegration relationship between variables. It is seen that while there exists long-term asymmetry between the current account deficit, net foreign assets, and financial balance the coefficients themselves are not statistically significant. However, the effect of the real effective exchange rate and the Terms of Trade on the current deficit is statistically significant and substantial. The asymmetric cointegration result confirms, between the current account deficit and the inflation rate, KOF index, total investment, terms of trade, and GDP per capita growth a long-run integration exists.

Block chain technology as a promising innovation in the cyber space brings new opportunities. It serves not only the computer world but also other areas like the economy. The purpose of this study is to determine the effect of using block chain as the backend technology for digital currency on reducing costs in economic transactions, which has done in the period of 2019-2021. The hypothesis of the research claims that block chain enables us to reduce searching and bargaining costs towards resistance economy. This research benefits from a pluralistic method to study the impact of applying block chain technology in the field of economy. In doing so, three different methods were used in order to investigate the research hypothesis including theoretical analysis, interview with 20 experts and statistical inference. the findings indicated that applying block chain technology results in reduction of searching and bargaining costs. block chain immutability and decentralizing characteristic reduce searching and bargaining costs more than other features and the existence of distributed ledger has impact on decreasing both searching and bargaining costs. Moreover, block chain can be aligned towards the goals of the resistance economy by bringing new technology into the economy and reducing the costs.

Balancing the internal and external sectors of the economy is one of the important issues for adopting policies that promote stability and growth. The purpose of this study is to investigate the effects of budget deficit and savings gap on the current account deficit in Iran. In this regard, the validity of the twin deficit hypothesis is reviewed and the validity of the triple deficit hypothesis is evaluated considering the importance and role of private sector savings. To achieve this goal, the Autoregressive Distributed Lags (ARDL) model has been used to evaluate the long-run relationship. To evaluate the short-term dynamics between model variables, the Error Correction Model (ECM) in the period 1978-2018 has been used. The results of our study show that considering the determining role of both budget deficit and savings gap variables with having a completely contradictory behavior in creating external balance in both oil and non-oil economies, the validity of the triple deficit hypothesis is confirmed. The validity of the twin deficit hypothesis is not confirmed in Iran. Finally, the results of this study indicate that the conclusion of the twin deficit hypothesis test in Iran, ignoring the pivotal role of private sector savings and the importance of the savings-investment gap on the current account deficit, is incorrect and invalid.

Our goal in this paper analysis the dynamics of national saving investment relationships between 1978 and 2017 in the economy of Iran to determine the degree of capital mobility. For this purpose, the validity of the Feldstein-Horioka hypothesis was tested by relying on the ARDL Bounds testing approach to co-integration and vector error correction model. The authors interpret the close relationship between national saving and investment in the long run as a reflection of a lack of capital mobility. These results suggest that the Feldstein-Horioka Hypothesis is applicable for the Iran economy in the period analyzed. The analysis of the time series characteristics of the current account balance shows that the current account balance does not have a unit root and the link between Iran's economy and international capital markets is not significant. We observed that trade openness, can't help explain the investment. Our findings for Iran suggest that home bias in the allocation of domestic savings significantly declines when domestic investment is financed by domestic savings alone. Furthermore, the empirical results indicate that the Feldstein-Horioka puzzle does not hold for the Iran economy.

The geopolitical environment can be considered as a network within which there are different actors and actors. In this network, each of the actors has a different role, weight, importance, communication, and ability to influence and act. In such a way I can see a hierarchy of power, influence and influence in it. The geopolitical position of countries plays an important role in generating their power. Iran because of its ancient civilization. Having extensive natural resources; The population has a significant geopolitical centrality. Iran is a country whose power is greatly influenced by its geopolitical position. This study intends to make a comparative study of Iran's geopolitical centrality in the Pahlavi and Islamic Republic governments. The Middle East region, as a geopolitical network, has several sub-networks, and in total, we can name 11 geopolitical sub-networks, the most important of which are the sub-network of Islam, energy, democracy, and the sub-network of resistance.

 The research method in this article is analytical-descriptive. The data and information in this article have been done using the library method and by studying articles, books and documents.

The Middle East is a geopolitical network in which different actors compete for control and influence, and this competition takes place in several subnets. The Middle East Geopolitical Network has eleven geopolitical sub-networks Which include:  Resources, Economy and Energy, Shiism, Islam, Sunni, Arabs, Security, West, Resistance, Terrorism, Democracy, Gulf Cooperation Council Iran, as one of the countries in the Middle East region, has had a different position in these sub-networks in different periods.  In the Pahlavi era, the centrality of Iran was mostly related to the security, western and economic sub-networks but in the period of the Islamic Republic, they changed their nature and took on more ideological aspects. Before the 1979 revolution, Iran was more concentrated on the three networks of the West, security, and the economy. Under the Western network, which existed against the communist regime, and all the countries of the Middle East except Syria, South Yemen, and Iraq were present in this sub-network. Iran was highly centralized due to more advanced modernism than other countries
The security network included Iran and several other countries, including Pakistan, Saudi Arabia, and Turkey in order to counter the influence of communism and to defend the West, they realize that Iran is being considered by the Western powers and is centrally managing this network. The economic sub-network includes the oil countries of the region, in which Iran is the center of energy flow in the Middle East. The occurrence of the Islamic Revolution in February 1978 is the beginning of a new chapter in the contemporary history of Iran and established a republic based on Shiite Islam under the name of the Islamic Republic. This revolution caused many changes in Iran and the region Iran subnets in this period include Shiite subnets, democracy, and resistance. The Shiite sub-network includes Iran, Iraq, Bahrain, and Lebanon, with Iran as a key player, as opposed to the Saudi-led Sunni network. The geopolitical subnet of democracy also includes countries with democratic governments, including the United States and the West, Turkey, Iran, Lebanon, Iraq, and Israel. There is a fundamental contradiction in this subnet, and that is the presence of the West and Iran together. Iran is not very central in this sub-network. Iran argues for religious democracy in the face of the Western model of democracy. Religious democracy is influenced by the form of government of the Islamic Republic and is based on the two foundations of republic and Islam. Resistance-based subnets include Iraq, Syria, Hezbollah, Lebanon, Ansar al-Yamin, Hamas . These sub-networks have been formed in opposition to the West and seek to confront the West and allied countries with the West, especially Israel.

The Middle East is one of the most challenging regions in the world today due to its strategic location and the abundance of vital resources and the intervention of great powers. As a result, most countries and their governments are in crisis or are looking for weapons and ammunition for fear of war.  Iran, as one of the most important countries in the Middle East, is no exception to this rule. This article comparatively examines the geopolitical centrality of Iran in the two Pahlavi and Islamic Republic periods. Based on the findings of this study, the influential factor in Iran's geopolitical subnets in the Pahlavi period (West, security and economy) has been the West. In 1978, the Islamic Revolution of Iran led by Imam Khomeini won and the Islamic Republic of Iran became a country that did not belong to any of the ideologies of communism and capitalism and established its government based on the religion of Islam.  The victory of the Islamic Revolution causes a change in the geopolitical sub-networks of Iran in comparison with the Pahlavi era and new sub-networks with an ideological nature are formed (democracy, Shiite, resistance).

The degree of international capital mobility is a decisive and vital factor in the economic, political, and social life of countries and low capital mobility is considered as a concern for them. Capital mobility among countries has always been the focus of many policymakers and observers of the international economy. The main issue in this research is to address a new approach in measuring the degree of capital mobility and solving the Feldstein-Horioka (FH) puzzle in the studied countries. The main purpose of this study is to investigate the status of international capital mobility between 10 developing oil-exporting countries in the period 2000-2018 using the dynamic panel data technique. Theoretically in an open economy, saving and investment are more affected by capital flows and global interest rates. Hence, the relationship between these two variables is not expected to be strong in an economy that is open to capital flows. This analysis contradicts the results of the FH study. Their experimental findings in 1980, using cross-sectional analysis, showed that the correlation between savings and investment for the 16 OECD countries during the period 1960-1974 was close to one (between 0.85 and 0.95). They interpreted the value of this coefficient as the reason for the low mobility of capital. This finding was contrary to the expectations of capital mobility in these countries, because, in fact, the degree of integration of these countries in international capital markets has been high. This became known as the FH puzzle and became the source of discussions about the degree of financial integration and the degree of trade openness in the industrialized world. The results of research in many cases indicate that experimental models that do not take into account the degree of financial openness and economic globalization, lead to an upward bias in the savings coefficient. Therefore, our empirical approach includes adding the variables of the degree of trade openness and the Kof index as indicators of traditional and modern globalization, respectively, as well as the interactive effect of the Kof index on the original equation, which has been used for the first time in domestic and foreign studies.  Also, for the first time, by adding new variables on the initial form of the FH equation, a new specification of the initial equation for solving the puzzle in internal studies has been investigated. Given the characteristics of the countries under study that have sufficient financial resources to finance and do not need external resources, the study of international capital mobility for them can be important because it clarifies the role of home bias in accurately estimating international capital flows.The results indicate the elimination of home bias in estimating the relationship between saving and investment and the realization of the relationship between the two variables.

After performing the unit root test on the model variables, through the Leimer test, the H0 hypothesis was rejected for the pooled data model, so we used cross-sectional analysis to estimate panel data for 10 developing oil-exporting countries (Iran, UAE, Oman, Saudi Arabia, Azerbaijan, Ecuador, Kazakhstan, Indonesia, Egypt, and Sudan). Then we used two cointegration techniques called the Pedroni panel-data cointegration test and the Kao panel-data cointegration test to detect the existence of a long-term relationship between variables. Finally, two fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimators were used to estimate the long-run equilibrium parameters in estimating the models. All research variables except the Kof index are extracted from World Bank (WDI) database. KOF Globalization Index statistics are taken from the 2021 time series on the website of the Swiss  Economic Institute.

As expected, the Kof variable has a significant positive coefficient in determining the investment ratio. The degree of openness has not helped to explain the investment ratio. The interaction effect of the Kof index with the savings ratio has a significant negative coefficient. The savings ratio variable with a significant (close to one) positive and significant coefficient indicates the importance of the savings ratio coefficient in determining the investment ratio. Under these conditions, domestic investment is made only through domestic savings.

The inclusion of the Kof index, the degree of trade openness, and the interaction of the Kof index in the original FH equation eliminated home bias and made the value of the savings ratio coefficients a reality. Therefore, the very low degree of capital mobility among the studied countries can be conclusively concluded.  In general, our main conclusion is that there is no evidence of the confirmation of the FH conundrum for the selected study countries. The degree of openness of trade as a factor reducing trade friction did not play a role in determining the investment ratio and reducing home bias, while increasing the Kof index as a factor reducing trade and financial friction played a decisive role in determining the investment ratio. The changes made to the FH equation play an important role in solving this important puzzle of the international economy. The degree of trade openness is not the best representative for reducing trade friction. Therefore, the results of our research confirm the introduction of the Kof index as an advanced and modern version of the degree of trade openness for studies on the FH puzzle.

The harmless rule is comprehensiveness and dynamism in the Islamic legal system and has an undeniable effect on Iranian civil laws and has been able to solve many problems and even emerging issues. The objective of this study is to analyze the "Harmless jurisprudential rule" with the investigation the effect of the sale of building density on the environment and individuals of the society.

This research is of theoretical type and descriptive-analytical and library and has been done by referring to documents, books and articles.

Ethical Considerations:

 In order to organize, while observing the authenticity of the texts, honesty and fidelity have been observed.

offering surplus density and selling building density In cities, especially metropolitan areas, which can be studied according to the consequences which have for the environment, society and individuals. by adopting appropriate mechanisms in the field of environmental protection and sustainable urban planning, jurisprudential and Islamic rules can be used to organize this area, and this important issue can be examined in the form of a harmless jurisprudential rule.

By understanding the importance of the quality of the environment and the health of society and with the help of jurisprudential teachings, in the framework of the "harmless rule", the sale of building density can be considering due to these facts of this rule which needs to be reviewed by the country's policymakers and housing officials.

Due to the importance of balancing internal and external of the economy, research on the interaction effects of the budget deficit, savings gap, and current account deficit has always been a major issue for policymakers. The main purpose of this study was to test the validity of the triple deficit hypothesis during the period 1978-2019 in the Iranian economy with the presence of the degree of trade openness for two models of oil trade and without oil trade. In the present paper, by providing a theoretical framework and using the Johansen - Juselius cointegration test method and the error correction mechanism, long-term and short-term relationships of the variables of this research are investigated. The results showed that the long-run relationship among the components of the triple deficit hypothesis is established in the two models of oil trade and without oil trade, but the validity of the triple deficit hypothesis is not confirmed in the short run. Through the Impulse response functions, decisions were made about the interrelationships among the variables, and the results of this method confirmed the validity of the triple deficit hypothesis for the oil trade model and the occurrence of the inverse mechanism for the oil-free trade model. Finally, in the oil trade model, internal and external imbalances reduced trade openness, and in the non-oil trade model, only the savings gap played such a role. This emphasized the key role of the private sector in reducing internal and external imbalances.

Since the liquidity situation is the basis for many people to judge the position of the economic unit, this issue has been considered by stakeholders including creditors and investors.The purpose of this study is a new understanding of cash flow behavior and cash balance forecasting. The statistical population of the present study is the annual cash balance of 48 branches of a certain bank. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root Model at three levels of microscopic, mesoscopic and macroscopic have been investigated and the geometric Brownie model has been approved as the optimal model; Then, using the mentioned optimal model, the cash balance is predicted in different time horizons. The result shows that the strength of the GBM model does not remain constant with increasing the length of the forecast time horizon and with increasing the forecast time horizon, they have different results. The accuracy of the model forecast with the MAPE criterion at the 14-day horizon is at an appropriate level.

Inflation is one of the most important economic problems that imposes a lot of costs on society by disrupting macroeconomic indicators, which are reflected in the reduction of economic growth rate, rising unemployment rate and unequal distribution of income. In addition, high inflation and instability of inflation damage the credibility of macroeconomic policymakers, especially the central bank, and its continuation can lead to acute cases of political instability in countries. At the same time, uncertainties due to high inflation rates increase inflation expectations. Accordingly, solutions to control inflation have been proposed. One of these proposals was the independence of the central bank, which has gained many supporters since the 1980s. With regard to this issue, in this study, the effect of central bank independence and policy targeting on inflation control in the economies of 22 Asian countries was examined using the panel data approach during the period 2019-2010. The results of the study indicate that among the variables studied in the previous period inflation, trade freedom and monetary base have a positive and significant effect on current period inflation. In contrast, central bank independence, initial equilibrium, financial development, and exchange rate regimes have a significant negative impact on the dependent variable, inflation in the current economies of 22 Asian countries.

Bone scintigraphy with 99mTc labeled radiopharmaceuticals is a valuable method in nuclear medicine for assessing the bony structure. In clinical setting, bone scintigraphy is accomplished after the injection of 99mTc labeled diphosphonate complexes into a peripheral vein. Inadvertent intra-arterial injection on the antecubital region may cause a special form of artifacts leading to problems inaccurately interpreting these studies as functional images.

We present a 44-year-old man with history of chest wall pain for bone scintigraphy as part of a work-up for determining the pain source. The patient received an injection of 740MBq 99mTc-methylene diphosphonate (MDP) into a blood vessel at the right forearm. Two hours later, an increased uptake of activity was observed on the right forearm and ulnar half of the wrist-hand in the whole body and spot images. The scan findings were consistent with the anatomical and physiological expectations of the ulnar arterial perfusion range. This case displays that an incidental injection with a 99mTc labeled diphosphonate into the ulnar artery results in a hot ulnar half of the palm and ulnar-sided three digits, because these areas are directly exposed to radiopharmaceutical, therefore more radiopharmaceutical is deposited.

It is important for the physician, and especially for the nuclear medicine technician, to know the specific appearance created in the bone scan due to such an event so that they do not make a diagnostic mistake.

In the conceptual framework of financial accounting, which serves the purposes of financial reporting, special attention has been paid to cash flow. The purpose of this study is a new understanding of cash flow behavior and the creation of a new experimental model. This research is applied in terms of purpose and quantitative in terms of implementation. The statistical population of the present study is the annual cash balance of 48 specific bank branches (due to the confidentiality of information, it is not mentioned). Two hypotheses have been considered in this research: 1) Cash balances has a Stochastic property; 2) The Geometric Brownie model is better than the Arithmetic Brownie, Vasicek, and Modified Square Root models. The results of the test have been confirmed to be random. Also, by comparing the four models using MSE, RMSE and MAE tests, the best estimation model has been selected and the comparison results of the models have confirmed the Geometric Brownie inclination model as a more efficient model.

The term of neural network has evolved to encompass a large class of models and learning methods. They interpret input raw data through a kind of machine perception, labeling or clustering models. They help to group unlabeled data according to similarities among the example inputs, and they classify data when they have a labeled dataset to train on. The neural networks consist of many layers. The layers are made of nodes. A node is just a place where computation happens, loosely patterned on a neuron in the human brain, which fires when it encounters sufficient stimuli. A node combines input from the data with a set of coefficients, or weights, which either amplify or dampen that input, thereby assigning significance to inputs with regard to the task the algorithm is trying to learn. These input-weight products are summed and then the sum is passed through a node’s so-called activation function, to determine whether and to what extent that signal should progress further through the network to affect the ultimate outcome, say, an act of classification. If the signals pass through, the neuron has been “activated.” A node layer is a row of those neuron-like switches that turn on or off as the input is fed through the net. Each layer’s output is simultaneously the subsequent layer’s input, starting from an initial input layer receiving your data. Pairing the model’s adjustable weights with input features is how we assign significance to those features with regard to how the neural network classifies and clusters input. Ensemble methods aim at improving the predictive performance of a given statistical learning or model fitting technique. The general principle of ensemble methods is to construct a linear combination of some model fitting method, instead of using a single fit of the method. Ensemble classifier has two common

Bagging and boosting that they are non-Bayesian procedures. They can be used to improve the accuracy of Classification & Regression Trees. Boosting and bagging are two ensemble models capable of squeezing additional predictive accuracy out of classification algorithms. When using either method, careful tuning of the hyper-parameters should be done to find the best balance of model flexibility, efficiency & predictive improvement. Bagging uses a simple approach that shows up in statistical analyses again and again — improve the estimate of one by combining the estimates of many. Bagging constructs n classification trees using bootstrap sampling of the training data and then combines their predictions to produce a final meta-prediction. In this way, boosting creates successive base classifiers that are told to place greater emphasis on the misclassified samples from the training data. Like bagging, the results from all boosting base classifiers are aggregated to produce a meta-prediction. Compared to bagging, the accuracy of the boosting ensemble improves rapidly with the number of base estimators. Boosting method has many different algorithms that Least Squared Boosting (LSBoost) model was used to improve prediction model in this paper. Discussion of Results &

In the first step, for implementing and evaluating the research’s suggested method, Tabriz bazaar was chosen as the world’s biggest, most important and most complicated covered spaces. As the most important reasons for this choice the large dimensions of this historical bazaar, its complicated structure, presence of a wide range of tradespeople and different occupiers in bazaar, citizens’ and tourists’ referral all year long can be mentioned. Then different information related to Tabriz bazaar’s various passages and buildings including Passage’s length, passage’s width, proportional population density, surface material, presence or absence of ventilation, user’s diversity, distance from nearby streets, roof’s height, temperature and proportional humidity was recorded via field observation. Afterwards training data were collected for neural network. This was done in 86 points with different conditions with the help of a Japanese sensor named Pocket PM2.5 sensor which can evaluate PM2.5 and PM10 pollutants in the range of 0-999 (μg/m^3 ). Collected data for both of the pollutants were classified based on the present standards and place’s conditions in four healthy, medium, warning and dangerous classes and was shown by one to four tags. Given that determining parameters like the number of hidden layers, the number of neurons, the number of replications, the kind of transferring and tutorial functions in neural networks’ utilization is very important and effective, to determine them optimally a code in matlab coding language was used that not only it checks all the feasible functions and the appropriate number for neurons and layers, but also it determines their best amounts. By making multilayer neural network it is possible to predict dispersion in various conditions of pollutants’ amounts. In this paper due to users’ requirement for noticing the pollutant’s class and increasing accuracy the Round operator was used for classificating the results to four classes one to four. Due to the low accuracy of the results, ensemble classifier was used to improve the network. LSBoost model of Ensemble algorithm with the help of 100 boosted decision trees has obtained very appropriate results for this paper’s case study with a learning rate of one (η=1). for performing the neural network in training and network creation phase, data were divided into three sections of train, validation and test data that the way of mean squared error’s convergency and result’s accuracy were evaluated for each of the PM2.5 and PM10 pollutants. Efficient network was choosen by convegency’s speed, performance and accuracy. Due to the implementation the best network for PM2.5 pollutant was determined by two hidden layers (first layer with 9 neurons and transfer function of poslin and second one with 5 neurons and transfer function of tansig) with traincgb’s train data and general accuracy of 97.67% and MSE of 0.385. Also for PM10 pollutant with a hidden layer containing 4 neurons, transfer function of tansig and train function of trainlm with the general accuracy of 97.67% and MSE of 0.2779 was obtained. Traincgb function of Conjugate gradient backprogation with Powell-Beale restarts and trainlm of Levenberg Marquadrat algorithm is a combination of Gauss-Newton and gradient descent which uses the ability of both algorithms and has a high speed in training. It should be noted that in addition to the aforementioned networks, the Ensemble classification algorithm was run on this paper’s data which was resulted to accuracy of 67.44% for PM10 and to accuracy of 68.60% for PM2.5 that indicates the optimality of the compositional approaches used in this study. In other words by using combinational algorithm Ensemble and backpropagation multilayer neural network, the accuracy of results have been improved about 30%. Then based on the collected data in different conditions, the training was done for PM2.5 pollutant with the help of Newff-Ensemble neural network and for PM10 with the help of Feedforward-Ensemble network and prediction was done for other 995 locations of bazaar and PM zoning map was prepared. Based on these maps it is clear that most of the center zones of Tabriz bazaar has appropriate air quality. Some sections of bazaar including bazaarche shotorban, bazaarche yakhchal, chaharsog sadegieh, bazaar dalaleh zan bozorg, raste bazaar sadegieh, karvansarayeh shazdeh bozorg, dalan khan and bazaar jambor ha were in 4th class because of particulate matters and attendance of people who suffer respiratory disorders. Based on collected data for this study and by checking the results of this paper’s proposed model, four criteria Passage’s length, proportional population density, presence of ventilation, user type have been much more effective in increasing particulate matters’ class . So due to the obtained results from this study, areas which are located in dangerous class, effective and serious solutions should be done. For example related to the construction of these areas, modern or classic ventilation systems can be installed to improve the quality of bazaar’s indoor air.

This study was conducted to determine the chemical composition and nutritive value of sunflower residues silage (SRS) and effects of its substitution with alfalfa hay and corn silage on lactation performance, feed intake, nutrient digestibility and some blood parameters of Mohabadi dairy goats. Four experimental diets were formulated to gradually replace alfalfa hay and corn silage with SRS as follows: Control (no inclusion of SRS, group 1) and groups 2 to 4, representing 15, 30 and 45.00% replacement of common forages in the diet with SRS, respectively. Sixteen multiparous dairy goats weighing 60.00 ± 3.00 were divided into two 4 × 4 latin square design. Ensiling was being able to increase crude protein content, reduce neutral detergent fiber and increase acid detergent lignin in sunflower residues. Daily dry matter (DM) intake and DM and organic matter (OM) digestibility decreased with increasing levels of SRS in the diet. The highest and the lowest digestibility coefficients belonged to 30 and 45.00% embedment levels, respectively. Milk yield decreased with increasing levels of SRS and differences were statistically significant compared to the highest substitution level. Milk composition was similar among diets, but daily production of milk decreased in higher substation levels. Statistically significant differences were found in serum low-density lipoproteins (LDL) concentrations between treatments and LDL levels decreased as dietary levels of SRS increased. According to these results, SRS is an acceptable feed for dairy goats and common dietary forages can be replaced up to 30.00% with SRS without negative effects on milk yield and composition.

This paper deals with the subject of leader- follower formation control of unmanned aerial vehicle (UAVs) by PID - fuzzy. This is done to increase the performance of follower in meeting the leader’s instructions on speed and altitude in group-flights as guidance parameters for better maintenance of flight orders and more rapid maneuvers between leader-follower arrangements. For this purpose, the formation method is considered to achieve the required aim for maintaining three parameters of speed, altitude and heading angle according to leader-made changes and relative changes between the leader and follower. The simulation results are taken for 6 degrees of nonlinear freedom for a two-seat group of unmanned aerial vehicle by a body coordinate system. The considered control is for unmanned aerial vehicle with nonlinear inverse dynamic control. According to the results, the improving of the follower speed performance following the leader is observed in appropriate velocity and altitude parameters.

This study describes the preparation, biodistribution of 153Sm-DTPA-SPION after intravenous injection in rats.
The chelator DTPA dianhydride was conjugated to SPION using a small modification of the well-known cyclic anhydride method. Conjugation was done at a 1: 4 (SPION: ccDTPA) molar ratio. Conjugation reaction was purified with magnetic assorting column (MACs) using high gradient magnetic field following incubation, the radio labeled conjugate was checked using RTLC method for labeling and purity checked.
The RTLC showed that labeling yield was above 99% after purification and the compound have good in vitro stabilities until 48 hr post injection in the presence of human serum. The biodistribution of 153Sm-DTPA-SPION in rats showed dramatic uptake in the reticuloendothelial system (RES) and their clearance is so fast in other organs especially in the blood. Biodistribution results show that after 30 min post injection more than 84% of injected activities were taken up by the liver and spleen (about 64% and 20%, respectively).
Due to magnificent uptakes of this radiotracer in the liver and spleen and their fast clearance from other tissues, especially in blood, it is suggested that this radiotracer would be a potential candidate for RES theranostic purposes.

Healthy water, which is vital to humans’ health, is defined as a water that is free from chemicals and pathogens. Healthy water can also be used as a necessary raw material in various key industries including electronics, pharmacology and food industries. Nowadays, the world faces a lot of challenges to respond to the ever-growing demand for healthy water as a fresh water resource.  With the advent of new technologies, there are currently new techniques and achievements in different fields as well as wastewater and industrial wastewater treatment. Nanotechnology enjoys an especial place in understanding and controlling different organic pollutants. Recent treatment technologies have led to new techniques using nanotechnology and porous media which display high capacities in eliminating organic elements from water and wastewater. In this review study we focused on researches on nanomaterials including, removing organics from water using nanoparticles and active coal, transferring metal oxide nanoparticles in saturated porous medium, using zero valent iron nanoparticles to remove chrome from water, removing arsenic from water using zero valent iron on active carbon, effective bromate reduction in water using active carbon granules impregnated with iron nano-hydroxide, nitrate reduction using Fe/Cu nanoparticles, synthesis of porous nanocomposite natural charcoal-magnesium oxide in order to remove phosphate and nitrate from aqueous solution, development and characterization of micro-porous ceramic membrane, Ti3SiC2, to carry out microorganism filtration. The aim of this study was to review methods and chemicals that eliminate organics from liquids such as acids and other similar particles as well as presenting some nano materials applications in eliminating pollutants from water.

A 65 year-old overweight man with a history of prostate cancer was referred to our nuclear medicine department for bone scanning. Anterior projection images showed two small foci of increased radiotracer uptake corresponding to the anterior arcs of the right and left sixth ribs, which were interpreted as suspicious for metastatic involvement. Eight months later the patient was referred for follow-up bone scan. In the follow-up scan, those two foci of abnormal radiotracer activity were outside the limits of the bony structures of the chest. In fact, those foci changed their position and were due to radiotracer uptake by the enlarged breasts of this gentelman (Gynecomastia). Previously, it has been just one report concerning radiotracer uptake in the breasts of a man. Based on our case report, this abnormal finding is not exclusively observed in women and it can be also seen in men who suffer from gynecomastia. Physical examination in these settings can be extremely helpful. Oblique, lateral and SPECT (Single Photon Emission Tomography) views can also confirm the extraskeletal origin of radiotracer uptake.