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The agricultural sector is one of the most basic and vital component in the social and economic structures of any country. Today, with increasing in the world's population and needing to provide food on the other hand, and increasing in the price fluctuations of agricultural products on the other hand, traditional agriculture is no longer responsible for the sustainable food security of the world population. In recent years, the occurrence of two incidents of the spread of the corona virus and the outbreak of war in Ukraine, have made the price of agricultural products extremely unstable. Today, even many farmers and agricultural associations in developing countries are not aware of the changes in market prices and the latest technological developments in the field of agricultural product prices, and they do not have the ability to discover the optimal price for selling their products. In such a situation, the use of intelligent models in order to accurately forecast the price of agricultural goods is vitally important for farmers and agricultural sector activists. Smart agriculture is an emerging concept that involves the integration of advanced technologies to collect and analyze data in order to solve the challenges and problems of the agricultural sector. In the meantime, forecasting the price of agricultural products involves with some basic challenges; including: 1) Data of agricultural product price is mostly non-linear, unstable, non-normal, and noisy and follows chaotic behavior, 2) There is uncertainty in the forecasted data obtained from different models, 3) In the studies related to price forecasting, the "publishable base model" is not provided in order to provide the forecasted price values. Therefore, the aim of this study is to provide a non-linear hybrid intelligent model for accurate forecasting of the future price of pistachios in the field of smart agriculture through managing the multidimensional nature of data, considering uncertainty in the forecasting data and finally building a publishable base model in the field of product price prediction. The hybrid model proposed in this study has the following innovations; 1) the deep learning neural network model and the Auto-Encoder network have been used to forecast the agricultural product price and determine the optimal lag of price as an input variable simultaneously, 2) The Monte Carlo method has been used as a nonparametric method to provide a confidence interval and calculate the most likely price that can happen, 3) The practical application of price forecasting models, i.e., "publishable base model" is presented in order to provide forecasted price values. Materials and Methods The implementation of the proposed hybrid model in this study includes the steps of "data preparation", "data feature engineering", "training and testing the final deep learning neural network model", "building the optimal base model", "creating the most likely price scenarios" using the Monte Carlo method and "inferring new prices or making out-of-sample forecasting" with new data sets" by feeding new price data into the deep learning neural network model. In the proposed hybrid model, data mining techniques are used, including Wavelet Transform (WT), Long-Short Term Memory (LSTM), Auto-Encoder network (AE), Monte Carlo-Markov chain (MCMC) simulation method and the concept of "inferring new prices". In the data preparation stage, using methods such as data smoothing, data rebuilding, correction of duplicate data in several consecutive days, and correction of missing data, the continuous set of pistachio future price time series is prepared to enter the primary model. Also, the wavelet transform function has been used for de-noising the data, the Auto-Encoder network has been used to determine the optimal lag, the Monte Carlo-Markov chain simulation has been used to create the most probable price scenarios, and the deployment concept has been used for out-of-sample forecasting with new data sets. The data used in this study is the time series of the daily price of pistachio futures on the Iran Commodity Exchange in the period from 10/13/2019 to 12/14/2021 in Rials per kilogram. Results and Discussion The results of this study showed that 1) by using the wavelet theory to de-noise the data, the error rate of the price data was reduced and the data had a stable trend, 2) the results of the implementation of the Auto-Encoder network showed that the optimal lag of one can be used as an input variable to forecast the future price of pistachios, 3) The outcomes derived from employing Monte Carlo-Markov chain simulation, coupled with out-ofsample forecasting using the new dataset, reveal compelling insights into the future pricing of pistachios on the Iranian Commodity Exchange. According to the analysis, the most probable and sanguine projection places the future price at the price ceiling of 213 thousand Tomans. Impressively, the forecasted price exhibits a minimal variance of merely 0.7% from the actual observed price, attesting to the precision of the proposed model. The overall accuracy of the model stands commendably high at approximately 93%. Conclusion Based on the results, firstly, the forecasted price has a small error with the actual price and this small error shows the power of the built model in forecasting the future price trend of pistachios. Secondly, the alignment of the price resulting from the Monte Carlo simulation with the new price can also be used as a confidence index in risk management for traders and market participants. Thirdly, the process set is the most complete value chain in the production of price forecasting models. Therefore, the use of the proposed hybrid model and the use of the components used in it, i.e. wavelet transform function, Auto-Encoder network, deep learning neural network, Monte Carlo simulation and the concept of inferring new prices; are suggested. [ABSTRACT FROM AUTHOR]

In recent years, the fluctuation in agricultural commodity prices in Iran is increased and thus, accurate forecasting of price change is necessary. In this article, a flexible combined method in modeling monthly prices of beef, lamb and chicken from April 2001 to March 2021, was proposed. In this new method, three different approaches namely simple averaging, discounted and shrinkage methods were effectively used to combine the forecasting outputs of three hybrid methods (MLPANN-GA, MLPANN-PSO and MLPANN-ICA) together. In implementation stage of hybrid methods, based on test and error method, the optimal MLPANN structure was found with 3/2/4-6-1 architectures and the controlling parameters are carefully assigned. The results obtained from three hybrid methods indicate that, based on the RMSE statistical index, the MLPANN-ICA method performs the best when forecasting prices for beef, lamb, and chicken. The outputs of three combination approaches show that the shrinkage method, with a parameter value of K=0.25, achieves the highest prediction accuracy when forecasting prices for these three meats. In summary, the proposed method outperforms the other three hybrid methods overall. [ABSTRACT FROM AUTHOR]

Meat is one of the most important sources of animal protein and plays an important role in human nutrition. In addition, meat is one of the main commodities in the basket of Iranian households, so that it included about 20% of food costs in Iran. In recent years, fluctuations in meat prices have always been one of the main challenges of the meat market of Iran and every year the imbalance in its market reduces the welfare of consumers and causes damage to producers. In the current situation where the Iran foreign exchange resources are limited and prices of the meat market has many fluctuations, examining the price drivers of meat price in Iran from the perspective of microeconomics and especially the chain of vertical price transmission can be a good guide for policymakers and planners in adopting appropriate policies to control prices and domestic consumption of these products. The purpose of this study is to identify the drivers of the price of meat different types in Iran using the Panel-SVAR model in 30 provinces of the country during the years 2006-2019. Materials and Methods We use the panel SVAR methodology developed by Pedroni (2013) to analyze the implications of shocks on the price of meat types. Defining z𝑖t ≡ (y𝑖𝑡, x𝑖𝑡, s𝑖𝑡, m𝑖𝑡)′, the heterogeneous panel SVAR model can be formulated as: 𝐵𝑖 z𝑖𝑡 = 𝐴𝑖 (𝐿) z𝑖𝑡-1 +, 𝑖 = 1,..., 𝑡 = 1,. .., 𝑇 and 𝑢it ∼ (0,Σ𝑖) Where 𝐵𝑖 is the matrix of structural parameters, reflecting the instantaneous relations among model variables, 𝑧𝑖𝑡 is the vector of endogenous variables, (𝐿) is a polynomial of lagged coefficients for ith province. 𝑢𝑖𝑡 ≡ (𝑢𝑦𝑖𝑡, 𝑢x𝑖𝑡, 𝑢s𝑖𝑡, 𝑢m𝑖𝑡)′ is the vector of the structural shocks or innovations in 𝑧𝑖𝑡, the variance-covariance matrix Σ𝑖 is diagonal. Assuming 𝐵𝑖 be an invertible matrix, pre-multiply both sides of Equation (1) by 𝐵𝑖 -1, we get the reduced form VAR model: 𝑧it = Π𝑖 (𝐿) 𝑧it-1 + 𝜀it where Π𝑖 (𝐿) = 𝐵𝑖 -1𝐴𝑖 (𝐿), 𝜀𝑖𝑡 = 𝐵𝑖 -1 𝑢𝑖𝑡 and 𝜀it ∼ (0,Ω𝑖) Moreover, the variance-covariance matrix Ω𝑖 of the reduced form error 𝜀𝑖𝑡 = (𝜀𝑦𝑖𝑡, 𝜀x𝑖𝑡, 𝜀s𝑖𝑡, 𝜀m𝑖𝑡)′ is full rank and no diagonal. The reason is that the errors are correlated between equations, implying that the innovations are not orthogonal. Traditionally, when this happens, innovations are correlated with each other and the matrix Ω𝑖 can be orthogonal zed by structural Cholesky decompositions. This method imposes an economic structure and allows the specific ordering of the panel SVAR variables. Finally, the contemporary matrix 𝐵𝑖 is of the following Results and Discussion The results of Pedroni and Cao co-integration test showed that the hypothesis of no co-integration among the variables could not be rejected. The optimal lags length for the Panel-VAR model, using the criterion of Schwartz-Bayesian, was determined as 2. The unit root test of the circle also showed that the estimated Panel-VAR model provides the stability condition. The results of Panel-VAR Granger causality test also showed that there is a direct or indirect causal relationship between all the studied variables. The results of estimating the "matrix of long-term response function in the Panel-SVAR model showed that all estimated coefficients are significant. The results of the Impulse Response Functions (IRFs) showed that the effect of shocks of the value added of the agricultural sector in the agricultural sector on meat price index, mutton price and beef price is negative and on chicken price is positive, while the shocks effect of the price index of imported inputs (corn, soybean meal and barley), livestock prices and meat prices are positive on meat price changes (chicken, sheep and beef). The maximum and minimum effect of these variables occurred between the first to the fifth period and their effect pattern is sinusoidal, afterwards shocks continue to be almost constant (or with low amplitude). This result shows that the effect of shocks of meat price stimuli in Iran is continuous and stable. The results of analysis of variance and historical decompositions also showed that the shocks related to the value added of the agricultural sector have the least effect and the shocks of the meat price variable have the greatest effect on meat price changes in Iran. The results of analysis of variance and historical analysis also showed that the shocks related to the value added variable of the agricultural sector have the least effect and the shocks of the meat price variable itself have the greatest effect on variation of meat prices in Iran. This result indicates that the impact of agricultural shocks on the meat price of is relatively weak, in contrast, the impact of shocks of the price transmission especially in the short term (beginning of periods) play a vital role. Conclusion In this study, impulses effect of four variables of the value added of agricultural sector, price index of imported inputs (corn, barley and soybean meal) and livestock price (live chicken, live sheep, live calf) was examined in four channels (equation) of price including meat price index (Total meat market), chicken, mutton and beef using the Panel-SVAR model in 30 provinces during the years 2006-2019. The findings of this study showed that the most important cause of price fluctuations in the Iran meat market is due to shocks to the vertical price transmission channel, especially in the short term. Therefore, preventing from price shocks in the Iran meat market will be one of the most important tools to create efficiency in the market of this product. Managing inflation expectations is a good way to reduce the price of meat in Iran. In addition, the use of appropriate protectionist policies throughout the meat production, distribution and consumption chain, such as monitoring the production, distribution and consumption stages; modify market structure instead of price control; timely provision of production inputs for producers; development of livestock inputs in the country; providing the supply of meat in the stock market; adequate and timely distribution to consumers; cash payments are offered to households and meat producers in the event of price shocks and explosions, is suggested. [ABSTRACT FROM AUTHOR]

Curtailment of the production of wind resources due to uncertainty can affect the expansion of the transmission networks. The issue that needs to be addressed is how to expand the transmission network, which is accompanied by increasing wind energy utilization. In this paper, a new framework is proposed to solve the transmission expansion planning (TEP) problem in the presence of wind farms, considering wind curtailment cost. The proposed model is a risk-constrained stochastic bi-level problem that, the difference between the expected social welfare and investment cost is maximized at the upper level where optimal decisions on expansion plans are adopted by the independent system operator (ISO). To make the best use of wind generation resources, a new term called wind power curtailment cost is added to the upper level. Also, the risk index is included in expansion decisions. The market-clearing is considered at the lower level, aiming at maximizing social welfare. Uncertainties relating to wind power and the forecasted demand are modeled by sets of scenarios. Using duality theory, the proposed framework is modeled as mixed-integer linear programming (MILP) problem. The model is examined using the classical Garver's six-bus test system and the IEEE 24-bus reliability test system (RTS). The results show that by considering the wind curtailment cost, the transmission network is expanded in a way that increases the wind energy utilization factor from 92.05% to 95.17%. [ABSTRACT FROM AUTHOR]

A new species of Paurodontoides , P. siddiqii n. sp., is described and illustrated based on its morphological, morphometric, and molecular characters. The new species is characterized by a female 550–729 μm long, lip region continuous with body contour, stylet length 7.0–8.0 μm long or c. 1.0–1.2 times the lip region diameter, lateral fields with four smooth incisures, excretory pore at 85–125 μm from anterior end located at the base of the pharyngeal bulb or posterior to it, basal pharyngeal bulb with a short posterior extension projecting into the intestine, monodelphic–prodelphic reproductive system with prominent 19–22 μm long post-uterine sac, and elongate conoid tail with a filiform terminus. The new species is compared with two known species of the genus. It differs from the type species of the genus, P. linfordi, by having slightly shorter stylet, lateral field with smooth incisures, different position of the excretory pore, and absence of male. Compared to P. latus , the new species has a shorter body, shorter stylet, different position of the excretory pore, female tail shape and absence of male. The new species was also compared with close species of the genus Paurodontus because of lateral field marked with four lines, asymmetrical stylet knobs and absence of male. Molecular phylogenetic studies of the new species using partial sequences of 18S rDNA revealed that it forms a clade with a species of the genus Ficotylus. In phylogenetic analyses using partial sequences of the 28S rDNA D2-D3 domain, the new species formed a monophyletic group with a species of the genus Veleshkinema and Sphaerularia spp. (Sphaerulariinae). [ABSTRACT FROM AUTHOR]

Vicia (V.) ervilia, commonly termed as bitter vetch, produces grains belonging to legumes family. One of the factors limiting the usage of V. ervilia is the existence of large amounts of anti-nutritional factors in the grains thereof. Considering the importance of the anti-nutritional factors, the present study investigated the effect of different methods of soaking from V. ervilia grains on the reduction of antinutritional factors rates. All of the soaking methods were found considerably reducing the anti-nutritional factors rates in all treatments as compared to V. ervilia grain flour. It was also found out in the present study that alkaline treatment, provides for the highest reduction of hydrolysable and dense tannin, phenolic ingredients in contrast to the other methods. Moreover, considerable increase in canavanine ooze-out from V. ervilia was documented for aqueous and saline treatments. Among different treatments, the highest reduction in total phenolic compounds and tannins was observed in alkaline maceration, followed by acidic, aqueous and salt saline. Also the lowest amount of canavanine was observed in aqueous treatment and the highest amount in alkaline treatment. The results show that treatment method can be selected depending on the type of need to remove anti-nutritional compounds of V. ervilia seeds. So soaking in water and use of saline solutions is preferred to soaking in basic and acidic solutions for the latter damages to some nutrients under basic and acidic conditions. [ABSTRACT FROM AUTHOR]

A new species belonging to the genus Belondira is described from natural areas in Iran. Belondira coomansi n. sp. is characterized by its general size, the dimensions and appearance of its lip region, presence of distinct labial and post-labial sclerotization, the length of the odontostyle and its inconspicuous lumen and aperture, the length of the neck and its pharyngeal expansion, the reduction of the female anterior genital branch to a simple uterine sac, a very short posterior uterus, the anterior position of the vulva, the length and shape of the caudal region with distinctly thick cuticle at its tip, the length of the spicules, and the presence of only one pair of ventromedian supplements. The new species is close to Belondira brevibulba, B. sacchari , B. tenuidens and B. thornei , and it is compared to them. Molecular characterization (D2–D3 expansion segments of the rRNA large subunit) of the new species is also provided, representing only the second species of this genus for which any DNA sequence data are available. [ABSTRACT FROM AUTHOR]

Bursaphelenchus willibaldi, associated with trees in two separate locations in forests of northern Iran, are characterized and illustrated based on morphological, morphometric and molecular data. The Iranian population of B. willibaldi has a body length of 392-595 μm, stylet length of 12-14 μm, c-index of 9.0-14.5 and PUS length of 51-82 μm. Males have spicules 15-18 μm long along the arch line. The Iranian population showed morphometric variations compared with the originally described samples. For example, it has a shorter body in females and males, greater c-index, slightly greater range of V, slightly smaller range of PUS and tail length. Molecular phylogenetic analysis of the recovered populations revealed both sequenced isolates forming a clade with one European isolate of the species using Bayesian inference ( BI) analysis with full Bayesian posterior probability ( BPP). [ABSTRACT FROM AUTHOR]

In this paper, the bandwidth of one SIW rat-race (hybrid ring) coupler has been increased up to 30% by four U-shape slot-coupled transitions without disadvantages due to transmission line loss, radiation and design complexity. The SIW coupler structure has been analyzed by the mode matching method that uses the cylindrical vector expansion to minimize computational time and memory occupation. Throughout 11-15 GHz bandwidth, return loss and isolation as well as phase differences in output ports have been presented. It is observed that the numerical results are in good agreement with simulation and experimental measurement. [ABSTRACT FROM AUTHOR]

The article presents a case study on the success of women only parks from the point of view of the citizens in Tabriz Metropolis in Iran. Topics discussed include the motivations for going to the special parks, the successful and unsuccessful factors from women's point of view, and the effects or benefits of visiting women only parks.

A new species of the genus Paurodontella, P. composticola n. sp., collected from Nazar Abad City, Alborz Province, Iran, is described and illustrated. The new species has a body length of 803–1053 μ m (females n = 10) and 620 and 739 μ m (males n = 2). The cuticle is weakly annulated with four lateral lines. Cephalic region is annulated and continuous with body contour. The stylet is 8.0 to 9.0 μ m long with asymmetrical knobs. Esophageal basal bulb is present with a small posterior extension projecting into the intestine. Excretory pore is situated at the level of esophageal basal bulb region. Post-uterine sac is 5 to 8 μ m long and uterus is without diverticulum. Tails of both sexes are similar, short and sub-cylindrical. Males have 24 to 25 μ m long bursa leptoderan and spicules 24 or 25 µm long. A non-branching oviduct is present to form a uterine diverticulum; the new species is closely related to five known species of the genus, namely P. asymmetrica, P. balochistanica, P. densa, P. iranica and P. niger. It most closely resembles P. iranica, but differs from it morphologically by a shorter stem-like extension projecting into lumen of intestine and male with sub-cylindrical tail vs conoid. In addition to morphological comparisons, the molecular phylogenetic analyses based on 733 bp of the partial sequence of 28S D2/D3 expansion segments of the large subunit rDNA gene (LSU) revealed this as a new species.

The simultaneous heat and mass transfer by natural convection around a hot body in a rectangular cavity is investigated numerically. The cavity is filled with air and the ratio of body's length to enclosure's length is assumed to be constant at 1/3. The differential equations for continuity, momentum, energy and mass transfer are solved using the Patankar technique. The results are displayed in the form of isotherms, isoconcentrations and streamlines and the effects of Rayleigh number, Lewis number and buoyancy ratio on average Sherwood and Nusselt numbers are investigated. The study covers a wide range of Rayleigh numbers, Lewis numbers, and buoyancy ratios. It is observed that by increasing Lewis number, the average Sherwood number increases and the average Nusselt number decreases. Additionally, by increasing the absolute value of buoyancy ratio, the average Sherwood and Nusselt numbers enhance. This work is a novel one in this field in the light of the geometry and the range of dimensionless numbers. [ABSTRACT FROM AUTHOR]