Iran, due to its geographical location, has low rainfall and is considered a dry land. As a result, different regions of the country grapple with drought. The presence of water management systems, such as aqueducts and reservoirs, in most parts of the country, along with a variety of methods for conserving water for irrigation, may contribute to this claim. Considering that drought is an inherent phenomenon in Iran's climate, people have invented and used numerous methods to combat it and store water. The aim of this study is to monitor and evaluate drought in Iran. In order to realize this goal, precipitation data from synoptic, rain gauge, and climatology stations were extracted over a 51-year period, from 1970 to 2020. The results obtained from examining drought occurrences in five ten-year periods reveal that, with the exception of the third decade (1991 to 2000), drought has prevailed in the majority of Iran's regions compared to other decades. On the other hand, in the recent decades leading to 2020, the intensity of drought occurrences, especially in the Middle Zagros, has intensified, which has consistently been among the regions with the highest rainfall in Iran after the Caspian region. This situation can cause concern in Iran, a country where its agricultural production hub is established along the Zagros mountain range. Moreover, the fluctuating behavior of Iran's droughts, with return periods of 2 to 5 years, has complicated the management strategies for these types of hazards. These conditions appear to have created numerous issues in many areas of Iran, particularly in the agricultural sector of the western provinces, due to the lack of conformity with these types of occurrences.

Introduction: Juvenile Myoclonic Epilepsy (JME) is a generalized epileptic syndrome. Age of onset is usually between 12 to 18 years. JME consists of myoclonic jerks, generalized tonic-clonic seizures (GTCs) and typical absence attacks. EEG shows characteristic changes in JME. Long term video-electroencephalography monitoring (VEM) is a helpful diagnostic procedure in the diagnosis of patient with unclear history or EEG findings. In the current study, we aimed to evaluate the role of VEM in diagnosis of refractory epileptic patients.Materials and Methods: This study is retrospective and descriptive on patients of Epilepsy Monitoring Unit of Razavi Hospital, Mashhad, Iran between March 2011 and March 2012. Telephone interview was scheduled 6-18 months after discharge to evaluate results of VEM on the frequency of seizures, the therapeutic regimes and patients’ quality of life.Results: 24 cases with diagnosis of JME were chosen among 250 patients who were admitted with refractory epilepsy. Fourteen of them were female. The average age of patients was 24 years old and the average duration of the seizure attacks was 12.97 years. The mean frequency of GTCs was 2.76 attacks per month and after VEM and proper treatment, it decreased to 0.27 attacks per month.Conclusion: VEM is a helpful diagnostic procedure for evaluating of refractory JME epileptic patients.

The aim of this study was to develop and validate qualitative and quantitative models to discriminate different types of maize and also estimate biochemical constituents. Spectral data were taken from the central leaf of randomly-chosen plants grown in field trials in 2011 and 2012. Leaf chlorophyll and protein content and stalk protein content were determined in the same plants. Four different Support Vector Machine (SVM) models were generated and validated in this study. In qualitative models, maize type was designated as dependent variable while Full Spectral (FS) data (400-1, 000 nm) and Spectral Indices (SI) data (34 indices/bands) were independent variables. In the two quantitative models (SVMR-FS and SVMR-SI), independent variables were the same, whereas dependent variables were assigned as the quantitatively measured traits. Results showed the qualitative models to be a robust method of classification for distinguishing different maize types, such as High Oil Maize (HOM), High Protein Maize (HPM) and standard (NORMAL) maize genotypes. The SVMC-FS model was superior to SVMC-SI in terms of the genotypic classification of maize plants. Quantitative models with full spectral data gave more robust prediction than the others. The best prediction result (RMSEC=222.4 mg g-1, R2 for Cal=0.739, SEP=213.3 mg g-1; RPD=2.04 and r=0.877) was obtained from the SVMR-FS model developed for chlorophyll content. Indirect estimation models, based on relationships between leaf-based spectral measurements and leaf and stalk protein content, were less satisfactory.

Recently, researchers have shown game simulation as the best way of training. On the other hand, there are various posts in basketball which have different physiological and training demands. Therefore, metabolic changes of backcourt and frontcourt players were investigated during a basketball game. 5 main players of 14 teams that participated in 2017 under 23 years of age, national or premier leagues were selected as the subjects. Players’ saliva samples were collected after 40 minutes of a basketball game (with regard to the FIBA roles) and compared using metabolomics. HMNR was used for metabolomics and MestReNova and Metaboanalyst were applied for data analysis. PCA and PLSDA were used for statistical tests. Results showed that taurine, succinic acid, citric acid and glycerol metabolites were higher in backcourt players and lactate and alanine in frontcourt players. Therefore, it can be concluded that backcourt and frontcourt plays relay more on aerobic and anaerobic pathways repetitively. Also, it seems that active oxygen species production is more in backcourt players.