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Objective: To classify different types of acute leukemia based on cooperative game theory and Shapley value. Materials and Methods: In this study, patients data were collected from Flow Cytometry tests of the Iran Blood Transfusion Organization (IBTO) have been used. 304 different diagnosed samples in 8 classes of acute leukemia were investigated. Samples were initially in numerical format. In the next stage, we transformed them into Boolean format according to the defined threshold. Then, weights were assigned to these samples based on cooperative game theory and Shapley value. In this regard, different samples of acute leukemia were separated and classified (Learning Phase). In the diagnosis phase, using similarity measures, the similarities between new under study and the training samples were assessed and the type of under study leukemia were detected (Diagnosis phase). Results: The accuracy rate of the classification method based on the cooperative game theory for leukemia was 96.3% which indicates that the proposed method has a considerable precision rate to classify the different kind of classes. In order to find the validity and efficiency of the proposed method, the results were compared with neural network, which is one of the useful learning algorithms. The accuracy rate of the classification method based on Radial Basis Function method (RBF) was 91.80%. Conclusion: Considering the data, the proposed method gave very hopeful results for acute leukemia classification. In this regard, it can assist hematologists and physicians in reasonable and accurate diagnosis of the kind of leukemia, to make more suitable decisions.

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Wheat is harvested in a short period of time, but it takes several months to be processed and consumed. So wheat flour needs to be stored in suitable condition to retain its good quality for nutrition and industrial uses. On the other hand, exposure of wheat under improper conditions may deteriorate the quality resulting in high economic losses. In this study accelerated ageing of wheat grains was carried out by increasing moisture content (16, 18 and 20%) and keeping the samples in different temperatures (30, 40 and 50°C) for different periods (2, 5 and 8 days).Samples were then milled and physicochemical properties including moisture content, protein, ash, wet gluten, pH and falling number were determined. Response surface methodology with central composite design was applied to minimize total numbers of experimental runs and to determine the significance of the factors.Results showed that increasing storage temperature and time resulted in increasing protein, falling number and ash, while wet gluten, pH and moisture content decrease. By increasing moisture content, wet gluten, protein, ash and falling number decreased while moisture content and pH increased. Optimization using response surface methodology showed that the optimum condition for accelerated ageing of wheat grain contained 16% moisture content, storage temperature of 40.74°C for 2.57 days.

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There is some evidence on the effects of organic acids on the functional properties of native starches. However, there is little information on such effects on modified starches. The main objective of this study was to determine the effects of L-ascorbic acid (150 mg kg^-1, as the permitted level in bakery products) on functional properties of cross-linked wheat starch. Once the starch was treated with L-ascorbic acid, some spots and cracks appeared on the surface of the starch granules, as observed under a scanning electron microscope. Besides, the water solubility increased while water absorption decreased, but intrinsic viscosity of the samples, as determined by a U-tube viscometer, remained unchanged. Also, gelatinization temperature and enthalpy of gelatinization, measured by differential scanning calorimetery, as well as the hardness and elasticity of the starch gels decreased, while adhesiveness and cohesiveness of the gels remained unaffected. In general, it was concluded that the ascorbic acid had some degradation effect on cross-linked wheat starch molecules that could further affect its functional properties.

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Fresh fig is a highly perishable fruit with a very short storage life. Therefore, drying is the most common method for fig preservation. Changes in water content during storage may lead to undesired physical changes in dried fig which is of great importance in its structure and quality. The objective of this study was to assess the effect of water on the physical properties of dried fig, using glass transition temperature (T_g). T_g, melting temperature (T_m) and the melting enthalpy (ΔH) of dried figs at different moisture contents were measured using differential scanning calorimetry (DSC). DSC thermogram showed that dried fig has a semi-crystalline structure. T_g and T_m decreased while ΔH associated with the melting of the ordered structure increased with increasing moisture content of fig. The results showed that water is a strong plasticizer for dried fig and reduced flesh firmness of fig significantly. Measuring color differences of dried fig at different moisture contents showed that by increasing water, fig flesh became darker significantly. Changes in texture, color and crystallinity of the dried fig as function of moisture were assessed using temperature difference (ΔT) between the fig temperature (T) and T_g. By increasing ΔT, the rate of firmness reduction, ΔE value and the extent of crystallinity increased.

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In this study, 23 local genotypes of sour cherry from collection in Meshkin Dasht-Karaj in terms of physical and chemical characteristics including weight, flesh to core ratio, firmness, total soluble solids, dry matter content, titratable acidity, pH, flavour index, respiration rate, color indices of fruits and juices (L*, b*, a*, Hue and Chroma) and their correlations were examined. The results showed that all genotypes had significant differences (p ≤ 0.05) in terms of the studied characteristics. Based on the correlations in the color indices, a* index alone can be used to evaluate the red color differences of various genotypes. According to the results, genotypes of KB-100, KB-450, and KB-213 with suitable characteristics such as weight (>2.8 g), flesh to core ratio (>8.5), flavour index (>9.5) and acidity (<1.75%) are more suitable for fresh consumption and genotypes of KB-232 and KB-247 with suitable weight (>3.7 g), dry matter content (>15%) and respiration rate (<9000 mg CO₂/kg.hr) are more applicable for processing. Also, genotypes with high acidity (>3%) such as KB-157, KB-121, KB-234, and KB-152 are more suitable for pickling and fruit roll-up processing. Genotypes with high dry matter content (>21%) and intense redness (a*<9 for skin and a*<16 for fruit juice) such as KB-136 and KB-449 are more suitable for the production of powder, dried sour cherries, syrup and nectar. Late harvested genotypes with firmness (>6N) such as KB-343 and KB-353 are also recommended for compote and jam processing, respectively.

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In this study some physical and geometrical properties of 11 superior apricot genotypes were determined. These properties such as respiration rate, fruit dimensions, perimeter, surface area, volume, compact factor, geometric mean diameter, projected area, shape factor, circularity, length to width ratio, length to thickness ratio, and length to mass ratio were measured at harvesting moisture content ranging from 75.19 to 87.67 %. Then the correlation among average values of the attributes was performed and the genotypes were classified using principal component analysis (PCA). The results showed that all the genotypes had significant differences in terms of all the studied attributes (P<0.01). There was a significant and positive correlation between fruit length and weight and fruit length and moisture content. Fruit shape factor and compression factor showed a positive and significant correlation, while these attributes had negative and significant correlations with circularity. This study showed that Iranian apricot genotypes could be discriminated by differences in their geometrical characteristics using principal component analysis. Based on the PCA results, the first two components account for the most of the variation in the data (91%) and five distinct groups were observed. Overall, the results of this study can be beneficial for the design of equipment for harvesting, transportation, separating, packaging, and processing of apricot fruit.