The effect of number of mating on longevity and fecundity of the predatory mite Euseius scutalis Athias-henriot was studied under laboratory conditions (at 25±1 ºC, 60 ± 5 % RH and 16: 8 L:D). Newly emerged adult females (less than 24 h) were held individually in a 9 cm arena. A male (less than 24 h) remained with a female for limited periods of time or continuously. Four treatments were designed: virgin females, single mated females, multiple mated females (female had access to a male every five days), multiple mated females (female had continuous access to a male). Mating was necessary for oviposition. Virgin females lived the longest (25 days). However, no significant differences were found among longevity of mated females (12- 15). Similarly, no significant differences were detected among fecundity of females with different numbers of mating (18- 22 eggs). Sex ratio was significantly female-biased in progeny of single mated females and multiple mated females with periodic access to male. However, no significant difference was found in sex ratio of progeny of multiple mated females with continuous access to male.

In traditional speech processing, feature extraction and classification were conducted as separate steps. The advent of deep neural networks has enabled methods that simultaneously model the relationship between acoustic and phonetic characteristics of speech while classifying it directly from the raw waveform. The first convolutional layer in these networks acts as a filter bank. To enhance interpretability and reduce the number of parameters, researchers have explored the use of parametric filters, with the SincNet architecture being a notable advancement. In SincNet's initial convolutional layer, rectangular bandpass filters are learned instead of fully trainable filters. This approach allows for modeling with fewer parameters, thereby improving the network's convergence speed and accuracy. Analyzing the learned filter bank also provides valuable insights into the model's performance. The reduction in parameters, along with increased accuracy and interpretability, has led to the adoption of various parametric filters and deep architectures across diverse speech processing applications. This paper introduces different types of parametric filters and discusses their integration into various deep architectures. Additionally, it examines the specific applications in speech processing where these filters have proven effective.

Recognition and understanding the genetic control of traits, combining ability and genetic structure are directly related to the success of breeding programs. For this purpose, a 7 × 7 one-way diallel design was conducted in a randomized complete block design with three replications. The measured traits were included plant height, height to the first capsule, number of days to 50% and 90% of flowering, number of capsules per plant, number of seeds per capsule, number of days to physiological ripening, number of branches, leaves number and length, 1000-seeds weight, capsule weight, length and width, chlorophyll a, b and total chlorophyll, biological andeconomic yields, harvest index, oil and protein percentage. Analysis of variance showed that there was a significant difference between genotypes and diallel analysis showed that the additive variance of all traits and dominant variance of all traits except height to the first fruit-bearing capsule were significant. The oltan cultivar was the best and Ardestan genotype was the worst genotype in terms of general combining ability. Sabzevar×TS-3 and Sirjan×Fars were the best hybrids in most traits. The general heritability was between 0.90 to 0.96 for biologic yield and number of branches, respectively and narrow heritability was between 0.36 to 0.91 for the number of branches and harvest index, respectively. The analysis of variance by Hayman method confirmed the results of Griffing analysis.

Today, the use of renewable energies has become increasingly important due to the fossil fuels being consumed which cause environmental pollution. The use of solar energy due to the abundance and availability of this energy and the ability to save and convert it into other forms of energy has been considered. In this work, a stepped solar still is simulated in two dimensions using Comsol software. Also, increasing the number of stairs and adding a number of Fins to increase the amount of fresh water produced has been studied. The simulation results were compared with the experimental data. The average error rate for fresh water produced and the temperature of saline water obtained from the software with experimental values are 11.78 and 1.75 percent, respectively. The results show that as the number of steps increases, the amount of fresh water produced increases. In addition, adding three thermal fins with a size of 0.3 cm on the stairs compared to the existing state of the device, the amount of fresh water produced increases by 9.65%.

Recently the stepped spillways have been used as an appropriate solution for energy dissipation. In the present study, Siahbisheh dam spillway is simulated by using Computational Fluid Dynamic (CFD), in which the Mixture method and Reynolds Stresses Model (RSM) turbulence model is used. In the first modeling series the over all steppes slope is constant. The number of the steps is increased to 80, in which the step height and length is decreased to 0.51 and 1.53 m, respectively. In another case, by reducing the number of the steps to 30, steps height and length increased to 1.36 and 3.9 m, respectively. In the next modeling series, the steppes slope was changed. By reducing the number of the steps in to 30, spillway slope increased to 330 and the height of the steps increased to 1.36 (step length was 2.1 m). Then by increasing the number of the steps to 80, spillway slope decreased to about 140 and the height of the steps decreased to 0.51m (step length was 2.1 m). Results analysis and comparison of the increasing the energy dissipation to 60 steppes case shows that by decreasing the number of the steppes into 30, the energy dissipation decreases. This trend is expected to continue by increasing the steppes number into 80, but it is not. It seems that there is no fixed pattern between the number of the steppes and energy dissipation percentage. It can be said the increasing the number of the steppes and decreasing the slope up to a certain value increases the energy dissipation, and this number would be optimal under certain conditions. Finally it seems that the effect of the slope is considerable, so that the case in which larger number of steppes with a mild slope is closer to the optimum condition of maximum energy dissipation.

In order to identify the correlations and relationships between different traits in the bread wheat, 30 genotypes were investigated as sub-factors under the split plot experiment in the completely randomized design in greenhouse and the randomized complete block design in the field with three replications under the normal irrigation and post-anthesis water stress conditions. The results of the canonical correlation analysis showed that at both normal and moisture stress levels, there was a significant correlation between the pair of canonical variables obtained from the phenological traits and the yield components. Under the normal conditions in the greenhouse, to increase the spike density and length, the number of days to 50% flowering can be considered as a suitable selection criterion. According to the results of canonical correlation analysis, under the stressed conditions in greenhouse, to increase the spike length, the number of days to the heading, maturity and 50% of flowering were among the important and effective factors. Under the optimum irrigation conditions in the field, the number of days to maturity was considered as one of the factors influencing the seed weight per spike. The results of canonical correlation analysis under the field stress conditions showed that to increase the 1000-seed weight, the number of days to maturity can be considered an appropriate selection criterion.

The electrical behavior of neurons can be more complex in the presence of autapse. In the presence of an autaptic connection, the Izhikevich neuron model can show a variety of dynamic behaviors, such as chaotic behavior. This paper presents a novel, high speed and robust pseudo random number generator based on the autaptic Izhikevich neuron oscillator and its FPGA implementation. The autaptic Izhikevich neuron model is simulated and dynamically analyzed. Then, the proposed pseudo-random number generator is modeled and simulated using the Xilinx system generator platform, synthesized using Xilinx Synthesis Tool, and implemented on the XILINX SPARTAN-6 XC6SLX9 FPGA evaluation board. As a post processing operation, the XOR function is used to increase the randomness of the output bit sequences. The FPGA implementation results show that the implementation cost of the proposed pseudo-random number generator is lower than similar works, and the proposed generator achieves a maximum frequency of 63.2 MHz. The NIST test suite is used for testing the quality of the generated bit sequences. The NIST test results indicates the high quality of the generated random bit sequence.

Purpose: Food security is a critical global challenge that is influenced by research and innovation in the field. Therefore, the objective of this study is to analyze the scientific output of developing countries in food security and examine its relationship with patents and Gross Domestic Product (GDP).Methodology: This applied research utilized the Scientometric approach. A total of 8,416 papers published between 1992-2023 in the field of food security by developing countries were included in the study using citation databases from Clarivate Analytics. Additionally, patent registrations from the WIPO database and GDP data from the World Bank were analyzed. Information was collected through note-taking, and the data was analyzed using Pearson's correlation coefficient.Findings: The findings reveal an upward trend in the publication and citation of scientific outputs related to food security in developing countries. China has higher numbers of papers, patents, GDP, and food production index compared to Iran, Japan, and South Korea. There is also a positive correlation observed between population and the number of papers, gross production and the number of papers, food production and the number of published papers, as well as the number of patents and papers citing scientific outputs of countries.Conclusion: These results highlight the significant relationship between increasing scientific output, GDP, the number of patents, and food security. Greater emphasis on food security contributes to enhanced scientific output, GDP, and innovation. Similarly, increasing scientific output, GDP, and innovation positively impact food security in countries.Value: This study emphasizes the importance of scientific outputs in driving technological advancements, innovations, and ultimately, ensuring food security in developing countries.

Recently, particular attention has been paid to the stepped spillways due to the increasing effect of energy dissipation and the reduction of cavitations risks with the development of Roller Compacted Concrete (RCC) technique. Flow regimes on the spillways divide into three groups, namely skimming, jet and transition flow. Compared to the numerical methods, the majority of performed studies in this field have been done using experimental methods, which requires a lot of time and expenditure. This paper has attempted to train an Artificial Neural Network (ANN) which includes two layers for determination of the number of aerated steps over broad-crest stepped spillways under the jet flow regime condition using MATLAB. The best network was trained entailing one neuron on each layer. Results show that the number of aerated steps can be obtained by having the critical depth, steps height, chute length, chute angle, and total number of steps. The obtained nonlinear relationship was validated using testing data. The predicted results have been compared to experimental data. Proper conformity of outputs and experimental data has been investigated using SPSS. The P-Value of Man-Whitney Test of the training and testing data compared to experimental data are 0.89 and 0.77, respectively. Good agreement was shown between experimental data and predicted results using ANN.