A graph $G$ is called irregular if the degrees of all its vertices are not the same. A graph is said to be \textit{stepwise Irregular} (SI) if the difference of the degrees of any two adjacent vertices is always 1 (one). This paper deals with \textit{2-stepwise Irregular} (2-SI) graphs in which the degrees of every pair of adjacent vertices differ by 2. Here we discuss some properties of 2-SI graphs and generalize them for $k$-SI graphs for which the imbalance of every edge is $k$. Besides, we also compute bounds of irregularity for the Albertson index in any 2-SI graph.

K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. First, the effectiveness of the algorithm is affected by redundant and irrelevant features. Furthermore, this algorithm does not consider the differences between samples, which led the algorithm to have inaccurate predictions. In this paper, we proposed a novel scheme for improving the accuracy of the KNN classification algorithm based on the new weighting technique and stepwise feature selection. First, we used a stepwise feature selection method to eliminate irrelevant features and select highly correlated features with the class category. Then a new weighting method was proposed to give authority value to each sample in train dataset based on neighbor categories and Euclidean distances. This weighting approach gives a higher preference to samples that have neighbors with close Euclidean distance while they are in the same category, which can effectively increase the classification accuracy of the algorithm. We evaluated the accuracy rate of the proposed method and analyzed it with the traditional KNN algorithm and some similar works with the use of five real-world UCI datasets. The experiment results determined that the proposed scheme (denoted by WAD-KNN) performed better than the traditional KNN algorithm and considered approaches with the improvement of approximately 10% accuracy.

In recent decades, necessity to protect environment has been a serious concern for all people and international communities. In appropriate development of human economic activities, subsistence dependence of the growing world population on nature decreases the natural diversity of ecosystems and habitats day by day and provides additional constraints for life and survival of wildlife. As a result, implementation of programs to protect species and ecosystems is of great importance. The current study was carried out to implement a comprehensive strategic environmental management plan in the Mond protected area in southern Iran. Accordingly, the protected area was zoned using multi criteria decision method. According to the numerical models, fifteen data layer were obtained on a scale of 1: 50,000. The results revealed that 28.35% out of the entire study area belongs to nature conservation zone. In the following step, in order to offer the strategic planning using strength, weaknesses, opportunities and threats method, a total number of 154 questionnaires were prepared and filled by the relevant experts. For this purpose, after identifying the internal and external factors, they were weighted in the form of matrices as; internal factor evaluation and external factor evaluation. Analytical hierarchy process and expert choice software were applied to weight the factors. At the end, by considering the socioeconomic and environmental issues, the strategy of using protective strategies in line with international standards as well as a strong support of governmental national execution with a score of 6.05 was chosen as the final approach.

Rock structures are subjected to cyclic tension-compression loading due to a blasting, earthquake, traffic, and injection-production in an underground storage case. Therefore, studying the fatigue behavior of rock samples under this type of loading is required. In this study, the accumulated fatigue damage for a Green Onyx rock sample consisting only one mineral composition with two-step high-low sequences of loading levels was investigated under a completely reversed loading condition. New apparatus based on the R. R. Moore fatigue test machine was designed to assess this type of loading. A comparison was conducted between the predicted behavior of the Linear Damage Rule and the experimental data and a new damage model was proposed based on the experimental observation. The results showed a good agreement between the proposed damage model and the experimental data.

Background: Citrus is among the cold temperature (freezing) susceptible plants. The performance of storage and breeding of horticultural crops is mainly dependent on the correlation among the traits. Objectives: The present study was conducted to identify the physiological and biochemical traits of some citrus cultivars with the greatest influence on stress tolerance and determine the direct and indirect effects of these traits on the median Lethal Time (LT50) using integrated pathway analysis (i. e., stepwise regression and causality coefficient). Methods: Pathway analysis (i. e., stepwise regression and causality coefficient) based on additive models, which is among the robust statistical methods to describe the relationship among the traits, was used to investigate the physiological and biochemical charac, teristics of four citrus cultivars (i. e., Japanese mandarin, Thomson orange, Ruby Star grapefruit, and Lisbon lemon) at temperature levels (-8,-4, and +4°, C) in a completely randomized design with three replications in 2021. Results: The results showed that Japanese mandarin and Thomson orange cultivars had the highest stress tolerance (LT50). The results of the correlation coefficient demonstrated that the highest positive and significant correlations belonged to the LT50 with total flavonoid (0. 443**), chlorophyll a with chlorophyll b (0. 613**), carotenoid with chlorophyll a (0. 929**), chlorophyll b (0. 573**), and total chlorophyll (0. 849**), relative moisture content with malondialdehyde (0. 559**), glycine-betaine with catalase (0. 919**), hydrogen peroxide with total flavonoid (0. 405**), and catalase (0. 611**). Conclusions: The results of stepwise regression for all traits indicated the importance and critical role of total flavonoid, proline, and LT50 characteristics.