Background and Objectives: Silibinin, an antioxidant, is used to prevent and treat skin inflammatory disorders. This study aimed to develop a liposomal silibinin formulation to increase its bioavailability and water solubility and control its kinetic release to improve the healing process of skin wounds. Methods: liposomes carrying silibinin were prepared using the thin film method. The loading capacity and drug release kinetics were evaluated using the reading drug absorption in the suitable wavelength. The particle size and surface potential (ζ-potential) of nanosystems were determined using dynamic light scattering technique. Lipid nanoparticle morphology was determined using a scanning electron microscope. An MTT assay was then used to determine the cytotoxicity on human skin fibroblasts. The obtained data were analyzed using a 1-way analysis of variance in SPSS software, version 18. Results: The particle size and ζ-potential of liposomal nanoparticles with silibinin optimized liposomal silibinin are 112±9. 07 nm and-14. 5±2. 2 mV, respectively. The encapsulation of silibinin in liposome was 84%±5. 3%, and the total drug release at 37°C during 24 h was 67. 3%±4. 98%. In addition, the results of cellular toxicity showed that silibinin alone or liposomes containing silibinin do not have cytotoxicity on healthy human fibroblasts. Further, encapsulated silibinin versus its free form promotes the growth of fibroblast healthy cells. Conclusion: The results show that a nanoliposomal silibinin formulation can be used as a nanodrug containing an effective herbal agent for speeding up the healing of skin wounds.

The central issue of the present paper is the study of the causes of the mother tongue decline in the Sahne city in Kermanshah province. The issue of language is beyond the dialect of people and is refer to the form of life and the matter of macroeconomic and political relations. From this perspective, the form of life and the language associated with it explain the praxis of the members of the society. The appropriate method of examining the problem should be able to analyze the justification of agents to their situation, that is why Grounded Theory is chosen as the method of this research and data analysis is taken from abduction reasoning. The results of the analysis introduced the categories of globalizing, modernizing, de-use of language, economic necessity and the government as the most important factors of local language fading. In this essay the meaning of globalization is the globalizing of special type of economic relation that explain other categories role in the process of fading of languages.

Identifying the constraining factors of production and yield gap is very important. Therefore; this research was performed to identify the production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

A B S T R A C TFor choosing suitable place multiple methods are introduced, which examine the qualities, methods and patterns of location selection. The current methods use global approach and do not pay attention to spatial differences, environmental variation in variables, local changes modeled by local weighting indicators. It has been selected as a case study to evaluate the EMS center of Fars province and to evaluate the indicators of distance from the power plant, distance from logistics centers, industries, transportation terminals, hospitals, hotels and tourism, cities, rural areas and custom centers. has been used, using the AHP method to weight the qualities, and then for local weights, non-overlapping neighborhood filtering within a radius of 25 km are used and calculate the corresponding changes, quantity, ratio Presented in this article, the obtained weights, then the compute local weighted layers, and then local weight was multiplied in the normalized layers and the final layer were obtained. In the next step, it was combined and calculated to compare the data using the global method. The results of the two methods were transferred to the points of the EMS and the results were analyzedExtended AbstractIntroductionIn geographical studies and spatial planning, there are different approaches to choosing the right place for all kinds of applications and uses, and a process is followed to choose the best places. This process includes stating the research problem (cognition), choosing the criteria and preferences of decision makers and how to determine the weight of indicators, combining criteria (design) and finally, choosing the best option. In the current methods of spatial decision, the criteria are given a fixed weight, while in geographical locations, the distribution of geographical phenomena is not uniform. In this case, attention should be paid to the spatial distribution pattern of geographical phenomena based on the principle of sensitivity of the range of changes, the size of the range of changes affects the outputs, and the data with a smaller range of changes also have a lesser effect on the output. The data with a larger range of changes will have a more significant effect on the output. Therefore, in spatial analysis, indicators that have small changes are less important. Local models have been presented to model local changes in spatial multi-criteria decision-making; in this research, the main issue is how to model the local changes that affect the expected outputs. MethodologyThe research process is based on multi-criteria spatial decision-making methods (national and local). First, spatial patterns of indicators were analyzed through exploratory analyzes of ESDA spatial data. Then based on the review of the research criteria, the direct weighting method was used to calculate the weight of the indicators, and the experts were asked to specify the weight of the criteria in the range of 1 to 10. The opinions were combined, and the final weight was obtained. First, the data were spatially modelled to model and calculate the local weights. Then Block Statistics spatial filter without overlap was used to determine the neighborhood. The range of local changes, maximum and minimum values, were calculated, and local weights were obtained based on that. Finally, the information layers were descaled. After that, the unscaled criterion layers were multiplied by the national weights and the final national scores were obtained. In the next step, the data of the evaluated information layers (local and national) were transferred to the points of emergency databases. Based on the analysis, the fit was done. Results and discussionGeneral or global weights pay attention to the relative importance of indicators, which is the starting point for calculating local weights. Based on the research results, the most critical indicators are industries, cities and hospitals, which are more important in the location of road emergency stations. However, in order to achieve better results, it is necessary to build a local weight layer. The results of the research show that the indicators' weight and the difference in the criteria (general weight) are not equal in the entire geographical area, and the areas with a larger range of changes have a higher coefficient.Because, unlike general weights that are obtained based on different methods, local weights are estimated based on the principle of sensitivity of the range of changes and are changed spatially, and a fixed value is not considered for all areas. According to the research findings, the highest level in the general and local evaluation method corresponds to 0.5 to 0.7. Based on the local (geographic) weight method, it is less than the national or general method in the range of 0.9 to 1. Furthermore, this is due to the more precise nature of this method, which models the effects of local changes. To evaluate the compliance of the emergency centers with the final maps of suitability assessment, the information on the suitability maps was transferred to the map of the emergency center points of Fars province. Based on the evaluation of 207 emergency stations, according to the general method, 14 percent are in the high group (0.9-1), and according to the local or geographical method (16.9), percent are in this group. ConclusionAt the level of space and geographical regions, phenomena and geographical complications are not uniformly distributed, some phenomena have a homogeneous distribution, and some have a heterogeneous distribution. On the one hand, the phenomena and decision issues are affected by the context in which they are formed and evolve; on the other hand, these phenomena are placed in the network of mutual relations. Furthermore, the results of the set of phenomena may differ from the results of the phenomena individually and separately; in this article, an attempt has been made to address the issue that in spatial analysis and planning, it is necessary to pay attention to geographical differences in decision-making. Furthermore, it should not be evaluated in general terms of spatial decision problems; one of the methods of modelling these differences and spatial changes is to consider the local weight of the criteria. Based on the research findings, local (geographical) and national analysis results are different and can better show these changes. On the other hand, the pattern of spatial differences also has its spatial pattern, and paying attention to these differences in spatial differences can be the subject of further studies. FundingThere is no funding support. Authors’ ContributionAuthors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none. Conflict of InterestAuthors declared no conflict of interest. Acknowledgments We are grateful to all the scientific consultants of this paper.