46 research outputs found
One-dimensional backreacting holographic superconductors with exponential nonlinear electrodynamics
In this paper, we investigate the effects of nonlinear exponential
electrodynamics as well as backreaction on the properties of one-dimensional
-wave holographic superconductors. We continue our study both analytically
and numerically. In analytical study, we employ the Sturm-Liouville method
while in numerical approach we perform the shooting method. We obtain a
relation between the critical temperature and chemical potential analytically.
Our results show a good agreement between analytical and numerical methods. We
observe that the increase in the strength of both nonlinearity and backreaction
parameters causes the formation of condensation in the black hole background
harder and critical temperature lower. These results are consistent with those
obtained for two dimensional -wave holographic superconductors.Comment: 8 pages (two columns), 2 figures (each including 2 subfigures), 3
table
Analysis of the Interaction of Resilience Variables of New Urban Habitations against Earthquake Risk: A Case Study of Isfahan Metropolitan)
IntroductionAmong natural disasters, earthquakes are one of the most important natural disasters that pose a threat to the development of the society. Each year, it causes various physical, social, and economic damage around the world. The consequences of an earthquake, both in terms of recurrence and in terms of the damage it causes, affect society. Because, on the one hand, earthquakes contribute to the lack of security for residents at risk, and on the other hand, they reduce the risk of achieving sustainable development. Therefore, earthquakes, both psychologically and financially, due to the speed of occurrence and the volume of destruction, have devastating effects and are at the forefront of natural disasters. Until the 1980s, the dominant approach to crisis management worldwide was based on reducing vulnerability, but since the 1980s, efforts have been made to change the prevailing crisis management paradigm. Thus, the prevailing view has shifted from focusing solely on reducing vulnerability to increasing disability resilience. In this new paradigm, the shift from reactivity to deterrence and participation has changed. Meanwhile, analyzing the interaction of earthquake resilience variables to identify key factors is one of the issues that should be considered in any society. It is noteworthy that the type of attitude towards the issue of resilience and how it is analyzed, on the one hand, plays a key role in how resilience recognizes the current situation and its causes, and on the other hand, affects policies and measures to reduce risk and how to deal with it. Therefore, analyzing the interaction of resilience variables against earthquakes and reducing their effects according to the results will be of great importance.Keywords: Resilience, Interaction, New Urban Habitations, Earthquake Risk, Isfahan Urban Area.MethodologyDue to the studied components and the nature of the subject, the approach of this research is descriptive-analytical. The interaction analysis method was used to analyze the data. Interaction/structural interaction analysis is a method for analyzing the possible occurrence of an issue in a predicted set. The probabilities of this can be adjusted by judgments about the potential for interaction between the predicted subjects. In this study, using 86 variables in the form of 6 indicators, the interaction of the studied resilience variables in the new urban Habitations of the Isfahan metropolitan was analyzed using MIC Mac software. DiscussionPreliminary analysis of the matrix data indicates that there are a total of 3496 relationships for the matrix. Also, the degree of saturation of the matrix is %63.29, which indicates that the selected factors have a relatively large and scattered effect on each other, and in fact, the system has been in an unstable state. Out of 4791 evaluable relations in this matrix, 2778 relations have zero numbers, which means that the factors have not affected or have not affected each other. Also, the studied matrix was %100 desirable and optimized based on statistical indices with two data rotations. The results of direct matrix data analysis have shown that the variables of geographical confinement diversity, level of awareness about seismicity of the habitation, and population density with scores of 159, 158, and 146, respectively. As the most important influential variables of the severity of the damage, compensation capacity proximity to hazardous areas with 191, 162, and 157 points, respectively, have been identified as the most important variables. In a cross-matrix, the sum of the row numbers of each factor indicates the degree of influence, and the sum of its columns indicates the degree of influence of that factor on other factors. Also, the results of indirect matrix data analysis have shown that the variables of geographical environment diversity, level of knowledge about seismicity in the region, and population density with scores of 1312373, 1272025, and 1200271, respectively, were the most important indirect variables. Severity, damage capacity and compensation capacity, and community-based risk management with scores of 15372702, 1298828, and 1298341, respectively, have been identified as the most important indirectly affected variables. What can be understood from the scattering plane of the variables affecting the resilience of new urban Habitations in the Isfahan metropolitan, the concentration of most variables around the diagonal axis, which indicates the instability of the system under study? ConclusionIn this study, using Mick Mac software, the effective variables on resilience forecasting of new urban Habitations in the Isfahan urban area have been investigated. The results of direct matrix data analysis have shown that the variables of geographical confinement diversity, level of awareness about seismicity of habitat, and population density were the most important influential variables. Severity, compensation capacity, and proximity were the most important risk areas. The analysis of indirect matrix data has also shown that the variables of geographical environment diversity, level of knowledge about seismicity of the region, and population density were the most important indirect variables. The variables of the severity of the damage, and compensation capacity were the most important indirectly affected risk-based risk management variables. EReferences- Ahmad Pour, A., Abdali, Y., Sadeghi, A., & AllahGholi Pour, S. (2018). Analysis of resilience components in the central tissue of Hamedan using Moran spatial autocorrelation. Quarterly Journal of Physical Development Planning, 5(1), 93-106.- Aksha, S. K., & Emrich, C. T. (2020). Benchmarking community disaster resilience in Nepal. International Journal of Environmental Research and Public Health, 17(6), 1-22.- Delavar, M. R., Sadrykia, M., & Zare, M. (2017). A GIS-based fuzzy decision making model for seismic vulnerability assessment in areas with incomplete data. International Journal of Geo-Information, 6(4), 119.- Febriyanti, F., Martini, S., Hidajah, A. C., & Dwirahmadi, F. (2021). A study on community economic resilience in response to earthquakes in Jailolo sub–district, North Maluku. Journal Berkala Epidemiologi, 9(2), 105-114.- Forrester, I. T., Mayaka, P., Brown-Fraser, S., Dawkins, N., Rowel, R., & Sitther, V. (2017). Earthquake disaster resilience: A framework for sustainable gardening in haiti’s vulnerable population. Journal of Hunger & Environmental Nutrition, 12(1), 136-149.- Godet, M. (2008). Strategic foresight. France, Paris: Lipsor Working Paper.- Haidarifar, M. R., Sialigli, M., & Soleimanirad, E. (2019). The evaluation of urban resilience components (case study: Kermanshah metropolis). Journal of Geography and Environmental Studies, 7(28), 107-125.- Kawachi, I., Aida, J., Hikichi, H., & Kondo, K. (2020). Disaster resilience in aging populations: Lessons from the 2011 Great East Japan earthquake and tsunami. Journal of the Royal Society of New Zealand, 50(2), 263-278.- Khayambashi, E., Taghvaei, M., & Varesi, H. R. (2020). Isfahan metropolitan resilience predictive model in crisis and unexpected incidents. Journal of Geographical Researchers, 35(1), 19-30.- Liu, B., Chen, X., Zhou, Z., Tang, M., & Li, S. (2020). Research on disaster resilience of earthquake-stricken areas in Longmenshan fault zone based on GIS. Journal of Environmental Hazards, 19(1), 50-69.- Matsuura, H. (2021). Level of disaster resilience and migration patterns in Japanese and foreign residents. Springer International Publishing.- Mitchell, J. K. (2014). Crucibles of hazard: Mega–cities and disasters in transition. Tokyo: Tokyo University Press.- Naimi, K., & Pourmohammadi, M. R. (2016). Identifying key factors affecting the future of Sanandaj's lower urban settlements with emphasis on future research application. Quarterly Journal of Urban Studies, 5(20), 53-64.- O’Brien, K., Sygna, L., & Haugen, J. E. (2004). Vulnerable or resilience? A multi–scale assessment of climate impacts and vulnerability in Norway. Journal of Climate Change, 64(1-2), 193-225.- Panday, S., Rushton, S., Karki, J., Balen, J., & Barenes, A. (2021). The role of social capital in disaster resilience in remote communities after the 2015 Nepal earthquake. International Journal of Disaster Risk Reduction, 55, 1-11.- Parizadi, T., Shaikholeslami, A., & Karimi Razakani, A. (2019). Analysis of the state of urban resilience against natural hazards (case study: Baqer-shahr city). Journal of Research and Urban Planning, 37, 41-54.- Rabbani, T. (2012). Structural analysis method is a tool for identifying and analyzing variables affecting the outcome of urban issues. Proceedings of the First National Conference on Future Research. February 17, 2012. Tehran.- Rao, F., & Summers, R. J. (2016). Planning for retail resilience: Comparing Edmonton and Portland. Cities, 58, 97-106.- Salmani, M.,  Kazemi Sani Ataallah, N., Badri S. A., & Motavaf, Sh. (2016). Identifying and analyzing the impact resilience indicators in the rural areas of north and northeast Tehran. Journal of Spatial Analysis Environmental Hazards, 3(2), 1-25.- Song, J., Huang, B., Li, R., & Pandey, R. (2020). Construction of the scale-specific resilience index to facilitate multi-scale decision making in disaster management: A case study of the 2015 Nepal earthquake. Journal of Social Indicators Research, 148(1), 189-223.- Soofi, S. Y. (2016). Achieving urban resilience: Through urban design and planning principles. Master’s Thesis, Oxford Brookes University. Oxford. UK.- Spaans, M., & Waterhout, B. (2017). Building up resilience in cities worldwide Rotterdam as participant in the 100 resilient. Cities, 61, 109-116.- Statistics Center of Iran (2016). The results of the 2016 census of Isfahan province. (n.p).- Turner Ii, B. L. (2010). Vulnerability and resilience: Coalescing or paralleling for approaches sustainability science?. Journal of Global Environmental Change, 20(4), 570-576.- Varesi, H. R., & Ahmadi, S. (2011). A study of the performance of new cities with emphasis on population (case study: Majlesi new city). Journal of Population Quarterly, 18(75-76), 157-178.- Zali, N. (2012). Strategic futurism in regional planning and development. Second Edition. Tehran: Research Institute for Strategic Studies Publications.- Zangiabadi, A., Nastaran, M., & Mo'meni, Z. (2015). Geographical analysis and location of temporary urban housing centers in environmental crises using GIS (case study: District 6 of Isfahan). Journal of Geography and Planning, 20(56), 149-169.- Zangiabadi, A., & Tabrizi, N. (2006). Tehran earthquake and spatial assessment of vulnerability in urban areas. Journal of Geographical Research, 38(56), 115-130.- Zhang, X., Tang, W., Huang, Y., Zhang, Q., Duffield, C. F., Li, J., & Wang, E. (2018). Understanding the causes of vulnerabilities for enhancing social-physical resilience: Lessons from the Wenchuan earthquake. Journal of Environmental Hazards, 17(4), 292-309
Optimal operation and management of multi-microgrids using blockchain technology
This paper tries to address the optimal operation of networked microgrid from the reliability perspective in a correlated atmosphere for the wind generators. The suggested approach performs based on unscented transformation in the form of a nonlinear projection and the heuristic method as the optimizer. The proposed structure is arranged as a complex constraint optimization problem with several targets seeing the varied objectives such as energy not supplied, system interruption frequency, system interruption duration and energy losses. Owing to the interrelated natural surroundings of multi-microgrids, it is a necessity for the microgrids to let the each other access the operation info and with the central unit. In this situation, it is quite wise to provide a secured construction made of the blockchain for the assurance of the reliability and adequate security of data sharing in the microgrids. With the aim of validation of the proposed model, an IEEE standard system is considered and divided into four interrelated microgrids with one side connection to the main grid. The simulation results show the high capability of the proposed framework for enhancing the operation and reliability indices. Moreover, it is seen that almost 0.6% and 0.77% additional cost is imposed to the system in the deterministic framework in the first and second scenarios, respectively. 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.Scopus2-s2.0-8511166059
Considerable decreased fruits and snack consumption in Iran population during COVID-19 lockdown: a cross-sectional web-based survey National Food and Nutrition Surveillance
Customer relationship management in small and medium sized hotels
Applying some "beneficial technologies" on "Small and Medium Enterprises (SMEs)" will have crucial benefits in the structure of these enterprises. For this paper, Customer Relationship Management (CRM) would be as the technology and SMEs would be the small and medium sized hotels. Among all SMEs, CRM works so well especially in hotels because it helps them to understand their guests, show their appreciation to them, as well as to gather some useful practical data about their customers. These will enable the hotels to present better services to the guests in their next visit.The importance of recognizing the rightway of implementingCRM in small and medium sized hotels should always be considered by enterprises. This paper is about the importance of CRM and its different usages on SME hotels. Moreover, the challenges of SME hotels in implementing CRM will be discussed
Density and Polarization Profiles of Dipolar Hard Ellipsoids Confined between Hard Walls: A Density Functional Theory Approach
The density and polarization profiles of the dipolar hard ellipsoids confined between hard walls are studied using the density functional theory (DFT). The Hyper-Netted Chain (HNC) approximation is used to write excess grand potential of the system with respect to the bulk value. The number density is expanded up to zero and first order in polarization to find the results. For the zero order in polarization, the coupled integral equations for the directional densities are obtained. Then, for the first order in polarization the coupled integral equations for the directional densities and polarization profiles are obtained. To simplify the calculations we use restricted orientation model (ROM) for the orientation of ellipsoids to find the density and polarization profiles. We also apply an electric field and write an expression for the excess grand potential of the system and obtain the coupled integral equations for the density and polarization profiles again. Finally, we calculate the density and polarization profiles for different cases and compare the obtained results