Materialidade e tipologia do património funerário. O Cemitério de Jesus em Múrcia, Espanha

The cemetery of Jesus of Murcia (Spain) has more than 600 pantheons, which converts it in a small funerary city, whose buildings show a large spectrum of architectural samples. This paper presents an exhaustive study of the typologies and materials used in those little buildings. In addition, this investigation addresses the study of the evolution and the distribution of the typologies and materials detected, drawing conclusions about both of these aspects.O cemitério de Jesus de Múrcia (Espanha) tem mais de 600 panteões, o que faz dele uma pequena cidade funerária, cujos edifícios exibem um grande espectro de amostras arquitetónicas. Este artigo apresenta um estudo exaustivo das tipologias e materiais utilizados nesses pequenos edifícios. Além disso, esta investigação aborda o estudo da evolução e distribuição das tipologias e materiais identificados, procurando tirar conclusões sobre ambos os aspetos

Design of a Support Tool to Improve Accessibility in Heritage Buildings—Application in Case Study for Public Use

The authors would like to thank the reviewers for their thoughtful comments and efforts towards improving our manuscript. This work was supported by the project PP2022.PP.27 belonging to the Research and Transfer Plan of the University of Granada, Research Group RNM 0179 of the Junta de Andalucia and the projects REMINE Programme for Research and Innovation Horizon 2020 Marie Sklodowska-Curie Actions, WARMEST Research and Innovation Staff Exchange (RISE) H2020-MSCA-RISE-2017, RRRMAKER H2020-MSCA-RISE-2020 (Marie Sklodowska-Curie Research and Innovation Staff Exchange and Scientific Unit of excellence "Ciencia en la Alhambra", ref. UCE-PP2018-01, University of Granada).The existing literature shows the interest in the study of accessibility within heritage architecture, particularly in the context of repurposing these structures to extend their lifespan. Published examples primarily focus on barrier identification or intervention within specific buildings, without the development of methods that facilitate their widespread application for barrier removal. The proposed methodology entails the division of the building into analytical zones, the identification of existing barriers, the proposal of feasible solutions, and the establishment of various action plans based on the building’s priorities. The results reveal a significant percentage of removable architectural barriers within the analysed buildings, all in harmony with the preservation of the heritage. Among the conclusions, it is noteworthy that the method’s applicability extends to heritage and non-heritage buildings of varying uses and typologies, showcasing the substantial accessibility potential within heritage architecture.Research and Transfer Plan of the University of Granada PP2022.PP.27Junta de Andalucía RNM 0179Project REMINE Programme for Research and Innovation Horizon 2020 Marie Sklodowska-Curie ActionsProject WARMEST Research and Innovation Staff Exchange (RISE) H2020-MSCA-RISE-2017Project RRRMAKER H2020-MSCA-RISE-2020 (Marie Sklodowska-Curie Research and Innovation Staff Exchange and Scientific Unit of excellence "Ciencia en la Alhambra") UCE-PP2018-01University of Granad

Flavonoides en Musgos: consideraciones quimiosistemáticas.

LÓ¡±z-SÁEZ,JA.. M.J. PÉREZ-ALONSO & A. VELASCO NEGIJERUELA. 1996. Flavonoids in Musci: cheinosystemarie eonsiderations. Bat. Complutensis 21: 9-38. Tbk work confirnis that mosses are not primitive embryo-ptants. They are closely related tovaseu¡ar plants, aecording to their flavonoid counposition.LÓPEz-SÁrz, JA., PÉREZ-ALONSO & A. VELASCO NIIQUERUELA. 1996. Flavonoides en Musgos: consideraciones quimiosistemáticas. Bot. Complutensis 21: 9-38. Se argunienta el significado quíiníosistcinátíco dc la presencia de flavonoides en Musci, y se apoya la propuesta de que los musgos no son embriobiontes primitivos, sino que comparten una fuerte afinidad con las plantas vasculares, habiendo ido bioquimicamente hablando muy paralelos en su evolución

Project portfolio selection for increasing sustainability in supply chains

[EN] Sustainability practices impact on the competitiveness of organizations. Enterprises need approaches that both support the implementation of these practices by helping to define the strategic elements of sustainable supply chains and prioritize projects to increase profitability. The purpose of this paper is to propose an approach using the Analytic Hierarchy Process that supports the portfolio project decision by aligning the project selection process to the strategic objectives of a supply chain that pursue sustainability. This approach will benefit enterprises to prioritize projects that have the highest impact on the sustainability strategy of the supply chain over time. The approach has been applied to an Agri-food supply chain.Authors of this publication acknowledge the contribution of the Project GV/2017/065 "Development of a decision support tool for the management and improvement of sustainability in supply chains" funded by the Regional Government of Valencia.Verdecho Sáez, MJ.; Pérez Perales, D.; Alarcón Valero, F. (2020). Project portfolio selection for increasing sustainability in supply chains. Economics and business letters. 9(4):317-325. https://doi.org/10.17811/ebl.9.4.2020.317-325S3173259

An Analysis of the Cost of Water Supply Linked to the Tourism Industry. An Application to the Case of the Island of Ibiza in Spain

[EN] Tourist activity has a number of impacts on the destinations in which it takes place, among which are the environmental ones. A particular problem is the increase in water demand and wastewater production, which can compromise the balance of ecosystems. As many authors point out, there is a research gap in the comparative analysis between available water resources and the demand associated with tourism. In this respect, the main objective of this work is, on the one hand, to assess the water needs linked to the tourism industry and the capacity of natural resources to meet such a demand and, on the other hand, to estimate the economic cost of the water supply associated with the growing tourist demand in a territory, such as the island of Ibiza in Spain. It has been determined that the resources available are not sufficient to meet the water demand of the resident population at this destination, which is why it is necessary to resort to producing desalinated water. Therefore, the additional requirements associated with tourism must be met fully with desalinated water, which results in an increased cost of water management for the region. This paper also points at water losses in distribution networks and tourism seasonality as two phenomena that aggravate this issue.González-Pérez, DM.; Martín-Martín, JM.; Guaita Martínez, JM.; Sáez-Fernández, FJ. (2020). An Analysis of the Cost of Water Supply Linked to the Tourism Industry. An Application to the Case of the Island of Ibiza in Spain. Water. 12(7). https://doi.org/10.3390/w1207200612

Armeria castrovalnerana sp. nov., un nuevo taxon de Armeria gr. alpina en el macizo del Castro Valnera (Cordillera Cantábrica, Burgos)

Se describe una nueva especie del género Armeria (Plumbaginaceae) recolectada en el macizo del Castro Valnera (extremo oriental de la Cordillera Cantábrica). Se ha detectado una única población con no más de 190 individuos, en condiciones de extremo aislamiento geográfico y ecológico. La evolución reticular característica del género, que con frecuencia llega a producir microespecies de área muy reducida, aconseja que se tomen medidas de protección que aseguren su supervivencia

An Analysis of the Cost of Water Supply Linked to the Tourism Industry. An Application to the Case of the Island of Ibiza in Spain

Tourist activity has a number of impacts on the destinations in which it takes place, among which are the environmental ones. A particular problem is the increase in water demand and wastewater production, which can compromise the balance of ecosystems. As many authors point out, there is a research gap in the comparative analysis between available water resources and the demand associated with tourism. In this respect, the main objective of this work is, on the one hand, to assess the water needs linked to the tourism industry and the capacity of natural resources to meet such a demand and, on the other hand, to estimate the economic cost of the water supply associated with the growing tourist demand in a territory, such as the island of Ibiza in Spain. It has been determined that the resources available are not sufficient to meet the water demand of the resident population at this destination, which is why it is necessary to resort to producing desalinated water. Therefore, the additional requirements associated with tourism must be met fully with desalinated water, which results in an increased cost of water management for the region. This paper also points at water losses in distribution networks and tourism seasonality as two phenomena that aggravate this issue

Using Machine-Learning Algorithms for Eutrophication Modeling: Case Study of Mar Menor Lagoon (Spain)

[EN] The Mar Menor is a hypersaline coastal lagoon with high environmental value and a characteristic example of a highly anthropized hydro-ecosystem located in the southeast of Spain. An unprecedented eutrophication crisis in 2016 and 2019 with abrupt changes in the quality of its waters caused a great social alarm. Understanding and modeling the level of a eutrophication indicator, such as chlorophyll-a (Chl-a), benefits the management of this complex system. In this study, we investigate the potential machine learning (ML) methods to predict the level of Chl-a. Particularly, Multilayer Neural Networks (MLNNs) and Support Vector Regressions (SVRs) are evaluated using as a target dataset information of up to nine different water quality parameters. The most relevant input combinations were extracted using wrapper feature selection methods which simplified the structure of the model, resulting in a more accurate and efficient procedure. Although the performance in the validation phase showed that SVR models obtained better results than MLNNs, experimental results indicated that both ML algorithms provide satisfactory results in the prediction of Chl-a concentration, reaching up to 0.7 R-CV(2) (cross-validated coefficient of determination) for the best-fit models.This research was partially funded by the Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia under Project 20813/PI/18, and by Spanish Ministry of Science, Innovation and Universities under grants RTI2018-096384-B-I00 and RTC-2017-6389-5.Jimeno-Sáez, P.; Senent-Aparicio, J.; Cecilia-Canales, JM.; Pérez-Sánchez, J. (2020). Using Machine-Learning Algorithms for Eutrophication Modeling: Case Study of Mar Menor Lagoon (Spain). International Journal of Environmental research and Public Health (Online). 17(4):1-14. https://doi.org/10.3390/ijerph17041189S114174Pérez-Ruzafa, A., Pérez-Ruzafa, I. M., Newton, A., & Marcos, C. (2019). Coastal Lagoons: Environmental Variability, Ecosystem Complexity, and Goods and Services Uniformity. Coasts and Estuaries, 253-276. doi:10.1016/b978-0-12-814003-1.00015-0Kennish, M. J. (2015). Coastal Lagoons. Encyclopedia of Earth Sciences Series, 140-143. doi:10.1007/978-94-017-8801-4_47García-Ayllón, S. (2019). New Strategies to Improve Co-Management in Enclosed Coastal Seas and Wetlands Subjected to Complex Environments: Socio-Economic Analysis Applied to an International Recovery Success Case Study after an Environmental Crisis. Sustainability, 11(4), 1039. doi:10.3390/su11041039Le Moal, M., Gascuel-Odoux, C., Ménesguen, A., Souchon, Y., Étrillard, C., Levain, A., … Pinay, G. (2019). Eutrophication: A new wine in an old bottle? Science of The Total Environment, 651, 1-11. doi:10.1016/j.scitotenv.2018.09.139Alcolea, A., Contreras, S., Hunink, J. E., García-Aróstegui, J. L., & Jiménez-Martínez, J. (2019). Hydrogeological modelling for the watershed management of the Mar Menor coastal lagoon (Spain). Science of The Total Environment, 663, 901-914. doi:10.1016/j.scitotenv.2019.01.375Nixon, S. W. (1995). Coastal marine eutrophication: A definition, social causes, and future concerns. Ophelia, 41(1), 199-219. doi:10.1080/00785236.1995.10422044Huang, J., Gao, J., & Zhang, Y. (2015). Combination of artificial neural network and clustering techniques for predicting phytoplankton biomass of Lake Poyang, China. Limnology, 16(3), 179-191. doi:10.1007/s10201-015-0454-7Canfield, D. E. (1983). PREDICTION OF CHLOROPHYLL A CONCENTRATIONS IN FLORIDA LAKES: THE IMPORTANCE OF PHOSPHORUS AND NITROGEN. Journal of the American Water Resources Association, 19(2), 255-262. doi:10.1111/j.1752-1688.1983.tb05323.xPhillips, G., Pietiläinen, O.-P., Carvalho, L., Solimini, A., Lyche Solheim, A., & Cardoso, A. C. (2008). Chlorophyll–nutrient relationships of different lake types using a large European dataset. Aquatic Ecology, 42(2), 213-226. doi:10.1007/s10452-008-9180-0EL PAÍS https://elpais.com/elpais/2019/10/22/inenglish/1571743580_215496.htmlGarcía-Ayllón, S. (2017). Integrated management in coastal lagoons of highly complexity environments: Resilience comparative analysis for three case-studies. Ocean & Coastal Management, 143, 16-25. doi:10.1016/j.ocecoaman.2016.10.007Garcia-Ayllon, S. (2018). The Integrated Territorial Investment (ITI) of the Mar Menor as a model for the future in the comprehensive management of enclosed coastal seas. Ocean & Coastal Management, 166, 82-97. doi:10.1016/j.ocecoaman.2018.05.004Pérez-Ruzafa, A., Campillo, S., Fernández-Palacios, J. M., García-Lacunza, A., García-Oliva, M., Ibañez, H., … Marcos, C. (2019). Long-Term Dynamic in Nutrients, Chlorophyll a, and Water Quality Parameters in a Coastal Lagoon During a Process of Eutrophication for Decades, a Sudden Break and a Relatively Rapid Recovery. Frontiers in Marine Science, 6. doi:10.3389/fmars.2019.00026Iglesias, C., Martínez Torres, J., García Nieto, P. J., Alonso Fernández, J. R., Díaz Muñiz, C., Piñeiro, J. I., & Taboada, J. (2013). Turbidity Prediction in a River Basin by Using Artificial Neural Networks: A Case Study in Northern Spain. Water Resources Management, 28(2), 319-331. doi:10.1007/s11269-013-0487-9Najah, A., El-Shafie, A., Karim, O. A., & El-Shafie, A. H. (2012). Application of artificial neural networks for water quality prediction. Neural Computing and Applications, 22(S1), 187-201. doi:10.1007/s00521-012-0940-3Li, X., Cheng, Z., Yu, Q., Bai, Y., & Li, C. (2017). Water-Quality Prediction Using Multimodal Support Vector Regression: Case Study of Jialing River, China. Journal of Environmental Engineering, 143(10), 04017070. doi:10.1061/(asce)ee.1943-7870.0001272Su, J., Wang, X., Zhao, S., Chen, B., Li, C., & Yang, Z. (2015). A Structurally Simplified Hybrid Model of Genetic Algorithm and Support Vector Machine for Prediction of Chlorophyll a in Reservoirs. Water, 7(12), 1610-1627. doi:10.3390/w7041610Abba, S. I., Hadi, S. J., & Abdullahi, J. (2017). River water modelling prediction using multi-linear regression, artificial neural network, and adaptive neuro-fuzzy inference system techniques. Procedia Computer Science, 120, 75-82. doi:10.1016/j.procs.2017.11.212Juntunen, P., Liukkonen, M., Pelo, M., Lehtola, M. J., & Hiltunen, Y. (2012). Modelling of Water Quality: An Application to a Water Treatment Process. Applied Computational Intelligence and Soft Computing, 2012, 1-9. doi:10.1155/2012/846321Li, X., Sha, J., & Wang, Z. (2016). A comparative study of multiple linear regression, artificial neural network and support vector machine for the prediction of dissolved oxygen. Hydrology Research, 48(5), 1214-1225. doi:10.2166/nh.2016.149Charulatha, G., Srinivasalu, S., Uma Maheswari, O., Venugopal, T., & Giridharan, L. (2017). Evaluation of ground water quality contaminants using linear regression and artificial neural network models. Arabian Journal of Geosciences, 10(6). doi:10.1007/s12517-017-2867-6Keller, S., Maier, P., Riese, F., Norra, S., Holbach, A., Börsig, N., … Hinz, S. (2018). Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity. International Journal of Environmental Research and Public Health, 15(9), 1881. doi:10.3390/ijerph15091881Li, X., Sha, J., & Wang, Z.-L. (2017). Chlorophyll-A Prediction of Lakes with Different Water Quality Patterns in China Based on Hybrid Neural Networks. Water, 9(7), 524. doi:10.3390/w9070524Yi, H.-S., Park, S., An, K.-G., & Kwak, K.-C. (2018). Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea. International Journal of Environmental Research and Public Health, 15(10), 2078. doi:10.3390/ijerph15102078Nazeer, M., Bilal, M., Alsahli, M., Shahzad, M., & Waqas, A. (2017). Evaluation of Empirical and Machine Learning Algorithms for Estimation of Coastal Water Quality Parameters. ISPRS International Journal of Geo-Information, 6(11), 360. doi:10.3390/ijgi6110360Erena, Domínguez, Aguado, Soria, & García-Galiano. (2019). Monitoring Coastal Lagoon Water Quality Through Remote Sensing: The Mar Menor as a Case Study. Water, 11(7), 1468. doi:10.3390/w11071468García-Oliva, M., Marcos, C., Umgiesser, G., McKiver, W., Ghezzo, M., De Pascalis, F., & Pérez-Ruzafa, A. (2019). Modelling the impact of dredging inlets on the salinity and temperature regimes in coastal lagoons. Ocean & Coastal Management, 180, 104913. doi:10.1016/j.ocecoaman.2019.104913López-Ballesteros, A., Senent-Aparicio, J., Srinivasan, R., & Pérez-Sánchez, J. (2019). Assessing the Impact of Best Management Practices in a Highly Anthropogenic and Ungauged Watershed Using the SWAT Model: A Case Study in the El Beal Watershed (Southeast Spain). Agronomy, 9(10), 576. doi:10.3390/agronomy9100576Senent-Aparicio, J., Pérez-Sánchez, J., García-Aróstegui, J., Bielsa-Artero, A., & Domingo-Pinillos, J. (2015). Evaluating Groundwater Management Sustainability under Limited Data Availability in Semiarid Zones. Water, 7(12), 4305-4322. doi:10.3390/w7084305Navarro, M. C., Pérez-Sirvent, C., Martínez-Sánchez, M. J., Vidal, J., Tovar, P. J., & Bech, J. (2008). Abandoned mine sites as a source of contamination by heavy metals: A case study in a semi-arid zone. Journal of Geochemical Exploration, 96(2-3), 183-193. doi:10.1016/j.gexplo.2007.04.011Conesa, H. M., & Jiménez-Cárceles, F. J. (2007). The Mar Menor lagoon (SE Spain): A singular natural ecosystem threatened by human activities. Marine Pollution Bulletin, 54(7), 839-849. doi:10.1016/j.marpolbul.2007.05.007Domingo-Pinillos, J., Senent-Aparicio, J., García-Aróstegui, J., & Baudron, P. (2018). Long Term Hydrodynamic Effects in a Semi-Arid Mediterranean Multilayer Aquifer: Campo de Cartagena in South-Eastern Spain. Water, 10(10), 1320. doi:10.3390/w10101320Stefanova, A., Hesse, C., & Krysanova, V. (2015). Combined Impacts of Medium Term Socio-Economic Changes and Climate Change on Water Resources in a Managed Mediterranean Catchment. Water, 7(12), 1538-1567. doi:10.3390/w7041538Velasco, J., Lloret, J., Millan, A., Marin, A., Barahona, J., Abellan, P., & Sanchez-Fernandez, D. (2006). Nutrient And Particulate Inputs Into The Mar Menor Lagoon (Se Spain) From An Intensive Agricultural Watershed. Water, Air, and Soil Pollution, 176(1-4), 37-56. doi:10.1007/s11270-006-2859-8García-Oliva, M., Pérez-Ruzafa, Á., Umgiesser, G., McKiver, W., Ghezzo, M., De Pascalis, F., & Marcos, C. (2018). Assessing the Hydrodynamic Response of the Mar Menor Lagoon to Dredging Inlets Interventions through Numerical Modelling. Water, 10(7), 959. doi:10.3390/w10070959Wei, B., Sugiura, N., & Maekawa, T. (2001). Use of artificial neural network in the prediction of algal blooms. Water Research, 35(8), 2022-2028. doi:10.1016/s0043-1354(00)00464-4(2000). Artificial Neural Networks in Hydrology. I: Preliminary Concepts. Journal of Hydrologic Engineering, 5(2), 115-123. doi:10.1061/(asce)1084-0699(2000)5:2(115)Jimeno-Sáez, P., Senent-Aparicio, J., Pérez-Sánchez, J., & Pulido-Velazquez, D. (2018). A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain. Water, 10(2), 192. doi:10.3390/w10020192Nguyen, V. D., Tan, R. R., Brondial, Y., & Fuchino, T. (2007). Prediction of vapor–liquid equilibrium data for ternary systems using artificial neural networks. Fluid Phase Equilibria, 254(1-2), 188-197. doi:10.1016/j.fluid.2007.03.014Bekkari, N., & Zeddouri, A. (2019). Using artificial neural network for predicting and controlling the effluent chemical oxygen demand in wastewater treatment plant. Management of Environmental Quality: An International Journal, 30(3), 593-608. doi:10.1108/meq-04-2018-0084Zhang, Y., Gao, X., Smith, K., Inial, G., Liu, S., Conil, L. B., & Pan, B. (2019). Integrating water quality and operation into prediction of water production in drinking water treatment plants by genetic algorithm enhanced artificial neural network. Water Research, 164, 114888. doi:10.1016/j.watres.2019.114888Naghibi, S. A., Ahmadi, K., & Daneshi, A. (2017). Application of Support Vector Machine, Random Forest, and Genetic Algorithm Optimized Random Forest Models in Groundwater Potential Mapping. Water Resources Management, 31(9), 2761-2775. doi:10.1007/s11269-017-1660-3Kuhn, M. (2008). Building Predictive Models inRUsing thecaretPackage. 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Biodegradable Chitosan-Derived Thioureas as Recoverable Supported Organocatalysts – Application to the Stereoselective Aza-Henry Reaction

Producción CientíficaEight different biodegradable chitosan-supported bifunctional chiral thioureas have been prepared as a greener and more sustainable alternative to those supported on petrochemical-derived polymers. These organocatalysts promoted an enantioselective aza-Henry reaction, which afforded good product yields with moderate to high enantioselectivity. The activity and stereodirecting ability of these materials were dependent on the accessibility of the reactants to the active site and increased with the length of the tether that connected the thiourea to the biopolymer. The best performing catalyst was able to be recovered and recycled five times without a loss of activity.2018-10-10Ministerio de Economía, Industria y Competitividad (Project CTQ 2014-59870-P

A methodology to select suppliers to increase sustainability within supply chains

[EN] Sustainability practice within supply chains remains in an early development phase. Enterprises still need tools that support the integration of sustainability strategy into their activity, and to align their sustainability strategy with the supplier selection process. This paper proposes a methodology using a multi-criteria technique to support supplier selection decisions by taking two groups of inputs that integrate sustainability performance: supply chain performance and supplier assessment criteria. With the proposed methodology, organisations will have a tool to select suppliers based on their development towards sustainability and on their alignment with the supply chain strategy towards sustainability. The methodology is applied to an agri-food supply chain to assess sustainability in the supplier selection process.The authors of this publication acknowledge the contribution of Project GV/2017/065 'Development of a decision support tool for the management and improvement of sustainability in supply chains', funded by the Regional Valencian Government. Also, the authors acknowledge Project 691249, RUC-APS: Enhancing and implementing knowledge-based ICT solutions within high risk and uncertain conditions for agriculture production systems (www.ruc-aps.eu), funded by the European Union according to funding scheme H2020-MSCA-RISE-2015.Verdecho Sáez, MJ.; Alarcón Valero, F.; Pérez Perales, D.; Alfaro Saiz, JJ.; Rodríguez Rodríguez, R. (2021). A methodology to select suppliers to increase sustainability within supply chains. 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Int J Prod Perform Manag 56(4):305–334Awasthi A, Govindan K, Gold S (2018) Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. Int J Prod Econ 195:106–117Azadnia AH, Ghadimi P, Zameri M, Saman M, Wong KY, Heavey C (2013) An integrated approach for sustainable supplier selection using fuzzy logic and fuzzy AHP. Appl Mech Mater 315:206–221Azimifard A, Moosavirad SH, Ariafar S (2018) Selecting sustainable supplier countries for Iran’s steel industry at three levels by using AHP and TOPSIS methods. Resour Pol 57:30–44Bai C, Sarkis J (2010) Integrating sustainability into supplier selection with grey system and rough set methodologies. Int J Prod Econ 124:252–264Bhagwat R, Sharma MK (2007) Performance measurement of supply chain management: a balanced scorecard approach. Comput Ind Eng 53(1):43–62Bititci US, Mendibil K, Martinez V, Albores P (2005) Measuring and managing performance in extended enterprises. 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