Although ultrafiltration membranes have been used for the separation of macromolecules and colloids from solutions, this process has a limited application in the removal of dyes present in coloured discharges of textile industry, as these typically have much lower molecular weight than the molecular cut-off of the membranes (MWCO). In the present work, we have evaluated the behaviour of a polysulfone ultrafiltration membrane in the removal of different dyes from aqueous solutions (Congo red, methyl green and amaranth). Different variables (tangential flow rate, concentration of dye and pH of the feed) were studied to determine their influence on the separation processes (permeate flux and rejection coefficient). The results show that Congo red is easily removed with a GR60PP membrane (MWCO = 25 kDa), whereas methyl green and amaranth show rejection coefficient values of approximately 25.78% and 13.85%, respectively, at neutral pH. Also, an interesting effect is observed for the rejection coefficient for methyl green at different pH values. In addition, several treatments were performed to the membrane so as to modify its surface, trying to improve the values obtained for permeate flux and rejection rate.

Three-dimensional digital models of historical buildings must seamlessly integrate a wide array of data from diverse sources, including point clouds, alphanumeric information, 2D and 3D representations, BIM, GIS, images, sensor data, and real-time information streams, among other heterogeneous resources. Centralizing and presenting this multifaceted information cohesively is fundamental for fostering a comprehensive understanding and analysis of these historical monuments. In this context, the article introduces an automated process (Scan-to-HBIM) tailored specifically to transform point clouds into threedimensional models within BIM environments. This innovative approach not only enhances the accuracy in representing historic buildings but also significantly amplifies the level of detail (LoD), enabling a more nuanced representation of architectural structures. The article delves into the Scan-to-HBIM process, elucidating its relevance in the broader context of digitization and preservation of historic buildings, with a particular focus on its application to a sample point cloud. Furthermore, it underscores the pivotal advantages of this approach, emphasizing its proficiency in managing diverse datasets, elevating the level of detail, and exploring practical applications in both BIM and GIS realms.

Accurate documentation of the geometry of historical buildings presents a considerable challenge, especially when dealing with complex structures like the Metropolitan Cathedral of Valencia. Advanced technologies such as 3D laser scanning has enabled detailed spatial data capture. Still, efficient handling of this data remains challenging due to the volume and complexity of the information. This study explores the application of clustering techniques employing Machine Learning-based algorithms, such as DBSCAN and K-means, to automate the process of point cloud analysis and modelling, focusing on identifying and extracting floor plans. The proposed methodology includes data geo-referencing, culling points to reduce file size, and automated floor plan extraction through filtering and segmentation. This approach aims to streamline the documentation and modelling of historical buildings and enhance the accuracy of historical architectural surveys, significantly contributing to the preservation of cultural heritage by providing a more efficient and accurate method of data analysis.

This paper presents a methodology for using geospatial tools to enact efficient tourism planning and management in streets and other public spaces in historic centres. The study uses 3D laser scanning, GIS, and spatial data processing techniques to analyse the visitor carrying capacity of streets near cultural attractions. The methodology was tested on Miguelete Street in València (Spain), next to the Cathedral. The results show that these digital tools are efficient and accurate for the spatial analysis of visitor carrying capacity studies.

En la actualidad, la información sobre los edificios históricos se encuentra representada como una colección de documentos con diversas fuentes, elaborados por diferentes profesionales. Así, se propone la inclusión de la metodología HBIM con los objetivos fundamentales de agilizar y automatizar la manipulación de la información, facilitando la lectura de los edificios complejos. En este artículo se muestran las contribuciones de la metodología HBIM para la elaboración de la hipótesis de fases históricas constructivas de la Iglesia de San Lorenzo de Valencia. El método de trabajo utilizado ha sido la propuesta de un modelo de actuación aplicado a la edificación, que tiene origen en el periodo medieval y ha sufrido diversas transformaciones a lo largo de su historia.

The rapid development of digital technologies has significantly transformed architectural heritage research through the emergence of Historic Building Information Modeling (HBIM) and Historic Digital Twin (HDT) approaches. This study aims to analyze and compare the scientific evolution, collaboration patterns, and technological trends of these two research domains between 2019 and 2025. A comparative bibliometric analysis was conducted using publications retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases. The results indicate that the HBIM domain represents a more mature and consolidated research field characterized by stable publication growth and strong international collaboration networks, particularly in European countries. The findings also reveal a strong conceptual relationship between both domains, suggesting that HBIM currently functions as a foundational framework for the development of HDT systems.