Diagnosis, management, and treatment of a heritage-built environment in South Chile

In Chile, photography arrived at the end of the 19th century together with the establishment of settlements of migrants from central Europe to southern Chile. The aims of this study are: (i) contextualise functional states of existing buildings in a specific sector of the historic Valdivia city centre; (ii) determine the state of conservation of the 42 cases under study; (iii) conduct qualitative and quantitative analyses of the main pathologies presented in the sample; (iv) perform an analysis focused on the urban context according to façade alignment, façade visibility index, and ratio of height versus street width; and (v) comparatively analyse the results achieved. This research reflects the importance of developing innovative procedures and mitigation strategies focused on preventive maintenance actions and future control systems that can maximise the resilience of a specific local context (Los Ríos region) and its surroundings. This study revealed that the number of pathologies detected was directly proportional to the state of conservation of the cases, classified by the functional service life model. Properties in Condition C were mainly affected by pathologies of a structural nature, which indicates that their functionality is not guaranteed, and a deeper inspection is needed for conservation and preservation actions. First published online 12 December 202

Solutions of the attraction-repulsion-chemotaxis system with nonlinear diffusion

In this study, we consider the well-posedness of the attraction-repulsion chemotaxis system. This paper explores the dynamics of species movement in reaction to two chemically opposing substances, incorporating nonlinear diffusion. Our primary objective is to establish the existence of a global-in-time weak solution for the proposed model in an unbounded three-dimensional spatial domain. Our study has confirmed the existence of a global-in-time weak solution for the proposed system in three dimensions. Furthermore, we demonstrate that global-in-time weak solutions are also attainable for the proposed system in a bounded domain with a smooth boundary

The perspective of the aviation organizations on the ICAO’s SMS framework: a spherical fuzzy AHP study

The International Civil Aviation Organization (ICAO) has developed a Safety Management System (SMS) to ensure safety in aviation organizations. SMS components are essential to overall safety performance in aviation organizations. However, the importance of these components may be perceived differently among different aviation organizations. This study aims to evaluate the perception of the importance of ICAO SMS components in aviation organizations in Turkey using the Global Fuzzy Analytical Hierarchical Process (SFAHP). The sample of the research consists of managers and employees of different aviation organizations. Data were collected using a survey questionnaire and analyzed via the SFAHP method. The results of this study indicate that all ICAO SMS components were considered important by the participants. In this context, hazard identification, training, and education and safety risk assessment and mitigation are the most important components. The study also revealed that the perception of the importance of SMS components differs between different types of aviation organizations. The SMS components with the highest deviation are listed as the appointment of key safety personnel, safety risk assessment and mitigation and management commitment. Therefore, the study provides valuable information regarding the perception of the importance of ICAO SMS components in aviation organizations

On the stability and efficiency of high-order parallel algorithms for 3D wave problems

In this work, we investigate the stability conditions for four new high-order ADI type schemes proposed to solve 3D wave equations with a non-constant sound speed coefficient. This analysis is mainly based on the spectral method, therefore a basic benchmark problem is formulated with a constant sound speed coefficient. For a case of general non-constant coefficient the stability analysis is done by using the energy method. Our main conclusion states that the selected ADI type schemes use different factorization operators (mainly due to the need to approximate the artificial boundary conditions on the split time levels), but the general structure of the stability factors are similar for all schemes and thus the obtained CFL conditions are also very similar. The second goal is to compare the accuracy and efficiency of the selected ADI solvers. This analysis also includes parallel versions of these schemes. Two schemes are selected as the most effective and accurate

Enhancing land use classification with hybrid machine learning and satellite imagery

The growing accessibility of satellite imagery and the rapid evolution of machine learning (ML) techniques have significantly advanced land use classification for environmental monitoring. However, challenges such as cloud coverage, varying image resolutions, and seasonal changes continue to hinder classification accuracy and consistency. This study aims to improve land use classification by proposing an integrated cloud interpolation, vegetation indices and ML based approach for classification of Sentinel-2 (S2) satellite data across the Baltic States. Specifically, a spatiotemporal interpolation module is introduced that reconstructs cloud-obscured pixels using multi-temporal coherence and derives optimized vegetation-index composites to enhance class separability under varying seasonal conditions. In order to achieve this aim and to choose the best ML algorithm for land use classification, we compare the performance of three classification algorithms, i.e., Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machines (SVM), and evaluate their effectiveness in handling noisy and incomplete data. Our experimental results show that all three methods achieve strong classification accuracy, with RF exceeding 90%, while KNN and SVM also demonstrate competitive results. These methodological enhancements have been demonstrated to reduce cloud-induced misclassification and provide a scalable, transferable framework for operational land-use mapping in challenging atmospheric and seasonal contexts. These findings highlight the robustness of the proposed approach and provide valuable insights for future applications of ML in land use classification and environmental analysis.

PHASE: a Matlab-based software for the DInSAR PS processing

The availability of free Synthetic Aperture Radar (SAR) images, like the ones delivered by the ESA Copernicus Sentinel-1 satellites, has led to the development of several processing tools, some of which are also free and open source. In this framework, when analyzing Sentinel data, the ESA SNAP software is usually required for data preprocessing, while, in the context of free and open source (FOS), Persistent Scatterer Interferometry (PSI) analysis can be performed by StaMPS (released by Stanford University). The workflow could be completed by the snap2stamps package, aiming at integrating the two main software packages. However, these tools are not designed to automate all the required steps to perform a complete PSI analysis. For this reason, the aim of this work is to develop PHASE (Persistent scatterer Highly Automated Suite for Environmental monitoring), a Matlab-based software suite that relies on already available FOS software, properly updated, enhanced and integrated, all accessible and customizable through a simple GUI. The focus is on minimizing the user interaction with the software, thus decreasing potential sources of error, while improving processing repeatability. The user will therefore primarily be responsible for configuring the processing parameters. Indeed, a streamlined procedure has been established, covering the entire process from downloading the SAR images to exporting the PS time series into a simple table format. In the paper, we present the developed software, highlighting its strengths compared to the status quo, while also providing a short example of successful application of the entire procedure

Double trouble: Time-varying connectedness between stock and housing markets

Joint new records in the stock and housing markets are now gradually becoming a focal point of controversy in Taiwan. Based on the local heterogeneity of real estate assets, this study proposes setting up a two-market transmission mechanism between the stock and city-level housing markets to fully reply to this question. The estimation results using the Diebold-Yilmaz spillover method offer some critical information: the fact that the overheated housing market is precisely caused by the Taiwan stock market, which serves as evidence of the wealth effect. As far as the housing network is concerned, it is interesting to note that housing prices in Taipei as the source city spill out from near to far: New Taipei, Taichung and ultimately Kaohsiung. All these things make it clear that the authorities pay special attention to the status of the stock market as well as to inter-city differences in terms of housing spillovers

Experimental and theoretical investigation of tension stiffening and curvature in RC beams with extended concrete cover

Accurate assessment of tension stiffening is important for predicting deflection and crack width in RC structures. Earlier studies by the authors have shown that an extended cover thickness increases tension stiffening in bending RC members. The current study experimentally and theoretically investigates curvature and tension stiffening in RC beams nominally having a 50 mm cover for 32 mm bars of tensile reinforcement. The four-point bending tests were carried out on square section (400×400 mm) RC beams. Mean experimental curvatures were obtained for the pure bending zone by different approaches, namely, from a mid-point deflection and from strains at several horizontal layers measured either by LVDT or DIC technique. The tension stiffening effect in the test beams was quantified by inversely calculating the resultant internal force of tensile concrete, Nct, using the test moment – curvature diagrams. Tension stiffening is characterized by parameter β0 indicating the ratio of β0 = M / Mcr at which the force Nct reaches zero. The condition Nct = 0 represents the bending stiffness of a fully cracked RC section. Earlier studies by the authors have shown that parameter β0 equals to 3 for the beams with a typical cover thickness (25–35 mm). The current study has demonstrated that for the beams having nominal cover thickness of 50 mm and bar diameter of 32 mm, parameter β0 reached rather high values indicating a little degradation of tension stiffening with increasing load

GIS based ground water assessment of Nilakkottai Taluk, Tamil Nadu, India: hydrogeochemistry and statistical perspective

Water quality is imperative for drinking and agriculture purposes in order to meet the increasing requirements for water. The systematic assessment of groundwater quality in Nilakkottai Taluk, Dindigul District, Tamil Nadu, was performed. In order to ascertain the quality of the study area’s groundwater, various water quality indices, spatial distribution maps, multivariate statistical analysis, and hydrofacies diagrams have been contemplated. 40 samples were collected and analysed for 20 water quality parameters, using the standard techniques. The quality results of the irrigation analysis showed that the groundwater samples were satisfactory for agricultural use. The deduction of four principal components denotes that hydrogeochemical processes and anthropogenic inputs were the main controlling factors. The durov plot demonstrated the dominance of Ca-HCO3 type groundwater, indicating a weathering process through fresh water recharge. This study insisted that majority of the samples satisfactory for crop yield and need to be protected from further contamination

Development of an automated surface crack detection and BIM-integrated management system for concrete bridges

Bridge inspection work typically requires inspectors to capture hundreds to thousands of images, consuming substantial time for review. This research developed an “Automated Crack Image Cloud Detection System” and the “Auto Predictor” application, enabling automatic crack identification and deterioration image recognition through uploads. This platform integrates with the “Bridge BIM Cloud Management System”, connecting crack information with three-dimensional models. Engineers can create BIM models based on structural design drawings, while inspectors can photograph cracks and integrate relevant information. The study utilized deterioration images from long-term bridge inspections in Taiwan, covering various real-world environmental conditions. Through effective deterioration labeling strategies and comparing YOLOv4 and YOLOv7 algorithms with recommended parameters, an optimal model was obtained for system implementation. Research results demonstrate that the “Automated Crack Image Cloud Detection System” successfully identified cracks in bridge inspections and short beam shear test specimens. The deep integration with the “Bridge BIM Cloud Management System” enables automatic component crack identification and generates location charts, providing decision-makers with intuitive visual data. The YOLOv7-based model achieved a mean Average Precision (mAP) of 87.64%, significantly improving bridge inspection efficiency and demonstrating exceptional application potential