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Obtaining durable materials that lengthen the service life of constructions and thereby contribute to sustainability requires research into products that improve the durability of cementitious materials under aggressive conditions. This paper studies the effects of sulfuric acid exposure on four mortar types (control mortar, mortar with nanosilica, mortar with zinc stearate, and mortar with an ethyl silicate coating), and evaluates which of them have better performance against the acid attack. After 28 days of curing, the samples were exposed to a sulfuric acid attack by immersing them in a 3% w/w of H2SO4 solution. Physical changes (mass loss, ultrasonic pulse velocity, open porosity, and water absorption), and mechanical changes (compressive strength) were determined after the sulfuric acid exposure. A scanning electron microscope (SEM) was used to characterize the morphology of the surface mortars after the exposure. The control mortar had the highest compressive strength after the acid attack, although of the four types, the zinc stearate mortar showed the lowest percentage of strength loss. The zinc stearate mortar had the lowest mass loss after the acid exposure; moreover, it had the lowest capillary water absorption coefficient (demonstrating its hydrophobic effect) both in a non-aggressive environment and acid attack.

The present paper focuses on the study of mortar samples where expansions with thaumasite formation occur as a consequence of sulphate attack. The samples correspond to a masonry mortar used in a rural construction located in the Spanish province of Toledo made of cement with limestone filler addition CEM II/AL. Composition and microstructure of the mortars have been analysed by means of scanning electron microscopy (SEM) using secondary and backscattered electrons (BSE) and X-ray diffraction (XRD). The results show that aggregates are contaminated with gypsum, which is the source of the sulphates for the internal attack. It seems that thaumasite is formed through an ettringite transformation where aluminium atoms are replaced with silicon atoms by means of a solid solution. The study highlights that thaumasite can be formed in warm weather through an internal sulphate attack due to gypsum contamination of aggregates.

Currently, political policies aimed at curbing the abuse of natural resources have given rise to a conscientiousness leading to the reevaluation of wastes. Wastes generated from previous mining operations greatly impact the environment, often leaving a legacy of elevated concentrations of heavy metals in the surrounding soil and water. In this study, two types of waste from the mining district of La Union (Spain) were used to study their use as a component of road wearing courses. The physical and mechanical characteristics were determined to identify the optimal content of bitumen, as well as the fatigue resistance using the four-point beam fatigue test, in all the mixtures manufactured. The mine tailings exhibited adequate physical and mechanical properties to be utilized as a coarse aggregate for a wearing course. The results indicate that one of the studied mine tailing forms could be used as a wearing course component, since it has properties similar to a control mix that is typically used in wearing course construction.

Using durable materials is a sustainable solution for extending the lifetime of constructions. The use of crystalline admixtures makes cementitious materials more durable. They plug pores, capillary tracts and microcracks, blocking the entrance of water due to the formation of crystals that prevent the penetration of liquids. The literature has covered the performance of these admixtures on concrete, but studies on mortars are still scarce. The aim of this study is to investigate the effect of an aggressive environment (sulphuric acid solution—3 wt%) on mortars produced with different percentages of a crystalline admixture (1%, 1.5% and 2% by weight of cement content). Physical and mechanical properties were studied after immersing the mortars in a H2SO4 solution for 90 days. It was found that, after a 90-day sulphuric acid exposure, mortars with the crystalline admixture showed greater compressive strength than the control mortar, besides exhibiting lower mass loss. However, the crystalline admixture did not produce any significant effect on the capillary water absorption coefficient. In a nonaggressive environment, and in the short term, the crystalline admixture did not have a significant effect on the compressive strength, the capillary water absorption coefficient or the ultrasonic pulse velocity.

In view of the global sustainable development, it is imperative that supplementary cementing materials (SCM) be used for replacing cement in the concrete industry and several researchers have shown that mineral admixtures can enhance the workability of lightweight aggregate concrete (LWAC) mixture and its strength. In view of the beneficial effects of using SCM in LWAC, this article aims to verify the possible influence of the use of different types of SCM in the segregation phenomenon of LWAC. Three different SCM were studied: Silica Fume (SF), Fly Ash (FA) and Posidonia oceanica Ash (PA). For each SCM, three mixtures were prepared, considering three different percentage substitutions of cement. An image analysis technique was applied to estimate the segregation in each sample. The results show that a substitution of cement by other materials with different grain size, considering a constant water binder ratio, may also result in a variation of the consistency of concrete and the viscosity of the mortar matrix, which may contribute to increase or reduce segregation.

The use of RGB-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and color information using the same device. In this paper, we present a comparative analysis of the most important methods used in the literature for the registration of subsequent RGB-D video frames in static scenarios. The analysis begins by explaining the characteristics of the registration problem, dividing it into two representative applications: scene modeling and object reconstruction. Then, a detailed experimentation is carried out to determine the behavior of the different methods depending on the application. For both applications, we used standard datasets and a new one built for object reconstruction.

The problem of processing point cloud sequences is considered in this work. In particular, a system that represents and tracks objects in dynamic scenes acquired using low-cost sensors such as the Kinect is presented. An efficient neural network-based approach is proposed to represent and estimate the motion of 3D objects. This system addresses multiple computer vision tasks such as object segmentation, representation, motion analysis and tracking. The use of a neural network allows the unsupervised estimation of motion and the representation of objects in the scene. This proposal avoids the problem of finding corresponding features while tracking moving objects. A set of experiments are presented that demonstrate the validity of our method to track 3D objects. Moreover, an optimization strategy is applied to achieve real-time processing rates. Favorable results are presented demonstrating the capabilities of the GNG-based algorithm for this task. Some videos of the proposed system are available on the project website ( http://www.dtic.ua.es/~sorts/3d_object_tracking/ ).

In this work, we propose a new dataset for 3D object recognition using the new high-resolution Kinect V2 sensor and some other popular low-cost devices like PrimeSense Carmine. Since most already existing datasets for 3D object recognition lack some features such as 3D pose information about objects in the scene, per pixel segmentation or level of occlusion, we propose a new one combining all this information in a single dataset that can be used to validate existing and new 3D object recognition algorithms. Moreover, with the advent of the new Kinect V2 sensor we are able to provide high-resolution data for RGB and depth information using a single sensor, whereas other datasets had to combine multiple sensors. In addition, we will also provide semiautomatic segmentation and semantic labels about the different parts of the objects so that the dataset could be used for testing robot grasping and scene labeling systems as well as for object recognition.

Over the past three decades, exoplanet research has delivered an extensive census of planets spanning a wide range of masses, sizes, and orbital configurations. Despite this progress, the physical interpretation of these populations remains severely limited, as precise constraints on planetary masses, interior structures, and atmospheres are available only for a small, highly selected subset of targets. As a result, most known exoplanets remain physically ambiguous, preventing the construction of robust population-level trends and limiting our understanding of planet formation, evolution, and habitability. In the coming decades, missions such as PLATO, Earth 2.0, and the Nancy Grace Roman Space Telescope will dramatically expand the number of exoplanets detected. However, without a corresponding capability to characterise planetary masses and atmospheres at scale, these discoveries will remain largely detection-driven. Current and planned facilities, including JWST and ELT-class instruments, excel at detailed studies of individual systems but are intrinsically unsuited for large, homogeneous surveys. This white paper identifies population-level physical characterisation as a fundamental science challenge for the 2040s and motivates the need for a new observational paradigm. We outline how photonics-enabled, modular telescope architectures can deliver the survey speed, stability, and scalability required to jointly probe planetary interiors and atmospheres across statistically meaningful samples, thereby enabling a comprehensive and physically grounded understanding of planetary systems.