Neural Colour Correction for Indoor 3D Reconstruction Using RGB-D Data.

With the rise in popularity of different human-centred applications using 3D reconstruction data, the problem of generating photo-realistic models has become an important task. In a multiview acquisition system, particularly for large indoor scenes, the acquisition conditions will differ along the environment, causing colour differences between captures and unappealing visual artefacts in the produced models. We propose a novel neural-based approach to colour correction for indoor 3D reconstruction. It is a lightweight and efficient approach that can be used to harmonize colour from sparse captures over complex indoor scenes. Our approach uses a fully connected deep neural network to learn an implicit representation of the colour in 3D space, while capturing camera-dependent effects. We then leverage this continuous function as reference data to estimate the required transformations to regenerate pixels in each capture. Experiments to evaluate the proposed method on several scenes of the MP3D dataset show that it outperforms other relevant state-of-the-art approaches.

ATOM Calibration Framework: Interaction and Visualization Functionalities.

Robotic systems are evolving to include a large number of sensors and diverse sensor modalities. In order to operate a system with multiple sensors, the geometric transformations between those sensors must be accurately estimated. The process by which these transformations are estimated is known as sensor calibration. Behind every sensor calibration approach is a formulation and a framework. The formulation is the method by which the transformations are estimated. The framework is the set of operations required to carry out the calibration procedure. This paper proposes a novel calibration framework that gives more flexibility, control and information to the user, enhancing the user interface and the user experience of calibrating a robotic system. The framework consists of several visualization and interaction functionalities useful for a calibration procedure, such as the estimation of the initial pose of the sensors, the data collection and labeling, the data review and correction and the visualization of the estimation of the extrinsic and intrinsic parameters. This framework is supported by the Atomic Transformations Optimization Method formulation, referred to as ATOM. Results show that this framework is applicable to various robotic systems with different configurations, number of sensors and sensor modalities. In addition to this, a survey comparing the frameworks of different calibration approaches shows that ATOM provides a very good user experience.

A Sequential Color Correction Approach for Texture Mapping of 3D Meshes.

Texture mapping can be defined as the colorization of a 3D mesh using one or multiple images. In the case of multiple images, this process often results in textured meshes with unappealing visual artifacts, known as texture seams, caused by the lack of color similarity between the images. The main goal of this work is to create textured meshes free of texture seams by color correcting all the images used. We propose a novel color-correction approach, called sequential pairwise color correction, capable of color correcting multiple images from the same scene, using a pairwise-based method. This approach consists of sequentially color correcting each image of the set with respect to a reference image, following color-correction paths computed from a weighted graph. The color-correction algorithm is integrated with a texture-mapping pipeline that receives uncorrected images, a 3D mesh, and point clouds as inputs, producing color-corrected images and a textured mesh as outputs. Results show that the proposed approach outperforms several state-of-the-art color-correction algorithms, both in qualitative and quantitative evaluations. The approach eliminates most texture seams, significantly increasing the visual quality of the textured meshes.

Blockchain Protocols and Edge Computing Targeting Industry 5.0 Needs.

"Industry 5.0" is the latest industrial revolution. A variety of cutting-edge technologies, including artificial intelligence, the Internet of Things (IoT), and others, come together to form it. Billions of devices are connected for high-speed data transfer, especially in a 5G-enabled industrial environment for information collection and processing. Most of the issues, such as access control mechanism, time to fetch the data from different devices, and protocols used, may not be applicable in the future as these protocols are based upon a centralized mechanism. This centralized mechanism may have a single point of failure along with the computational overhead. Thus, there is a need for an efficient decentralized access control mechanism for device-to-device (D2D) communication in various industrial sectors, for example, sensors in different regions may collect and process the data for making intelligent decisions. In such an environment, reliability, security, and privacy are major concerns as most of the solutions are based upon a centralized control mechanism. To mitigate the aforementioned issues, this paper provides the opportunities for and highlights some of the most impressive initiatives that help to curve the future. This new era will bring about significant changes in the way businesses operate, allowing them to become more cost-effective, more efficient, and produce higher-quality goods and services. As sensors are getting more accurate, cheaper, and have lower time responses, 5G networks are being integrated, and more industrial equipment and machinery are becoming available; hence, various sectors, including the manufacturing sector, are going through a significant period of transition right now. Additionally, the emergence of the cloud enables modern production models that use the cloud (both internal and external services), networks, and systems to leverage the cloud's low cost, scalability, increased computational power, real-time communication, and data transfer capabilities to create much smarter and more autonomous systems. We discuss the ways in which decentralized networks that make use of protocols help to achieve decentralization and how network meshes can grow to make things more secure, reliable, and cohere with these technologies, which are not going away anytime soon. We emphasize the significance of new design in regard to cybersecurity, data integrity, and storage by using straightforward examples that have the potential to lead to the excellence of distributed systems. This groundbreaking paper delves deep into the world of industrial automation and explores the possibilities to adopt blockchain for developing solutions for smart cities, smart homes, healthcare, smart agriculture, autonomous vehicles, and supply chain management within Industry 5.0. With an in-depth examination of various consensus mechanisms, readers gain a comprehensive understanding of the latest developments in this field. The paper also explores the current issues and challenges associated with blockchain adaptation for industrial automation and provides a thorough comparison of the available consensus, enabling end customers to select the most suitable one based on its unique advantages. Case studies highlight how to enable the adoption of blockchain in Industry 5.0 solutions effectively and efficiently, offering valuable insights into the potential challenges that lie ahead, particularly for smart industrial applications.

Extracellular Vesicles as Potential Bladder Cancer Biomarkers: Take It or Leave It?

Bladder cancer (BC) is the 10th most frequently diagnosed cancer worldwide. Although urine cytology and cystoscopy are current standards for BC diagnosis, both have limited sensitivity to detect low-grade and small tumors. Moreover, effective prognostic biomarkers are lacking. Extracellular vesicles (EVs) are lipidic particles that contain nucleic acids, proteins, and metabolites, which are released by cells into the extracellular space, being crucial effectors in intercellular communication. These particles have emerged as potential tools carrying biomarkers for either diagnosis or prognosis in liquid biopsies namely urine, plasma, and serum. Herein, we review the potential of liquid biopsies EVs' cargo as BC diagnosis and prognosis biomarkers. Additionally, we address the emerging advantages and downsides of using EVs within this framework.

Urban objects classification using Mueller matrix polarimetry and machine learning.

Detecting and recognizing different kinds of urban objects is an important problem, in particular, in autonomous driving. In this context, we studied the potential of Mueller matrix polarimetry for classifying a set of relevant real-world objects: vehicles, pedestrians, traffic signs, pavements, vegetation and tree trunks. We created a database with their experimental Mueller matrices measured at 1550 nm and trained two machine learning classifiers, support vector machine and artificial neural network, to classify new samples. The overall accuracy of over 95% achieved with this approach, with either models, reveals the potential of polarimetry, specially combined with other remote sensing techniques, to enhance object recognition.

Feeding exposure and feeding behaviour as relevant approaches in the assessment of the effects of micro(nano)plastics to early life stages of amphibians.

The sedimentation of micro and nanosized plastics is of considerable environmental relevance and the need to assess its sublethal effects to biota increasingly recognized. In their majority, as bottom, non-selective grazers, independent-feeding young life stages of amphibians, an already severely endangered worldwide group, may be particularly vulnerable to sedimented plastics. Alongside, they may be good model organisms for the assessment of the effects of micro(nano)plastics (MNPs) through ingestion. However, to our knowledge, few studies have assessed amphibians' exposure to MNPs through contaminated food or its effects in feeding behaviour assays. The available studies reveal a lack of consistent methodology: organisms, food type, media of exposure, or exposure conditions (temperature and light) in the assessment of effects. This perspective article, will address major differences found in the available studies, identifying type, size and concentrations of the polymers tested, species, and observed effects, aiming to highlight the importance of feeding exposure assays when attempting to evaluate the effect of MNPs in amphibians.

Effects of nanoplastics on zebrafish embryo-larval stages: A case study with polystyrene (PS) and polymethylmethacrylate (PMMA) particles.

Plastic production has been rising consistently in the last 30 years and with it, the presence of plastic particles in the environment. A decrease in size often increases the bioavailability and reactivity of the particles. In this study the impact of polystyrene (PS; 22 nm) and polymethylmethacrylate (PMMA; 32 nm) nanoparticles on zebrafish embryo-larval stages was assessed by studying mortality, hatching, morphological features, and biochemical endpoints (associated with neurotransmission, antioxidant status and oxidative damage, and energy metabolism) after 96 h exposure, and swimming behavior after 120 h exposure. Organisms exposed to PMMA nanoparticles exhibited higher mortality and pericardial edema than those exposed to PS nanoparticles but displayed less effects on swimming behavior. Biochemical endpoints were altered to a higher degree in organisms exposed to PS nanoparticles (acetylcholinesterase, glutathione S-transferase and catalase activities) but higher peroxidative damage was found after exposure to lower concentrations of PMMA nanoparticles. Both types of nanoparticles affected energy metabolism with higher levels of glycogen found in animals exposed to PS nanoparticles. The use of integrated biomarker response index confirmed that PS nanoparticles had a higher impact on biochemical endpoints of zebrafish.

Does parental exposure to nanoplastics modulate the response of Hediste diversicolor to other contaminants: A case study with arsenic.

Plastic pollution is a serious problem in aquatic systems throughout the world. Despite the increasing number of studies addressing the impact of macro- and microplastics on biota, there is still a significant knowledge gap regarding the effects of nanoplastics alone and in combination with other contaminants. Among the aquatic contaminants that may interact with nanoplastics is arsenic (As), a metalloid found in estuarine and coastal ecosystems, pernicious to benthic organisms. This study aimed to understand how a parental pre-exposure to 100 nm polystyrene nanoplastics (PS NPs) would influence the response of Hediste diversicolor to exposure to arsenic in terms of behaviour, neurotransmission, antioxidant defences and oxidative damage, and energy metabolism. The obtained data revealed an increase in burrowing time and a significant inhibition in cholinesterase activity in all polychaetes exposed to As, regardless of the pre-exposure to PS NPs. Oxidative status was altered particularly in parentally exposed organisms, with damage detected in terms of lipid peroxidation at 50 µg/L and protein carbonylation at 50 and 250 µg As/L exposed organisms when compared to control. Overall, data shows that parental pre-exposure to plastics influences the response of aquatic organisms, increasing their susceptibility to other contaminants. Thus, more studies should be performed with other environmental contaminants, to better understand the potential increased risk associated with the presence of nanoplastics to aquatic ecosystems.

Plasma lipemia: When the blood donor becomes a patient.

Lipemic plasma donations are not a strange phenomenon to blood bankers. According to quality standards for plasma fractionation, lipemic plasma donations must be discarded. Beyond quality control and inventory aspects, plasma lipemia is also an important risk factor for cardiovascular diseases, acute pancreatitis and is associated with overall mortality, however little attention is given to the management of these donors in the literature. A retrospective analysis of every whole blood donation that yielded lipemic plasma between January 1st 2018 and December 31st 2019 was made. The medical examination and donor history for the respective donation was reviewed and the available data was collected regarding hour of donation, gender, age, drugs and coexisting pathologies. Whether the donor was called back for a follow up evaluation regarding the lipemic plasma was also noted. Our blood center received 18274 whole blood donations of which 115 (0,63 %) were reported as having plasma lipemia, in the period of this study. Of these 115 donors, 103 (89,57 %) were male. The average age was 47,63 ± 10,65 years. A clear peak in lipemic plasma donations 4 hours after the classic lunch hours is visible. For 88,70 % of the donors, this was the first time their hypertriglyceridemia was identified. The nonfasting elevation of plasma triglycerides in these donors represents a true metabolic derangement. This is a golden opportunity for early intervention and follow up evaluation is indicated. More attention must be given during the medical evaluation to properly identify donors at risk of lipemic donations.

A Robust 3D-Based Color Correction Approach for Texture Mapping Applications.

Texture mapping of 3D models using multiple images often results in textured meshes with unappealing visual artifacts known as texture seams. These artifacts can be more or less visible, depending on the color similarity between the used images. The main goal of this work is to produce textured meshes free of texture seams through a process of color correcting all images of the scene. To accomplish this goal, we propose two contributions to the state-of-the-art of color correction: a pairwise-based methodology, capable of color correcting multiple images from the same scene; the application of 3D information from the scene, namely meshes and point clouds, to build a filtering procedure, in order to produce a more reliable spatial registration between images, thereby increasing the robustness of the color correction procedure. We also present a texture mapping pipeline that receives uncorrected images, an untextured mesh, and point clouds as inputs, producing a final textured mesh and color corrected images as output. Results include a comparison with four other color correction approaches. These show that the proposed approach outperforms all others, both in qualitative and quantitative metrics. The proposed approach enhances the visual quality of textured meshes by eliminating most of the texture seams.

Challenging replacement of a maxillary canine with an implant-supported restoration: A surgical and prosthetic approach.

This clinical report describes the replacement of a traumatized maxillary canine that was extracted after unsuccessful orthodontic extrusion with an implant-supported restoration. Guided bone regeneration surgery was performed, followed by a second surgery with implant placement plus simultaneous bone and tissue regeneration. Esthetics and function were achieved with the placement of a veneered zirconia implant-supported restoration.

Legal regulation of ventilation rates in homes in Europe 2010-2022: Evolution and comparison study regarding Covid-19 recommendations.

The airborne transmission of SARS-CoV-2, the virus that causes Covid-19 disease, has been recognized as an essential route of contagion, so adequate ventilation is vital indoors. For this reason, the research goal focuses on carrying out the study and evolutionary and comparison analysis of the regulation of ventilation rates in dwellings in Europe (2010-2022) and on determining whether modifications are necessary for the said regulation based on the recommendations of competent international organizations. To do this, the methodology followed initially starts from the study carried out in 2010 by Christine Dimitroulopoulou, in which the existing regulation in various European countries regarding ventilation in dwellings was studied. Once this study has been analysed, it continues to update and compare the regulation of the different European countries cited in the said work, detecting during the process if a modification is necessary based on the recommendations indicated by international organizations such as the WHO or ECDC. The results and conclusions indicate that few countries have significantly changed their ventilation rates. Although the existing ones may be admissible, requiring controlled ventilation in the different regulations would be convenient.

Simultaneous Testicular and Appendix Testis Torsion: A Novel Clinically Relevant Association.

ABSTRACT: Torsion of the appendix testis (TAT) and testicular torsion (TT) are the most common causes of acute scrotum in the pediatric population. They usually present as separate conditions and have distinct managements. We report a unique case of a 16-year-old boy with concomitant TAT and TT. The role of TAT as a trigger factor to TT is addressed, and its clinical repercussion on the management of acute scrotum is discussed.

Robust Texture Mapping Using RGB-D Cameras.

The creation of a textured 3D mesh from a set of RGD-D images often results in textured meshes that yield unappealing visual artifacts. The main cause is the misalignments between the RGB-D images due to inaccurate camera pose estimations. While there are many works that focus on improving those estimates, the fact is that this is a cumbersome problem, in particular due to the accumulation of pose estimation errors. In this work, we conjecture that camera poses estimation methodologies will always display non-neglectable errors. Hence, the need for more robust texture mapping methodologies, capable of producing quality textures even in considerable camera misalignments scenarios. To this end, we argue that use of the depth data from RGB-D images can be an invaluable help to confer such robustness to the texture mapping process. Results show that the complete texture mapping procedure proposed in this paper is able to significantly improve the quality of the produced textured 3D meshes.

Enhancement of RGB-D Image Alignment Using Fiducial Markers.

Three-dimensional (3D) reconstruction methods generate a 3D textured model from the combination of data from several captures. As such, the geometrical transformations between these captures are required. The process of computing or refining these transformations is referred to as alignment. It is often a difficult problem to handle, in particular due to a lack of accuracy in the matching of features. We propose an optimization framework that takes advantage of fiducial markers placed in the scene. Since these markers are robustly detected, the problem of incorrect matching of features is overcome. The proposed procedure is capable of enhancing the 3D models created using consumer level RGB-D hand-held cameras, reducing visual artefacts caused by misalignments. One problem inherent to this solution is that the scene is polluted by the markers. Therefore, a tool was developed to allow their removal from the texture of the scene. Results show that our optimization framework is able to significantly reduce alignment errors between captures, which results in visually appealing reconstructions. Furthermore, the markers used to enhance the alignment are seamlessly removed from the final model texture.

Autonomous Scene Exploration for Robotics: A Conditional Random View-Sampling and Evaluation Using a Voxel-Sorting Mechanism for Efficient Ray Casting.

Carrying out the task of the exploration of a scene by an autonomous robot entails a set of complex skills, such as the ability to create and update a representation of the scene, the knowledge of the regions of the scene which are yet unexplored, the ability to estimate the most efficient point of view from the perspective of an explorer agent and, finally, the ability to physically move the system to the selected Next Best View (NBV). This paper proposes an autonomous exploration system that makes use of a dual OcTree representation to encode the regions in the scene which are occupied, free, and unknown. The NBV is estimated through a discrete approach that samples and evaluates a set of view hypotheses that are created by a conditioned random process which ensures that the views have some chance of adding novel information to the scene. The algorithm uses ray-casting defined according to the characteristics of the RGB-D sensor, and a mechanism that sorts the voxels to be tested in a way that considerably speeds up the assessment. The sampled view that is estimated to provide the largest amount of novel information is selected, and the system moves to that location, where a new exploration step begins. The exploration session is terminated when there are no more unknown regions in the scene or when those that exist cannot be observed by the system. The experimental setup consisted of a robotic manipulator with an RGB-D sensor assembled on its end-effector, all managed by a Robot Operating System (ROS) based architecture. The manipulator provides movement, while the sensor collects information about the scene. Experimental results span over three test scenarios designed to evaluate the performance of the proposed system. In particular, the exploration performance of the proposed system is compared against that of human subjects. Results show that the proposed approach is able to carry out the exploration of a scene, even when it starts from scratch, building up knowledge as the exploration progresses. Furthermore, in these experiments, the system was able to complete the exploration of the scene in less time when compared to human subjects.

Multi-Sensor Extrinsic Calibration Using an Extended Set of Pairwise Geometric Transformations.

Systems composed of multiple sensors for exteroceptive perception are becoming increasingly common, such as mobile robots or highly monitored spaces. However, to combine and fuse those sensors to create a larger and more robust representation of the perceived scene, the sensors need to be properly registered among them, that is, all relative geometric transformations must be known. This calibration procedure is challenging as, traditionally, human intervention is required in variate extents. This paper proposes a nearly automatic method where the best set of geometric transformations among any number of sensors is obtained by processing and combining the individual pairwise transformations obtained from an experimental method. Besides eliminating some experimental outliers with a standard criterion, the method exploits the possibility of obtaining better geometric transformations between all pairs of sensors by combining them within some restrictions to obtain a more precise transformation, and thus a better calibration. Although other data sources are possible, in this approach, 3D point clouds are obtained by each sensor, which correspond to the successive centers of a moving ball its field of view. The method can be applied to any sensors able to detect the ball and the 3D position of its center, namely, LIDARs, mono cameras (visual or infrared), stereo cameras, and TOF cameras. Results demonstrate that calibration is improved when compared to methods in previous works that do not address the outliers problem and, depending on the context, as explained in the results section, the multi-pairwise technique can be used in two different methodologies to reduce uncertainty in the calibration process.

Evaluating the potential of adaptive comfort approach using historic data to reduce energy consumption in buildings in southern Spain.

The application of adaptive comfort models is among the determinant factors to reduce greenhouse gas emissions in the building sector. This research studies the region of Andalusia (south of Spain). A cluster analysis is applied to 786 Andalusian municipalities, and 4 groups are established according to the potential of adaptive strategies. A town is chosen from each group, and an hourly specific study is conducted for the last 20 years, as well as a daily study of the old time series by using an artificial neural network based on the existing climate data. The possibility of application of the EN 16798-1:2019 standard during the days of the year is analysed, as well as the possibilities of using natural ventilation and the possibility of using adaptive setpoint temperatures in comparison with both 3 fixed heating temperatures and 3 fixed cooling temperatures by considering the energy saving. The results to apply the standard ranged 69.0 and 100% of the days of each year. The possibilities of natural ventilation considered were greater than 10% of the hours of the year in all the assumptions. The energy saving of cooling degrees reveals a greater potential in the area studied than that of heating degrees; this tendency is supported by the study of old temporary series which are part of the climate variation predicted throughout the 21st century.

Classical and Quantum Liquids Induced by Quantum Fluctuations.

Geometrically frustrated interactions may render classical ground states macroscopically degenerate. The connection between classical and quantum liquids and how the degeneracy is affected by quantum fluctuations is, however, not completely understood. We study a simple model of coupled quantum and classical degrees of freedom, the so-called Falicov-Kimball model, on a triangular lattice and away from half-filling. For weak interactions the phase diagram features a charge disordered state down to zero temperature. We provide compelling evidence that this phase is a liquid and show that it is divided by a crossover line that terminates in a quantum critical point. Our results offer a new vantage point to address how quantum liquids can emerge from their classical counterparts.