A digital twin is a virtual representation of a physical object or process capable of collecting information from the real environment to represent, validate and simulate the physical twin’s present ...and future behavior. It is a key enabler of data-driven decision making, complex systems monitoring, product validation and simulation and object lifecycle management. As an emergent technology, its widespread implementation is increasing in several domains such as industrial, automotive, medicine, smart cities, etc. The objective of this systematic literature review is to present a comprehensive view on the DT technology and its implementation challenges and limits in the most relevant domains and applications in engineering and beyond.
When the sensory–motor integration system is malfunctioning provokes a wide variety of neurological disorders, which in many cases cannot be treated with conventional medication, or via existing ...therapeutic technology. A brain–computer interface (BCI) is a tool that permits to reintegrate the sensory–motor loop, accessing directly to brain information. A potential, promising and quite investigated application of BCI has been in the motor rehabilitation field. It is well-known that motor deficits are the major disability wherewith the worldwide population lives. Therefore, this paper aims to specify the foundation of motor rehabilitation BCIs, as well as to review the recent research conducted so far (specifically, from 2007 to date), in order to evaluate the suitability and reliability of this technology. Although BCI for post-stroke rehabilitation is still in its infancy, the tendency is towards the development of implantable devices that encompass a BCI module plus a stimulation system.
•BCIs permit to reintegrate the sensory–motor loop by accessing to brain information.•Motor imagery based BCIs seem to be an effective system for an early rehabilitation.•This technology does not need remaining motor activity and promotes neuroplasticity.•BCI for rehabilitation tends towards implantable devices plus stimulation systems.
Environmental pollution is a critical issue that requires proper measures to maintain environmental health in a sustainable and effective manner. The growing persistence of several active ...pharmaceutical residues, such as antibiotics like tetracycline, and anti-inflammatory drugs like diclofenac in water matrices is considered an issue of global concern. Numerous sewage/drain waste lines from the domestic and pharmaceutical sector contain an array of toxic compounds, so-called “emerging pollutants” and possess adverse effects on entire living ecosystem and damage its biodiversity. Therefore, effective solution and preventive measures are urgently required to sustainably mitigate and/or remediate pharmaceutically active emerging pollutants from environmental matrices. In this context, herein, the entry pathways of the pharmaceutical waste into the environment are presented, through the entire lifecycle of a pharmaceutical product. There is no detailed review available on carbon-dots (CDs) as robust materials with multifunctional features that support sustainable mitigation of emerging pollutants from water matrices. Thus, CDs-based photocatalysts are emerging as an efficient alternative for decontamination by pharmaceutical pollutants. The addition of CDs on photocatalytic systems has an important role in their performance, mainly because of their up-conversion property, transfer photoinduced electron capacities, and efficient separation of electrons and holes. In this review, we analyze the strategies followed by different researchers to optimize the photodegradation of various pharmaceutical pollutants. In this manner, the effect of different parameters such as pH, the dosage of photocatalyst, amount of carbon dots, and initial pollutant concentration, among others are discussed. Finally, current challenges are presented from a pollution prevention perspective and from CDs-based photocatalytic remediation perspective, with the aim to suggest possible research directions.
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•Pollution is a critical issue that requires significant efforts to green the environment.•The trends in carbon dots-based photocatalysts from the past decade are scrutinized.•Sustainable mitigation strategies for highly hazardous toxins are given.•Several active pharmaceutical residues in water are pollutants of concern.
This paper presents an integrated monitoring system for the driver and the vehicle in a single case of study easy to configure and replicate. On-board vehicle sensors and remote sensors are combined ...to model algorithms for estimating polluting emissions, fuel consumption, driving style and driver's health. The main contribution of this paper is the analysis of interactions among the above monitored features highlighting the influence of the driver in the vehicle performance and vice versa. This analysis was carried out experimentally using one vehicle with different drivers and routes and implemented on a mobile application. Compared to commercial driver and vehicle monitoring systems, this approach is not customized, uses classical sensor measurements, and is based on simple algorithms that have been already proven but not in an interactive environment with other algorithms. In the procedure design of this global vehicle and driver monitoring system, a principal component analysis was carried out to reduce the variables used in the training/testing algorithms with objective to decrease the transfer data via Bluetooth between the used devices: a biometric wristband, a smartphone and the vehicle's central computer. Experimental results show that the proposed vehicle and driver monitoring system predicts correctly the fuel consumption index in 84%, the polluting emissions 89%, and the driving style 89%. Indeed, interesting correlation results between the driver's heart condition and vehicular traffic have been found in this analysis.
This study centers on creating a real-time algorithm to estimate brain-to-brain synchronization during social interactions, specifically in collaborative and competitive scenarios. This type of ...algorithm can provide useful information in the educational context, for instance, during teacher-student or student-student interactions. Positioned within the context of neuroeducation and hyperscanning, this research addresses the need for biomarkers as metrics for feedback, a missing element in current teaching methods. Implementing the bispectrum technique with multiprocessing functions in Python, the algorithm effectively processes electroencephalography signals and estimates brain-to-brain synchronization between pairs of subjects during (competitive and collaborative) activities that imply specific cognitive processes. Noteworthy differences, such as higher bispectrum values in collaborative tasks compared to competitive ones, emerge with reliability, showing a total of 33.75% of significant results validated through a statistical test. While acknowledging progress, this study identifies areas of opportunity, including embedded operations, wider testing, and improved result visualization. Beyond academia, the algorithm's utility extends to classrooms, industries, and any setting involving human interactions. Moreover, the presented algorithm is shared openly, to facilitate implementations by other researchers, and is easily adjustable to other electroencephalography devices. This research not only bridges a technological gap but also contributes insights into the importance of interactions in educational contexts.
Analyzing data related to the conditions of city streets and avenues could help to make better decisions about public spending on mobility. Generally, streets and avenues are fixed as soon as they ...have a citizen report or when a major incident occurs. However, it is uncommon for cities to have real-time reactive systems that detect the different problems they have to fix on the pavement. This work proposes a solution to detect anomalies in streets through state analysis using sensors within the vehicles that travel daily and connecting them to a fog-computing architecture on a V2I network. The system detects and classifies the main road problems or abnormal conditions in streets and avenues using Machine Learning Algorithms (MLA), comparing roughness against a flat reference. An instrumented vehicle obtained the reference through accelerometry sensors and then sent the data through a mid-range communication system. With these data, the system compared an Artificial Neural Network (supervised MLA) and a K-Nearest Neighbor (Supervised MLA) to select the best option to handle the acquired data. This system makes it desirable to visualize the streets' quality and map the areas with the most significant anomalies.
At present, optimization algorithms are used extensively. One particular type of such algorithms includes random-based heuristic population optimization algorithms, which may be created by modeling ...scientific phenomena, like, for example, physical processes. The present article proposes a novel optimization algorithm based on Hooke’s law, called the spring search algorithm (SSA), which aims to solve single-objective constrained optimization problems. In the SSA, search agents are weights joined through springs, which, as Hooke’s law states, possess a force that corresponds to its length. The mathematics behind the algorithm are presented in the text. In order to test its functionality, it is executed on 38 established benchmark test functions and weighed against eight other optimization algorithms: a genetic algorithm (GA), a gravitational search algorithm (GSA), a grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), teaching–learning-based optimization (TLBO), a grey wolf optimizer (GWO), a spotted hyena optimizer (SHO), as well as an emperor penguin optimizer (EPO). To test the SSA’s usability, it is employed on five engineering optimization problems. The SSA delivered better fitting results than the other algorithms in unimodal objective function, multimodal objective functions, CEC 2015, in addition to the optimization problems in engineering.
Herein, we reviewed polymeric constructs of polyhydroxyalkanoates (PHAs) at large and poly‐3‐hydroxybutyrate (P3HB), in particular, for drug delivery and tissue engineering applications. Polymeric ...constructs that can efficiently respond to numerous variations in their surroundings have gained notable attention from different industrial sectors such as biomedical, clinical, pharmaceutical, and cosmeceutical. Among them, considerable importance is given to their drug delivery and tissue engineering applications. PHAs with peculiar reference to P3HB are gaining prominence attention as candidate materials with such requisite potentialities. The unique structural and functional characteristics of PHAs and P3HB are of supreme interest and being used to engineer novel constructs for efficient drug delivery and tissue regeneration purposes. So far, an array of methodological approaches, such as in vitro, in vivo, and ex vivo techniques have been exploited though using different materials with different geometries for a said purpose. However, a low‐level production majorly limits their proper exploitation. Various physiochemical characteristics and production strategies have been introduced in this review. The data have been summarized on PHAs production by several microorganisms aiming to cover the scope of the last 10 years. The present review highlights the recent applications of PHAs and P3HB‐based constructs, such as micro/nanoparticles, biocomposite, nanofibers, and hydrogels as novel drug carries for regenerative medicine and tissue engineering. In summary, drug delivery and tissue engineering potentialities of PHAs and P3HB‐based constructs are discussed with suitable examples and envisioned directions of future developments.
Polymeric constructs of polyhydroxyalkanoates at large and poly‐3‐hydroxybutyrate, in particular, for drug delivery and tissue engineering applications. Polymeric constructs that can efficiently respond to numerous variations in their surroundings have gained notable attention from different industrial sectors such as biomedical, clinical, pharmaceutical, and cosmeceutical.
In recent years, the automotive industry has witnessed significant progress in the development of automated driving technologies. The integration of advanced sensors and systems in vehicles has led ...to the emergence of various functionalities, such as driving assistance and autonomous driving. Applying these technologies on the assembly line can enhance the efficiency, safety, and speed of transportation, especially at end-of-line production. This work presents a connected automated vehicle (CAV) demonstrator for generating autonomous driving systems and services for the automotive industry. Our prototype electric vehicle is equipped with state-of-the-art sensors and systems for perception, localization, navigation, and control. We tested various algorithms and tools for transforming the vehicle into a self-driving platform, and the prototype was simulated and tested in an industrial environment as proof of concept for integration into assembly systems and end-of-line transport. Our results show the successful integration of self-driving vehicle platforms in the automotive industry, particularly in factory halls. We demonstrate the localization, navigation, and communication capabilities of our prototype in a demo area. This work anticipates a significant increase in efficiency and operating cost reduction in vehicle manufacturing, despite challenges such as current low traveling speeds and high equipment costs. Ongoing research aims to enhance safety for higher vehicle speeds, making it a more viable business case for manufacturers, considering the increasing standardization of automated driving equipment in cars. The main contribution of this paper lies in introducing the general concept architecture of the integration of automated driving functionalities in end-of-line assembly and production systems. Showing a case study of the effective development and implementation of such functionalities with a CAV demonstrator in a more standardized industrial operational design domain.
Service Robots: Trends and Technology Gonzalez-Aguirre, Juan Angel; Osorio-Oliveros, Ricardo; Rodríguez-Hernández, Karen L. ...
Applied sciences,
11/2021, Letnik:
11, Številka:
22
Journal Article
Recenzirano
Odprti dostop
The 2021 sales volume in the market of service robots is attractive. Expert reports from the International Federation of Robotics confirm 27 billion USD in total market share. Moreover, the number of ...new startups with the denomination of service robots nowadays constitutes 29% of the total amount of robotic companies recorded in the United States. Those data, among other similar figures, remark the need for formal development in the service robots area, including knowledge transfer and literature reviews. Furthermore, the COVID-19 spread accelerated business units and some research groups to invest time and effort into the field of service robotics. Therefore, this research work intends to contribute to the formalization of service robots as an area of robotics, presenting a systematic review of scientific literature. First, a definition of service robots according to fundamental ontology is provided, followed by a detailed review covering technological applications; state-of-the-art, commercial technology; and application cases indexed on the consulted databases.
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