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Introduction: The formation of bacterial biofilms on knee arthroplasty implants can have catastrophic consequences. The aim of this study was to analyze the effectiveness of the bioelectric effect in the elimination of bacterial biofilms on cultivated knee arthroplasty implants.Methods: A novel device was designed to deliver a bioelectric effect on the surface of knee arthroplasty implants. 4-femoral prosthetic implants were cultivated with a staphylococcus aureus inoculum for 15 days. The components were divided into four different groups: A (not treated), B (normal saline 20-minutes), C (bioelectric effect 10-minutes), D (bioelectric effect 20-minutes). The implants were sonicated, and the detached colonies were quantified as the number of colony-forming unit (CFUs). The implants were sterilised and the process was repeated in a standardized manner four more times, to obtain a total of five samples per group.Results: The number of the CFUs after a 10-minute exposure to the bioelectric effect was of 208.2 ± 240.4, compared with 6,041.6 ± 2010.7 CFUs in group A, representing a decrease of 96.5% ± 4.3 (p = 0.004). And a diminution of 91.8% ± 7.9 compared with 2,051.0 ± 1,364.0 CFUs in group B (p = 0.109). The number of bacterial colonies after a 20-minute exposure to the bioelectric effect was 70 ± 126.7 CFUs, representing a decrease of 98.9% ± 1.9 (p = 0.000) compared with group A. And a decrease of 97.8% ± 3.0 (p = 0.019) compared with group B.Conclusions: The bioelectric effect was effective in the elimination of bacterial biofilm from knee arthroplasty implants. This method could be used in the future as part of conventional surgical procedures.

In an increasingly aging world, the effort to automate tasks associated with the care of elderly dependent individuals becomes more and more relevant if quality care provision at sustainable costs is desired. One of the tasks susceptible to automation in this field is the automatic detection of falls. The research effort undertaken to develop automatic fall detection systems has been quite substantial and has resulted in reliable fall detection systems. However, individuals who could benefit from these systems only consider their use in certain scenarios. Among them, a relevant scenario is the one associated to semi-supervised patients during the night who wake up and get out of bed, usually disoriented, feeling an urgent need to go to the toilet. Under these circumstances, usually, the person is not supervised, and a fall could go unnoticed until the next morning, delaying the arrival of urgently needed assistance. In this scenario, associated with nighttime rest, the patient prioritizes comfort, and in this situation, body-worn sensors typical of wearable systems are not a good option. Environmental systems, particularly visual-based ones with cameras deployed in the patient’s environment, could be the ideal option for this scenario. However, it is necessary to work with far-infrared (FIR) images in the low-light conditions of this environment. This work develops and implements, for the first time, a fall detection system that works with FIR imagery. The system integrates the output of a human pose estimation neural network with a detection methodology which uses the relative movement of the body’s most important joints in order to determine whether a fall has taken place. The pose estimation neural networks used represent the most relevant architectures in this field and have been trained using the first large public labeled FIR dataset. Thus, we have developed the first vision-based fall detection system working on FIR imagery able to operate in conditions of absolute darkness whose performance indexes are equivalent to the ones of equivalent systems working on conventional RGB images.

Introducción: La Facultad de Enfermería de la Universidad de la República ha incursionado en la adopción de la Planificación Estratégica como herramienta de gestión universitaria, dentro de una universidad que promueve esta metodología como una de sus políticas generales. Objetivo: evaluar el proceso de Planificación Estratégica de la Facultad de Enfermería, a través de los diferentes grupos de interés que la componen mediante el método responsivo-constructivista. Método: se empleó la evaluación de cuarta generación. Este método otorgó la posibilidad de que las personas afectadas por una determinada política o programa, pudieran ser los actores principales de la evaluación de las mismas, y ser también, generadores de propuestas de mejora. Asimismo, la investigación tuvo un enfoque cualitativo evaluativo, en la que los actores buscaron aprehender y mejorar su realidad. Así, la Planificación Estratégica de la Facultad de Enfermería fue considerada como la política general, que recayó sobre sus diferentes grupos de interés. Resultados: las cuestiones que emergieron en el proceso evaluativo fueron agrupadas en cuatro núcleos temáticos: Participación relativa, Comunicación ineficaz, Formación para la participación activa y Carrera de ascenso. Conclusiones: en este sentido, fue posible evaluar el proceso de Planificación Estratégica como herramienta de gestión, identificar las reivindicaciones, preocupaciones y problemas de los grupos de interés y proponer un plan de acción para consolidar los logros y ofrecer soluciones consensuadas a las preocupaciones y problemas identificados.

Com a chegada da pandemia de Covid-19, considerada o maior desafio de saúde pública do século 21, foram verificadas inúmeras controvérsias e polêmicas contemplando os planos de imunização e o ato de se vacinar em si, sobretudo envolvendo a contraposição entre direitos individuais e direitos coletivos. O presente artigo científico busca a realização de uma análise sobre a vacinação com base no direito coletivo à saúde, tendo como pano de fundo a aplicação da Teoria dos Deveres Fundamentais. Para tanto, fora realizada uma pesquisa que contou com as contribuições doutrinárias e jurisprudenciais, além da legislação e de achados em periódicos, com emprego do método hipotético-dedutivo para fomentar a discussão sobre o tema e apresentar como hipótese o caminho do cumprimento dos deveres coletivos, dentre eles o da vacinação obrigatória. O resultado alcançado neste estudo foi o de que o Estado é um interventor legítimo ao estabelecer o dever de se vacinar como um elemento para cumprir com o dever fundamental do indivíduo em zelar pela saúde pública. É uma forma de potencializar o direito difuso à saúde pública.

Abstract Fall detection systems use a number of different technologies to achieve their goals. This way, they contribute to better life conditions for the elderly community. The artificial vision is one of these technologies and, within this field, it has gained momentum over the course of the last few years as a consequence of the incorporation of different artificial neural networks (ANN's). These ANN's share a common characteristic, they are used to extract descriptors from images and video clips that, properly processed, will determine whether a fall has taken place. These descriptors, which capture kinematic features associated with the fall, are inferred from datasets recorded by young volunteers or actors who simulate falls. Systems based on this concept offer excellent performances in tests which use that kind of datasets. However, given the well‐documented differences between these falls and the real ones, concerns about system performances when processing falls of elderly people are raised. This work implements an alternative approach to the classical use of kinematic descriptors. To do it, for the first time to the best of the authors’ knowledge, the authors propose the introduction of human dynamic stability descriptors used in other fields to determine whether a fall has taken place. These descriptors approach the human body in terms of balance and stability; this way, differences between real and simulated falls become irrelevant, as all falls are a direct result of fails in the continuous effort of the body to keep balance, regardless of other considerations. The descriptors are determined by using the information provided by a neural network able to estimate the body centre of mass and the feet projections onto the ground plane, as well as the feet contact status. The theory behind this new approach and its validity is studied in this article with very promising results, as it is able to match or over exceed the performances of previous systems using kinematic descriptors employing available data and, given the independence of this approach from the conditions of the fall, it has the potential to have a better behaviour than classic systems when facing falls of elderly people.

Intrauterine adhesion (IUA) is the fibrosis within the uterine cavity. It is the second most common cause of female infertility, significantly affecting women's physical and mental health. Current treatment strategies fail to provide a satisfactory therapeutic outcome for IUA patients, leaving an enormous challenge for reproductive science. A self-healing adhesive hydrogel with antioxidant properties will be highly helpful in IUA prevention. In this work, we prepare a series of self-healing hydrogels (P10G15, P10G20, and P10G25) with antioxidant and adhesive properties. Those hydrogels exhibit good self-healing properties and can adapt themselves to different structures. They possess good injectability and fit the shape of the human uterus. Moreover, the hydrogels exhibit good tissue adhesiveness, which is desirable for stable retention and therapeutic efficacy. The in vitro experiments using P10G20 show that the adhesive effectively scavenges ABTS+, DPPH, and hydroxyl radicals, rescuing cells from oxidative stress. In addition, P10G20 offers good hemocompatibility and in vitro and in vivo biocompatibility. Furthermore, P10G20 lowers down the in vivo oxidative stress and prevents IUA with less fibrotic tissue and better endometrial regeneration in the animal model. It can effectively downregulate fibrosis-related transforming growth factor beta 1 (TGF-β1) and vascular endothelial growth factor (VEGF). Altogether, these adhesives may be a good alternative for the clinical treatment of intrauterine adhesion.

This article presents the EasyComVi Tool, an interactive application developed to facilitate the study of Computer Vision for students enrolled in an Engineering Master degree with a Distance Learning methodology. The main objective of this tool is to enable students in subjects related to Computer Vision with a distance learning methodology, to acquire a better understanding of different concepts about the subject studied in a theoretical way, through its interactive visual illustration, in an autonomous way. This tool offers the students the possibility to visualize the results of applying different image processing operations to various example images selecting the value of a set of input parameters. The usefulness and applicability of the tool has been evaluated by means of a questionnaire disseminated among the students of a subject on Computer Vision in a Master's degree in Industrial Engineering. This paper presents the preliminary results obtained in the study carried out, which are very promising and encourage further research in this work.

We present RGB-D-Fusion, a multi-modal conditional denoising diffusion probabilistic model to generate high resolution depth maps from low-resolution monocular RGB images of humanoid subjects. Accurately representing the human body in 3D is a very active research field given its wide variety of applications. Most 3D reconstruction algorithms rely on depth maps, either coming from low-resolution consumer-level depth sensors, or from monocular depth estimation from standard images. While many modern frameworks use VAEs or GANs for monocular depth estimation, we leverage recent advances in the field of diffusion denoising probabilistic models. We implement a multi-stage conditional diffusion model that first generates a low-resolution depth map conditioned on an image and then upsamples the depth map conditioned on a low-resolution RGB-D image. We further introduce a novel augmentation technique, depth noise augmentation, to increase the robustness of our super-resolution model. Lastly, we show how our method performs on a wide variety of humans with different body types, clothing and poses.

Abstract Osteoarthritis (OA) is the most common type of degenerative joint disease which affects 7% of the global population and more than 500 million people worldwide. One research frontier is the development of hydrogels for OA treatment, which operate either as functional scaffolds of tissue engineering or as delivery vehicles of functional additives. Both approaches address the big challenge: establishing stable integration of such delivery systems or implants. Adhesive hydrogels provide possible solutions to this challenge. However, few studies have described the current advances in using adhesive hydrogel for OA treatment. This review summarizes the commonly used hydrogels with their adhesion mechanisms and components. Additionally, recognizing that OA is a complex disease involving different biological mechanisms, the bioactive therapeutic strategies are also presented. By presenting the adhesive hydrogels in an interdisciplinary way, including both the fields of chemistry and biology, this review will attempt to provide a comprehensive insight for designing novel bioadhesive systems for OA therapy.

Transcriptomic and proteomic analyses reveal that glycosylation and carbohydrate metabolism are central processes in heart regeneration in zebrafish, including a shift from OXPHOS to glycolysis seven days after injury.

The structure of magnetic fields in galaxies remains poorly constrained, despite the importance of magnetism in the evolution of galaxies. Radio synchrotron and far-infrared (FIR) polarization and polarimetric observations are the best methods to measure galactic scale properties of magnetic fields in galaxies beyond the Milky Way. We use synthetic polarimetric observations of a simulated galaxy to identify and quantify the regions, scales, and interstellar medium (ISM) phases probed at FIR and radio wavelengths. Our studied suite of magnetohydrodynamical cosmological zoom-in simulations features high-resolutions (10 pc full-cell size) and multiple magnetization models. Our synthetic observations have a striking resemblance to those of observed galaxies. We find that the total and polarized radio emission extends to approximately double the altitude above the galactic disk (half-intensity disk thickness of h _I radio ∼ h _PI radio = 0.23 ± 0.03 kpc) relative to the total FIR and polarized emission that are concentrated in the disk midplane ( h _I FIR ∼ h _PI FIR = 0.11 ± 0.01 kpc). Radio emission traces magnetic fields at scales of ≳300 pc, whereas FIR emission probes magnetic fields at the smallest scales of our simulations. These scales are comparable to our spatial resolution and well below the spatial resolution (

This research introduces a conceptual framework designed to enhance worker safety and well-being in industrial environments, such as oil and gas construction plants, by leveraging Human Digital Twin (HDT) cutting-edge technologies and advanced artificial intelligence (AI) techniques. At its core, this study is in the developmental phase, aiming to create an integrated system that could enable real-time monitoring and analysis of the physical, mental, and emotional states of workers. It provides valuable insights into the impact of Digital Twins (DT) technology and its role in Industry 5.0. With the development of a chatbot trained as an empathic evaluator that analyses emotions expressed in written conversations using natural language processing (NLP); video logs capable of extracting emotions through facial expressions and speech analysis; and personality tests, this research intends to obtain a deeper understanding of workers’ psychological characteristics and stress levels. This innovative approach might enable the identification of stress, anxiety, or other emotional factors that may affect worker safety. Whilst this study does not encompass a case study or an application in a real-world setting, it lays the groundwork for the future implementation of these technologies. The insights derived from this research are intended to inform the development of practical applications aimed at creating safer work environments.

With the rapid proliferation of Internet of things (IoT) devices across various sectors, ensuring robust cybersecurity practices has become paramount. The complexity and diversity of IoT ecosystems pose unique security challenges that traditional educational approaches often fail to address comprehensively. Current curricula may provide theoretical knowledge but typically lack the practical components necessary for students to engage with real-world cybersecurity scenarios. This gap hinders the development of proficient cybersecurity professionals capable of securing complex IoT infrastructures. To bridge this educational divide, a remote online laboratory was developed, allowing students to gain hands-on experience in identifying and mitigating cybersecurity threats in an IoT context. This virtual environment simulates real IoT ecosystems, enabling students to interact with actual devices and protocols while practicing various security techniques. The laboratory is designed to be accessible, scalable, and versatile, offering a range of modules from basic protocol analysis to advanced threat management. The implementation of this remote laboratory demonstrated significant benefits, equipping students with the necessary skills to confront and resolve IoT security issues effectively. Our results show an improvement in practical cybersecurity abilities among students, highlighting the laboratory’s efficacy in enhancing IoT security education.

Abstract Bioadhesives are revolutionizing wound closure procedures. However, traditional bioadhesives lack functions to promote wound healing with a higher wound dehiscence rate than those treated with sutures. As a result, creating multifunctional bioadhesives to improve wound healing and facilitate wound care is extremely desirable in clinical settings. This study develops a series of multifunctional bioadhesives using succinic anhydride‐modified hyaluronic acid (HASA) and plant‐derived tannic acid (TA) with centrifuging and freeze‐drying. By varying the ratio of HASA to TA, HASATA 1:2, 1:7, and 1:14 are fabricated with tunable adhesive strength from 39.6 ± 8.2 to 63.0 ± 12.0 kPa. The bioadhesives exhibit self‐healing adhesive strength due to the reversible cohesion network developed by HASA and TA, enabling 25 to 50 times repeated wound closure. The animal studies reveal that the developed bioadhesives accelerate wound healing in the first week with a higher collagen content, more M2 macrophage upregulation and less oxidative stress. Moreover, the plant‐derived TA endows the bioadhesives with antioxidant properties against four kinds of free radicals, and antibacterial activity against both gram positive and negative bacteria. Altogether, these bioadhesives may open new avenues for noninvasive wound closure in the clinical setting.

Abstract Publicly available wind turbine failure rate and downtime studies are scarce in the scientific literature. Recent surveys in the field reveal that only 20 studies of wind farms based in Europe, Asia and the U.S. have been published, but there are no studies analysing wind farms located in Spain. With Spain holding the second place in terms of installed capacity in Europe, and the fifth worldwide, the importance of the Spanish wind power sector is evident. The present study comprehensively analyses the Spanish WT fleet in terms of yearly installed capacity and number of machines installed per technology and capacity ranges. The current fleet age ranges are also analysed. Under this scenario, the present work aims to contribute to the literature with a new failure rate and downtime study, where 75 WTs from six wind farms located in Spain are analysed over a period of 11 years. The most critical assemblies are identified per WT technology type and in general for the whole data set. Finally, the failure rate and downtime results obtained for the Spanish survey are compared against a selection of similar previously published studies.

Rumenotomy is one of the most widely used surgical techniques for the diagnosis and treatment of different rumen conditions in ruminants. It is commonly used for large ruminants, such as cattle. Although this technique is also applied to small ruminants, there is a lack of standardization. To date, it has not been fully described in the available literature, which is mostly from developing countries with a small number of peer-reviewed publications. This review is thus intended to summarize the body of knowledge related to the technique that has been published so far and make it available for clinical practice. The indications for rumenotomy, preoperative management of patients, different surgical techniques and postoperative management, including complications from the procedure, are discussed.

A fully planar dual polarized radiating element with internal embedded coupled dipoles is presented in this paper. The inclusion of these elements allows achieving three different goals: firstly, an extension of the bandwidth towards lower frequencies (from 1.69 GHz to 1.427 GHz) as required in new 5G standards; secondly, a reduction of the antenna size in comparison with other topologies for bandwidth extension and, finally, a reduction of the secondary lobes. The proposed dual polarized broadband antenna is based on two sets of dual polarized dipoles, with a fully planar structure. The objective of this paper is the design of an antenna working in the extended 5G band in order to fulfil the future 5G requirement in the microwave region, in which the new frequency bandwidth goes from 1.427 up to 2.69 GHz with the return losses lower than -14 dB and the crosspolar isolation larger than 28 dB.

Mergers are thought to be a fundamental channel for galaxy growth, perturbing the gas dynamics and the magnetic fields ( B -fields) in the interstellar medium (ISM). However, the mechanisms that amplify and dissipate B -fields during a merger remain unclear. We characterize the morphology of the ordered B -fields in the multiphase ISM of the closest merger of two spiral galaxies, the Antennae galaxies. We compare the inferred B -fields using 154 μ m thermal dust and 11 cm radio synchrotron emission polarimetric observations. We find that the 154 μ m B -fields are more ordered across the Antennae galaxies than the 11 cm B -fields. The turbulent-to-ordered 154 μ m B -field increases at the galaxy cores and star-forming regions. The relic spiral arm has an ordered spiral 154 μ m B -field, while the 11 cm B -field is radial. The 154 μ m B -field may be dominated by turbulent dynamos with high ^12 CO(1–0) velocity dispersion driven by star-forming regions, while the 11 cm B -field is cospatial with high H i velocity dispersion driven by galaxy interaction. This result shows the dissociation between the warm gas mainly disturbed by the merger, and the dense gas still following the dynamics of the relic spiral arm. We find a ∼8.9 kpc scale ordered B -field connecting the two galaxies. The base of the tidal tail is cospatial with the H i and ^12 CO(1–0) emission and has compressed and/or sheared 154 μ m and 11 cm B -fields driven by the merger. We suggest that amplified B -fields, with respect to the rest of the system and other spiral galaxies, may be supporting the gas flow between both galaxies and the tidal tail.

We present the analysis of the magnetic field ( B -field) structure of galaxies measured with far-infrared (FIR) and radio (3 and 6 cm) polarimetric observations. We use the first data release of the Survey of extragALactic magnetiSm with SOFIA of 14 nearby ( $\lt 20$ Mpc) galaxies with resolved ( $5^{\prime\prime} \mbox{--}18^{\prime\prime} ;$ 90 pc–1 kpc) imaging polarimetric observations using SOFIA/HAWC+ from 53 to 214 μ m. We compute the magnetic pitch-angle ( ${{\rm{\Psi }}}_{B}$ ) profiles as a function of the galactocentric radius. We introduce a new magnetic alignment parameter ( ζ ) to estimate the disordered-to-ordered ratio of spiral B -fields. We find FIR and radio wavelengths to not generally trace the same B -field morphology in galaxies. The ${{\rm{\Psi }}}_{B}$ profiles tend to be more ordered across all galactocentric radii in radio ( ${\zeta }_{6\mathrm{cm}}\,=\,0.93\pm 0.03$ ) than in FIR ( ${\zeta }_{154\mu {\rm{m}}}=0.84\pm 0.14$ ). For spiral galaxies, FIR B -fields are 2%–75% more turbulent than the radio B -fields. For starburst galaxies, we find that FIR polarization is a better tracer of the B -fields along the galactic outflows than radio polarization. Our results suggest that the B -fields associated with dense, dusty, turbulent star-forming regions (those traced at FIR) are less ordered than warmer, less dense regions (those traced at radio) of the interstellar medium. The FIR B -fields seem to be more sensitive to the activity of the star-forming regions and molecular clouds within a vertical height of a few hundred parsecs in the disk of spiral galaxies than the radio B -fields.

Introduction: Dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) reduces the rate of ischemic events but increases bleeding risk. DAPT score helps identify patients who benefit from prolonged DAPT. Nevertheless, its accuracy in patients with acute myocardial infarction (AMI) remains uncertain. The aim of this study was to validate the use of DAPT score to predict ischemic and bleeding events in patients undergoing PCI for AMI and who received prolonged DAPT. Material and Methods: This study included a cohort of patients with AMI who underwent PCI with stent placement and were treated with DAPT for more than 12 months. Results: Two hundred thirty subjects were included in the final analysis (age: 64 ± 12 years, 78% men, median follow-up: 31 months). Ischemic event (reinfarction or revascularization of target vessel or lesion) occurred in 17% and bleeding occurred in 5% of patients. DAPT score demonstrated modest prediction performance for ischemic events (C-statistic: 0.59, 95% confidence interval [CI]: 0.50-0.68, p

This paper forecasts learning technologies that are predicted to impact the practice of engineering education according to the perceptions of engineering education researchers and practitioners. These forecasts were derived from three worldwide surveys carried out in 2013, 2014 and 2015. The responses were analyzed to know the technologies that will have an impact in the short, medium and long term. In turn, differences in forecasts according to area of specialization and geographical region were studied. Moreover, this paper applies social analysis (Google Trends) and bibliometric analysis (Google Scholar, Scopus and Web of Science) to these predictions in order to discover which technologies were successful and really impacted in engineering education, and which ones failed to have the predicted impact and why.

Abstract Chronic limb threatening ischemia (CLTI) is a severe condition defined by the blockage of arteries in the lower extremities that leads to the degeneration of blood vessels and is characterized by the formation of non‐healing ulcers and necrosis. The gold standard therapies such as bypass and endovascular surgery aim at the removal of the blockage. These therapies are not suitable for the so‐called “no option patients” which present multiple artery occlusions with a likelihood of significant limb amputation. Therefore, CLTI represents a significant clinical challenge, and the efforts of developing new treatments have been focused on stimulating angiogenesis in the ischemic muscle. The delivery of pro‐angiogenic nucleic acid, protein, and stem cell‐based interventions have limited efficacy due to their short survival. Engineered biomaterials have emerged as a promising method to improve the effectiveness of these latter strategies. Several synthetic and natural biomaterials are tested in different formulations aiming to incorporate nucleic acid, proteins, stem cells, macrophages, or endothelial cells in supportive matrices. In this review, an overview of the biomaterials used alone and in combination with growth factors, nucleic acid, and cells in preclinical models is provided and their potential to induce revascularization and regeneration for CLTI applications is discussed.

Purpose. To evaluate the weight of intraocular lenses (IOLs) depending on their material, dioptric power, toricity, focality, and haptic design. Methods. Twenty-eight different IOL models from nine different medical companies (a total of 38 IOLs) and 1 capsular tension ring (CTR) were evaluated. IOLs were weighed using a precision scale, in hydrated conditions, as an approximation to their intraocular status. Results. Hydrophilic IOLs were heavier than hydrophobic lenses (p

Condition monitoring is central to the efficient operation of wind farms due to the challenging operating conditions, rapid technology development, and a large number of aging wind turbines. In particular, predictive maintenance planning requires the early detection of faults with few false positives. Achieving this type of detection is a challenging problem due to the complex and weak signatures of some faults, particularly the faults that occur on the gearbox bearings of a turbine drivetrain. The results of former studies addressing condition-monitoring tasks using dictionary learning indicate that unsupervised feature learning is useful for diagnosis and anomaly detection purposes. However, these studies are based on small sets of labeled data from test rigs operating under controlled conditions that focus on classification tasks, which are useful for quantitative method comparisons but gives little insight into how useful these approaches are in practice or how can be used by existing condition-monitoring systems. Here, we investigate an unsupervised dictionary learning method for condition monitoring using vibration data recorded over 46 months under typical industrial operations. Thus, we contribute real-world industrial vibration data that are made publicly available and novel test results. In this study, dictionaries are learned from gearbox vibrations in six different turbines, and the dictionaries are subsequently propagated over a few years of monitoring data when faults are known to occur. We perform the experiment using two different sparse coding algorithms to investigate if the algorithm selected affects the features of abnormal conditions. We propose a dictionary distance metric derived from the dictionary learning process as a condition indicator and find the time periods of abnormal dictionary adaptation starting six months before a drivetrain bearing replacement and one year before the resulting gearbox replacement. In addition, we investigate the distance between dictionaries learned from geographically close turbines of the same type under healthy conditions. We find that the features learned are similar and that a dictionary learned from one turbine can be useful for monitoring a similar turbine.

Objective To describe the epidemiological characteristics and trends of work-related eye injuries (WREIs) in Spain over a 10-year period by sex, age and occupational sector.Design and settings A descriptive, retrospective and longitudinal study based on data from workers insured by a labour insurance company in Spain from 2008 to 2018 was presented. The study considered the ratio of the number of WREI per 100 000 population and the relative risk of suffering an ocular injury. WREIs were characterised by sex, age and occupational sector of injured workers.Primary and secondary outcome measures Ratio of the number of WREI.Participants In Spain, all workers are insured by a labour insurance company that provides cover in the event of work-related accidents. In this study, we have included all workers insured by one of these insurance companies, IBERMUTUA, with workers in all areas of Spain.Results The study included 50 265 WREI in the company over the 10-year period. Most of the injuries occurred in males (44 445; 88.4%), in 35–44 age group (15 992; 31.8%) and in industry workers (18 899; 42.6%). The average incidence was 429.75 per 100 000 workers insured and 4273.36 per 100 000 IBERMUTUA accidents (related and not related to eyes). Males, 16–24 age group and industry occupational sector group, have the highest incidence for WREI. The incidence of WREI decrease over the study period in all variables. Males have 6.56 (95% CI 6.38 to 6.75) times more risk of suffering WREI than females. 16–24 age group have 1.77 (95% CI 1.71 to 1.83) times more risk than in the group of workers older than 55. Finally, industry workers have 7.73 (95% CI 7.55 to 7.92) times more risk than services workers.Conclusions The risks of suffering WREI is higher for males, younger and less experienced workers, and for those who works in a manual task.

Abstract Background Universal stress proteins (USPs) are present in all domains of life. Their expression is upregulated in response to a large variety of stress conditions. The functional diversity found in this protein family, paired with the sequence degeneration of the characteristic ATP-binding motif, suggests a complex evolutionary pattern for the paralogous USP-encoding genes. In this work, we investigated the origin, genomic organization, expression patterns and evolutionary history of the USP gene family in species of the phylum Platyhelminthes. Results Our data showed a cluster organization, a lineage-specific distribution, and the presence of several pseudogenes among the USP gene copies identified. The absence of a well conserved -CCAATCA- motif in the promoter region was positively correlated with low or null levels of gene expression, and with amino acid changes within the ligand binding motifs. Despite evidence of the pseudogenization of various USP genes, we detected an important functional divergence at several residues, mostly located near sites that are critical for ligand interaction. Conclusions Our results provide a broad framework for the evolution of the USP gene family, based on the emergence of new paralogs that face very contrasting fates, including pseudogenization, subfunctionalization or neofunctionalization. This framework aims to explain the sequence and functional diversity of this gene family, providing a foundation for future studies in other taxa in which USPs occur.

This paper analyzes the evolution of technology trends in education from 2010 to 2015, using as input the predictions made in the Horizon Reports on Higher Education, published yearly since 2004. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the midterm (the following two years), and the long term (the following four years). This paper applies social analysis, based on Google Trends, and bibliometric analysis, with data from Google Scholar and Web of Science, to these predictions in order to discover which technologies were successful and really impacted mainstream education, and which ones failed to have the predicted impact and why. This paper offers guidelines that may be helpful to those seeking to invest in new research areas.

The content at the end of any hyperlink is subject to two phenomena: the link may break (Link Rot) or the content at the end of the link may no longer be the same as it was when it was created (Content Drift). Reference Rot denotes the combination of both effects. Spatial metadata records rely on hyperlinks for indicating the location of the resources they describe. Therefore, they are also subject to Reference Rot. This paper evaluates the presence of Reference Rot and its impact on the 22,738 distribution URIs of 18,054 metadata records from 26 European INSPIRE spatial data catalogues. Our Link Rot checking method detects broken links while considering the specific requirements of spatial data services. Our Content Drift checking method uses the data format as an indicator. It compares the data formats declared in the metadata with the actual data types returned by the hyperlinks. Findings show that 10.41% of the distribution URIs suffer from Link Rot and at least 6.21% of records suffer from Content Drift (do not declare its distribution types correctly). Additionally, 14.94% of metadata records only contain intermediate HTML web pages as distribution URIs and 31.37% contain at least one HTML web page; thus, they cannot be accessed or checked directly.

Observational cosmology in the next decade will rely on probes of the distribution of matter in the redshift range between 0

Vision-based fall detection systems have experienced fast development over the last years. To determine the course of its evolution and help new researchers, the main audience of this paper, a comprehensive revision of all published articles in the main scientific databases regarding this area during the last five years has been made. After a selection process, detailed in the Materials and Methods Section, eighty-one systems were thoroughly reviewed. Their characterization and classification techniques were analyzed and categorized. Their performance data were also studied, and comparisons were made to determine which classifying methods best work in this field. The evolution of artificial vision technology, very positively influenced by the incorporation of artificial neural networks, has allowed fall characterization to become more resistant to noise resultant from illumination phenomena or occlusion. The classification has also taken advantage of these networks, and the field starts using robots to make these systems mobile. However, datasets used to train them lack real-world data, raising doubts about their performances facing real elderly falls. In addition, there is no evidence of strong connections between the elderly and the communities of researchers.

The Internet of Things (IoT) is widely considered as the next step towards a digital society, where objects and people are interconnected and interact through communication networks [...]

Internet of Things (IoT) learning involves the acquisition of transversal skills ranging from the development based on IoT devices and sensors (edge computing) to the connection of the devices themselves to management environments that allow the storage and processing (cloud computing) of data generated by sensors. The usual development cycle for IoT applications consists of the following three stages: stage 1 corresponds to the description of the devices and basic interaction with sensors. In stage 2, data acquired by the devices/sensors are employed by communication models from the origin edge to the management middleware in the cloud. Finally, stage 3 focuses on processing and presentation models. These models present the most relevant indicators for IoT devices and sensors. Students must acquire all the necessary skills and abilities to understand and develop these types of applications, so lecturers need an infrastructure to enable the learning of development of full IoT applications. A Web of Things (WoT) platform named Labs of Things at UNED (LoT@UNED) has been used for this goal. This paper shows the fundamentals and features of this infrastructure, and how the different phases of the full development cycle of solutions in IoT environments are implemented using LoT@UNED. The proposed system has been tested in several computer science subjects. Students can perform remote experimentation with a collaborative WoT learning environment in the cloud, including the possibility to analyze the generated data by IoT sensors.

The promise of an education revolution seems to be arriving. The emergence of free online courses, supported by some of the most prestigious universities in the world, is changing the traditional paradigm of teaching and paid classroom courses. In this new environment, new challenges and opportunities for the research community must be addressed both pedagogically and technically, always focusing on the open environments. This special issue of the RIED journal addresses this issue from different perspectives, all of which come from current initiatives.

In recent years, a significant amount of sequence data (both genomic and transcriptomic) for Echinococcus spp. has been published, thereby facilitating the analysis of genes expressed during a specific stage or involved in parasite development. To perform a suitable gene expression quantification analysis, the use of validated reference genes is strongly recommended. Thus, the aim of this work was to identify suitable reference genes to allow reliable expression normalization for genes of interest in Echinococcus granulosus sensu stricto (s.s.) (G1) and Echinococcus ortleppi upon induction of the early pre-adult development. Untreated protoscoleces (PS) and pepsin-treated protoscoleces (PSP) from E. granulosus s.s. (G1) and E. ortleppi metacestode were used. The gene expression stability of eleven candidate reference genes (βTUB, NDUFV2, RPL13, TBP, CYP-1, RPII, EF-1α, βACT-1, GAPDH, ETIF4A-III and MAPK3) was assessed using geNorm, Normfinder, and RefFinder. Our qPCR data showed a good correlation with the recently published RNA-seq data. Regarding expression stability, EF-1α and TBP were the most stable genes for both species. Interestingly, βACT-1 (the most commonly used reference gene), and GAPDH and ETIF4A-III (previously identified as housekeeping genes) did not behave stably in our assay conditions. We propose the use of EF-1α as a reference gene for studies involving gene expression analysis in both PS and PSP experimental conditions for E. granulosus s.s. and E. ortleppi. To demonstrate its applicability, EF-1α was used as a normalizer gene in the relative quantification of transcripts from genes coding for antigen B subunits. The same EF-1α reference gene may be used in studies with other Echinococcus sensu lato species. This report validates suitable reference genes for species of class Cestoda, phylum Platyhelminthes, thus providing a foundation for further validation in other epidemiologically important cestode species, such as those from the Taenia genus.