PEDESTRIAN PATHFINDING in URBAN ENVIRONMENTS: PRELIMINARY RESULTS

With the rise of urban population, many initiatives are focused upon the smart city concept, in which mobility of citizens arises as one of the main components. Updated and detailed spatial information of outdoor environments is needed to accurate path planning for pedestrians, especially for people with reduced mobility, in which physical barriers should be considered. This work presents a methodology to use point clouds to direct path planning. The starting point is a classified point cloud in which ground elements have been previously classified as roads, sidewalks, crosswalks, curbs and stairs. The remaining points compose the obstacle class. The methodology starts by individualizing ground elements and simplifying them into representative points, which are used as nodes in the graph creation. The region of influence of obstacles is used to refine the graph. Edges of the graph are weighted according to distance between nodes and according to their accessibility for wheelchairs. As a result, we obtain a very accurate graph representing the as-built environment. The methodology has been tested in a couple of real case studies and Dijkstra algorithm was used to pathfinding. The resulting paths represent the optimal according to motor skills and safety

Machine learning algorithms to predict breast cancer recurrence using structured and unstructured sources from electronic health records

Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone. We collected and preprocessed clinical data from a cohort of BC patients, resulting in 823 valid subjects for analysis. We derived three sets of features: structured information, features from free text, and a combination of both. We evaluated the performance of five ML algorithms to predict 5-year cancer recurrence and selected the best-performing to test our hypothesis. The XGB (eXtreme Gradient Boosting) model yielded the best performance among the five evaluated algorithms, with precision = 0.900, recall = 0.907, F1-score = 0.897, and area under the receiver operating characteristic AUROC = 0.807. The best prediction results were achieved with the structured dataset, followed by the unstructured dataset, while the combined dataset achieved the poorest performance. ML algorithms for BC recurrence prediction are valuable tools to improve patient risk stratification, help with post-cancer monitoring, and plan more effective follow-up. Structured data provides the best results when fed to ML algorithms. However, an approach based on natural language processing offers comparable results while potentially requiring less mapping effort.European Union | Ref. 875406Fondo Europeo de Desarrollo Regional (FEDER)Xunta de Galici

Assessment of Arthrobacter viscosus as reactive medium for forming permeable reactive biobarrier applied to PAHs remediation

Polycyclic aromatic hydrocarbons (PAHs) are significant environmental contaminants as they are present naturally as well as anthropogenically in soil, air and water. In spite of their low solubility, PAHs are spread to the environment, and they are present in surface water, industrial effluent or groundwater. Amongst all remediation technologies for treating groundwater contaminated with PAHs, the use of a permeable reactive biobarrier (PRBB) appears to be the most cost-effective, energy efficient, and environmentally sound approach. In this technology, the microorganisms are used as reactive medium to degrade or stabilize the contaminants. The main limits of this approach are that the microorganisms or consortium used for forming the PRBB should show adequate characteristics. They must be retained in the barrier-forming biofilm, and they should also have degradative ability for the target pollutants. The aim of the present work is to evaluate the viability of Arthrobacter viscosus as bioreactive medium for forming PRBB. Initially, the ability of A. viscosus to remove PAHs, benzo[a]anthracene 100 μM and phenanthrene 100 μM was evaluated operating in a batch bench-scale bioreactor. In both cases, total benzo[a]anthracene and phenanthrene removals were obtained after 7 and 3 days, respectively. Furthermore, the viability of the microorganisms was evaluated in the presence of chromium in a continuous mode. As a final point, the adhesion of A. viscosus to sepiolite forming a bioreactive material to build PRBB was demonstrated. In view of the attained results, it can be concluded that A. viscosus could be a suitable microorganism to form a bioreactive medium for PAHs remediation.This work has been supported by the Spanish Ministry of Economy and Competitiveness and FEDER Funds (Project CTM 2011-25389). Marta Pazos received financial support under the Ramon y Cajal programme and Marta Cobas under the final project master grant "Campus do Mar Knowledge in depth"

Telemonitoring Devices and Systems: Current Status and Future Trends

In the future, the number of elderly and chronically ill will be quite large. Additionally, pathologies will in many cases be in comorbidity. Alongside this reality, the health care resources will be insufficient for the population, thus the current research for solutions that can be fully implemented in the future. There are available several telemonitoring devices and systems for chronic diseases. Massive use of these devices will be essential to address the current and future lack of health system resources. Research on telemonitoring devices and systems for chronic diseases was con-ducted in academic and scientific databases. The technical specifications were collected in the manufacturers’ web page. The gathered data was analysed and compared in order to propose scenarios for the future trend of technical specifi-cations required in telemonitoring devices/system is performed. Telemonitoring for chronic diseases can bring great benefits to patient and health systems. Widening this practice will be a reality in the near future. This procedure will be fostered by the promotion and regulation of interoperability between de-vices/systems, as well as of front-end programs providing the link between health support systems. Interoperability issues are the main flaw of tedevicesring devices/systems on the market today.info:eu-repo/semantics/publishedVersio

Telemonitoring Devices and Systems: Current Status and Future Trends

In the future, the number of elderly and chronically ill will be quite large. Additionally, pathologies will in many cases be in comorbidity. Along with this reality, the health care resources will be insufficient for the population, thus the current research for technological solutions needs to be implemented in the future. There are available several telemonitoring devices and systems for chronic diseases. Massive use of these devices will be essential to address the current and future lack of health system resources. Research on telemonitoring devices and systems for chronic diseases was conducted in academic and scientific databases. The technical specifications were collected from the manufacturers’ web page. The collected data was analysed and compared in order to propose scenarios for the future trend of technical specifications required in telemonitoring devices/system. Telemonitoring for chronic diseases can bring great benefits to patient and health systems. Widening this practice will be a reality in the near future. This procedure will be fostered by the promotion and regulation of interoperability between devices/systems, as well as of front-end programs providing the link between health support systems. Interoperability issues are the main flaws of telemonitoring devices/systems on the market today.info:eu-repo/semantics/publishedVersio

Cognitive impairment induced by delta9-tetrahydrocannabinol occurs through heteromers between cannabinoid CB1 and serotonin 5-HT2A receptors

Delta-9-tetrahydrocannabinol (THC), the main psychoactive compound of marijuana, induces numerous undesirable effects, including memory impairments, anxiety, and dependence. Conversely, THC also has potentially therapeutic effects, including analgesia, muscle relaxation, and neuroprotection. However, the mechanisms that dissociate these responses are still not known. Using mice lacking the serotonin receptor 5-HT2A, we revealed that the analgesic and amnesic effects of THC are independent of each other: while amnesia induced by THC disappears in the mutant mice, THC can still promote analgesia in these animals. In subsequent molecular studies, we showed that in specific brain regions involved in memory formation, the receptors for THC and the 5-HT2A receptors work together by physically interacting with each other. Experimentally interfering with this interaction prevented the memory deficits induced by THC, but not its analgesic properties. Our results highlight a novel mechanism by which the beneficial analgesic properties of THC can be dissociated from its cognitive side effects

Growing up at Different Altitudes: Changes in Energy Content of the Abies religiosa Wood

Wood is considered an important renewable energy resource with a variable elemental chemical composition, which may change according to environmental conditions (e.g., temperature, precipitation, altitude). In this study, we evaluated how heating value (HV), elemental chemical composition, and main thermoenergetic parameters of Abies religiosa wood change along an altitudinal gradient. To evaluate these parameters, wood samples were collected from six independent trees in an altitudinal gradient (3000-3500 masl) every 100 m of altitude (36 trees) and their respective HV (higher and low), thermogravimetric and immediate analysis, specific carbon energy (SCE), and fuel value index (FVI) were determined. We found that the higher and lower heating values, elemental chemical composition and the majority of the studied parameters were significantly different (p < 0.05) between altitudes. Our results suggest that A. religiosa wood from 3300 masl has more energy content than wood from 3200 and 3500 masl. Additionally, FVI showed that wood from 3500 masl is the best feedstock in order to use as a solid biofuel. Finally, the results suggest that the altitude at which A. religiosa is grown significantly affects the energetic content of their wood and throughput as a solid biofue

Characterization of pathogenic germline mutations in human Protein Kinases

Background Protein Kinases are a superfamily of proteins involved in crucial cellular processes such as cell cycle regulation and signal transduction. Accordingly, they play an important role in cancer biology. To contribute to the study of the relation between kinases and disease we compared pathogenic mutations to neutral mutations as an extension to our previous analysis of cancer somatic mutations. First, we analyzed native and mutant proteins in terms of amino acid composition. Secondly, mutations were characterized according to their potential structural effects and finally, we assessed the location of the different classes of polymorphisms with respect to kinase-relevant positions in terms of subfamily specificity, conservation, accessibility and functional sites.&lt;p&gt;&lt;/p&gt; Results Pathogenic Protein Kinase mutations perturb essential aspects of protein function, including disruption of substrate binding and/or effector recognition at family-specific positions. Interestingly these mutations in Protein Kinases display a tendency to avoid structurally relevant positions, what represents a significant difference with respect to the average distribution of pathogenic mutations in other protein families.&lt;p&gt;&lt;/p&gt; Conclusions Disease-associated mutations display sound differences with respect to neutral mutations: several amino acids are specific of each mutation type, different structural properties characterize each class and the distribution of pathogenic mutations within the consensus structure of the Protein Kinase domain is substantially different to that for non-pathogenic mutations. This preferential distribution confirms previous observations about the functional and structural distribution of the controversial cancer driver and passenger somatic mutations and their use as a proxy for the study of the involvement of somatic mutations in cancer development.&lt;p&gt;&lt;/p&gt

The HEV Ventilator

HEV is a low-cost, versatile, high-quality ventilator, which has been designed in response to the COVID-19 pandemic. The ventilator is intended to be used both in and out of hospital intensive care units, and for both invasive and non-invasive ventilation. The hardware can be complemented with an external turbine for use in regions where compressed air supplies are not reliably available. The standard modes provided include PC-A/C(Pressure Assist Control),PC-A/C-PRVC(Pressure Regulated Volume Control), PC-PSV (Pressure Support Ventilation) and CPAP (Continuous Positive airway pressure). HEV is designed to support remote training and post market surveillance via a web interface and data logging to complement the standard touch screen operation, making it suitable for a wide range of geographical deployment. The HEV design places emphasis on the quality of the pressure curves and the reactivity of the trigger, delivering a global performance which will be applicable to ventilator needs beyond theCOVID-19 pandemic. This article describes the conceptual design and presents the prototype units together with their performance evaluation.Comment: 34 pages, 18 figures, Extended version of the article submitted to PNA

DIRAC Experiment and Test of Low-Energy QCD

The low-energy QCD predictions to be tested by the DIRAC experiment are revised. The experimental method, the setup characteristics and capabilities, along with first experimental results are reported. Preliminary analysis shows good detector performance: alignment error via $\Lambda$ mass measurement $m_\Lambda = 1115.6 MeV/c^2$ with $\sigma = 0.92 MeV/c^2$, $p \pi^-$ relative momentum resolution $\sigma_Q \approx 2.7 MeV/c$, and evidence for $\pi^