A semantic autonomous video surveillance system for dense camera networks in smart cities

Producción CientíficaThis paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network

Ultrasonographic features of the intrinsic foot muscles in patients with and without plantar fasciitis: a novel case-control research study

Introduction: The aim of the present study was to compare by ultrasound imaging (USI) the thickness and cross-sectional area (CSA) of the flexor hallucis brevis (FHB), flexor digitorum brevis (FDB), abductor hallucis brevis (AHB) and quadratus plantae (QP) muscles between individuals with and without plantar fasciitis (PF). Material and methods: A case-control study was performed with 64 participants divided into two groups: A, PF group (n = 32) and B, healthy group (n = 32). Results: USI measurements for FHB CSA (p = 0.035) decreased, showing statistically significant differences for the PF group, while the QP CSA (p = 0.40) increased, showing statistically significant differences for the PF group with respect to the healthy group. The rest of the intrinsic foot muscles (IFM) did not show statistically significant differences; however in FHB, FDB, QP and AHB thicknesses and FDB CSA showed a slightly decrease for the PF group. Conclusions: USI measurements showed that the CSA of the FHB muscle is reduced in patients with PF while the CSA of the QP muscle is increased in patients with PF

Analysis of the Interaction between Pisum sativum L. and Rhizobium laguerreae Strains Nodulating This Legume in Northwest Spain

[EN] Abstract: Pisum sativum L. (pea) is one of the most cultivated grain legumes in European countries due to the high protein content of its seeds. Nevertheless, the rhizobial microsymbionts of this legume have been scarcely studied in these countries. In this work, we analyzed the rhizobial strains nodulating the pea in a region from Northwestern Spain, where this legume is widely cultivated. The isolated strains were genetically diverse, and the phylogenetic analysis of core and symbiotic genes showed that these strains belong to different clusters related to R. laguerreae sv. viciae. Representative strains of these clusters were able to produce cellulose and cellulases, which are two key molecules in the legume infection process. They formed biofilms and produced acyl-homoserine lactones (AHLs), which are involved in the quorum sensing regulation process. They also exhibited several plant growth promotion mechanisms, including phosphate solubilization, siderophore, and indole acetic acid production and symbiotic atmospheric nitrogen fixation. All strains showed high symbiotic efficiency on pea plants, indicating that strains of R. laguerreae sv. viciae are promising candidates for the biofertilization of this legume worldwide

Features of Extrinsic Plantar Muscles in Patients with Plantar Fasciitis by Ultrasound Imaging: A Retrospective Case Control Research

[Abstract] The present study aimed to compare by ultrasound imaging (USI) the tibial posterior (TP), medial gastrocnemius (MG) and soleus muscle in patients with and without plantar fasciitis (PF). A sample of 42 individuals was recruited and divided into two groups: PF and a healthy group. The thickness, cross-sectional area (CSA), echointensity and echovariation were assessed in both groups by USI. TP, soleus and MG variables did not report differences (p > 0.05) for thickness and CSA. For the echotexture parameters significant differences were found for MG echointensity (p = 0.002), MG echovariation (p = 0.002) and soleus echointensity (p = 0.012). Non-significant differences (p > 0.05) were reported for soleus echovariation, TP echointensity and TP echovariation variables. The thickness and CSA of the TP, GM and soleus muscle did not show significant differences between individuals with and without PF measured by USI. Muscle quality assessment reported an increase of the MG echointensity and echovariation, as well as a decrease of echointensity of the soleus muscle in the PF group with respect to the healthy group. Therefore, the evaluation of the structure and muscle quality of the extrinsic foot muscles may be beneficial for the diagnosis and monitoring the physical therapy interventions

An intelligent surveillance platform for large metropolitan areas with dense sensor deployment

Producción CientíficaThis paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform’s control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coveraMinisterio de Industria, Turismo y Comercio and the Fondo de Desarrollo Regional (FEDER) and the Israeli Chief Scientist Research Grant 43660 inside the European Eureka Celtic project HuSIMS (TSI-020400-2010-102)

Current understanding of the diagnosis and management of the tendinopathy: An update from the lab to the clinical practice

[Abstract] Tendinopathy is labeled by many authors as a troublesome, common pathology, present in up to 30% medical care con- sultations involving musculoskeletal conditions. Despite the lasting interest for addressing tendon pathology, current re- searchers agree that even the exact definition of the term tendinopathy is unclear. Tendinopathy is currently diagnosed as a clinical hypothesis based on the patient symptoms and physical context. One of the main goals of current clinical management is to personalize treatment approaches to adapt them to the many different needs of the population. Tendons are complex structures that unite muscles and bones with two main objectives: to transmit forces and stor- age and release energy. Regarding the tensile properties of the tendons, several authors argued that tendons have higher tensile strength compared with muscles, however, are con- sidered less flexible. Tendinopathy is an accepted term which is used to indicated a variety of tissue conditions that appear in injured tendons and describes a non-rupture damage in the tendon or para- tendon, which is intensified with mechanical loading Even when the pathoetiology of tendinopathy is unclear, there is a wide array of treatments available to treat and manage tendinopathy. Although tendinitis usually debuts with an in- flammatory response, the majority of chronic tendinopathies do not present inflammation and so the choosing of treat- ment should vary depending on severity, compliance, pain and duration of symptoms. The purpose of this article is to review and provide an overview about the currently research of the tendon diagno- sis, management and etiology

Experimental Analysis of the Input Variables' Relevance to Forecast Next Day's Aggregated Electric Demand Using Neural Networks

Thanks to the built in intelligence (deployment of new intelligent devices and sensors in places where historically they were not present), the Smart Grid and Microgrid paradigms are able to take advantage from aggregated load forecasting, which opens the door for the implementation of new algorithms to seize this information for optimization and advanced planning. Therefore, accuracy in load forecasts will potentially have a big impact on key operation factors for the future Smart Grid/Microgrid-based energy network like user satisfaction and resource saving, and new methods to achieve an efficient prediction in future energy landscapes (very different from the centralized, big area networks studied so far). This paper proposes different improved models to forecast next day's aggregated load using artificial neural networks, taking into account the variables that are most relevant. In particular, seven models based on the multilayer perceptron will be proposed, progressively adding input variables after analyzing the influence of climate factors on aggregated load. The results section presents the forecast from the proposed models, obtained from real data.Hernández, L.; Baladrón Zorita, C.; Aguiar Pérez, JM.; Calavia Domínguez, L.; Carro Martínez, B.; Sanchez-Esguevillas, A.; Garcia Fernandez, P.... (2013). Experimental Analysis of the Input Variables' Relevance to Forecast Next Day's Aggregated Electric Demand Using Neural Networks. Energies. 6(6):2927-2948. doi:10.3390/en6062927S2927294866Zhang, Q., Lai, K. K., Niu, D., Wang, Q., & Zhang, X. (2012). A Fuzzy Group Forecasting Model Based on Least Squares Support Vector Machine (LS-SVM) for Short-Term Wind Power. Energies, 5(9), 3329-3346. doi:10.3390/en5093329Hsu, C.-C., & Chen, C.-Y. (2003). Regional load forecasting in Taiwan––applications of artificial neural networks. Energy Conversion and Management, 44(12), 1941-1949. doi:10.1016/s0196-8904(02)00225-xCarpaneto, E., & Chicco, G. (2008). Probabilistic characterisation of the aggregated residential load patterns. IET Generation, Transmission & Distribution, 2(3), 373. doi:10.1049/iet-gtd:20070280Shu Fan, Methaprayoon, K., & Wei-Jen Lee. (2009). Multiregion Load Forecasting for System With Large Geographical Area. IEEE Transactions on Industry Applications, 45(4), 1452-1459. doi:10.1109/tia.2009.2023569Pudjianto, D., Ramsay, C., & Strbac, G. (2007). Virtual power plant and system integration of distributed energy resources. IET Renewable Power Generation, 1(1), 10. doi:10.1049/iet-rpg:20060023Ruiz, N., Cobelo, I., & Oyarzabal, J. (2009). A Direct Load Control Model for Virtual Power Plant Management. IEEE Transactions on Power Systems, 24(2), 959-966. doi:10.1109/tpwrs.2009.2016607Hernandez, L., Baladron, C., Aguiar, J. M., Carro, B., Sanchez-Esguevillas, A., Lloret, J., … Cook, D. (2013). A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. IEEE Communications Magazine, 51(1), 106-113. doi:10.1109/mcom.2013.6400446Mousavi, S. M., & Abyaneh, H. A. (2011). Effect of Load Models on Probabilistic Characterization of Aggregated Load Patterns. IEEE Transactions on Power Systems, 26(2), 811-819. doi:10.1109/tpwrs.2010.2062542Ipakchi, A., & Albuyeh, F. (2009). Grid of the future. IEEE Power and Energy Magazine, 7(2), 52-62. doi:10.1109/mpe.2008.931384Naphade, M., Banavar, G., Harrison, C., Paraszczak, J., & Morris, R. (2011). Smarter Cities and Their Innovation Challenges. Computer, 44(6), 32-39. doi:10.1109/mc.2011.187Hernández, L., Baladrón, C., Aguiar, J. M., Calavia, L., Carro, B., Sánchez-Esguevillas, A., … Gómez, J. (2012). A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework. 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Artificial Neural Network for Short-Term Load Forecasting in Distribution Systems

The new paradigms and latest developments in the Electrical Grid are based on the introduction of distributed intelligence at several stages of its physical layer, giving birth to concepts such as Smart Grids, Virtual Power Plants, microgrids, Smart Buildings and Smart Environments. Distributed Generation (DG) is a philosophy in which energy is no longer produced exclusively in huge centralized plants, but also in smaller premises which take advantage of local conditions in order to minimize transmission losses and optimize production and consumption. This represents a new opportunity for renewable energy, because small elements such as solar panels and wind turbines are expected to be scattered along the grid, feeding local installations or selling energy to the grid depending on their local generation/consumption conditions. The introduction of these highly dynamic elements will lead to a substantial change in the curves of demanded energy. The aim of this paper is to apply Short-Term Load Forecasting (STLF) in microgrid environments with curves and similar behaviours, using two different data sets: the first one packing electricity consumption information during four years and six months in a microgrid along with calendar data, while the second one will be just four months of the previous parameters along with the solar radiation from the site. For the first set of data different STLF models will be discussed, studying the effect of each variable, in order to identify the best one. That model will be employed with the second set of data, in order to make a comparison with a new model that takes into account the solar radiation, since the photovoltaic installations of the microgrid will cause the power demand to fluctuate depending on the solar radiation.Our gratitude to CEDER-CIEMAT for providing the data to the presented work. In the same way, we want to convey our gratitude to the project partners MIRED-CON (IPT-2012-0611-120000), funded by the INNPACTO agreement of the Ministry of Economy and Competitiveness of the Government of Spain. Finally, a special mention to the help of the students Fatih Selim Bayraktar and Guniz Betul Yasar of Gazi University (Turkey), and Cristina Gil Valverde of UNED (Spain).Hernandez, L.; Baladron, C.; Aguiar, JM.; Calavia, L.; Carro, B.; Sanchez-Esguevillas, A.; Perez, F.... (2014). Artificial Neural Network for Short-Term Load Forecasting in Distribution Systems. Energies. 7(3):1576-1598. https://doi.org/10.3390/en7031576S1576159873Spencer, H. H., & Hazen, H. L. (1925). Artificial Representation of Power Systems. Transactions of the American Institute of Electrical Engineers, XLIV, 72-79. doi:10.1109/t-aiee.1925.5061095Hamilton, R. F. (1944). The Summation or Load Curves. 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Global model for short-term load forecasting using artificial neural networks. IEE Proceedings - Generation, Transmission and Distribution, 149(2), 121. doi:10.1049/ip-gtd:20020224Hernández, L., Baladrón, C., Aguiar, J., Carro, B., & Sánchez-Esguevillas, A. (2012). Classification and Clustering of Electricity Demand Patterns in Industrial Parks. Energies, 5(12), 5215-5228. doi:10.3390/en5125215Hernández, L., Baladrón, C., Aguiar, J. M., Calavia, L., Carro, B., Sánchez-Esguevillas, A., … Gómez, J. (2012). A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework. Sensors, 12(9), 11571-11591. doi:10.3390/s120911571Hagan, M. T., & Behr, S. M. (1987). The Time Series Approach to Short Term Load Forecasting. IEEE Transactions on Power Systems, 2(3), 785-791. doi:10.1109/tpwrs.1987.4335210Hernandez, L., Baladrón, C., Aguiar, J., Carro, B., Sanchez-Esguevillas, A., & Lloret, J. (2013). 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The cardiomyopathy of cystic fibrosis: a modern form of Keshan disease

IntroductionWe conducted a study to determine the prevalence of structural heart disease in patients with CF, the characteristics of a cardiomyopathy not previously described in this population, and its possible relationship with nutritional deficiencies in CF.MethodsWe studied 3 CMP CF patients referred for heart-lung transplantation and a prospective series of 120 adult CF patients. All patients underwent a clinical examination, blood tests including levels of vitamins and trace elements, and echocardiography with evaluation of myocardial strain. Cardiac magnetic resonance imaging (CMR) was performed in patients with CMP and in a control group. Histopathological study was performed on hearts obtained in transplant or necropsy.ResultsWe found a prevalence of 10% (CI 4.6%–15.4%) of left ventricular (LV) dysfunction in the prospective cohort. Myocardial strain parameters were already altered in CF patients with otherwise normal hearts. Histopathological examination of 4 hearts from CF CMP patients showed a unique histological pattern of multifocal myocardial fibrosis similar to Keshan disease. Four of the five CF CMP patients undergoing CMR showed late gadolinium uptake, with a characteristic patchy pattern in 3 cases (p < 0.001 vs. CF controls). Selenium deficiency (Se < 60 µg/L) was associated with more severe LV dysfunction, higher prevalence of CF CMP, higher NTproBNP levels, and more severe pulmonary and digestive involvement.Conclusion10% of adults with CF showed significant cardiac involvement, with histological and imaging features resembling Keshan disease. Selenium deficiency was associated with the presence and severity of LV dysfunction in these patients