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Abstract Defect in the SMN1 gene causes spinal muscular atrophy (SMA), which shows loss of motor neurons, muscle weakness and atrophy. While current treatment strategies, including small molecules or viral vectors, have shown promise in improving motor function and survival, achieving a definitive and long-term correction of SMA’s endogenous mutations and phenotypes remains highly challenging. We have previously developed a CRISPR-Cas9 based homology-independent targeted integration (HITI) strategy, enabling unidirectional DNA knock-in in both dividing and non-dividing cells in vivo. In this study, we demonstrated its utility by correcting an SMA mutation in mice. When combined with Smn1 cDNA supplementation, it exhibited long-term therapeutic benefits in SMA mice. Our observations may provide new avenues for the long-term and efficient treatment of inherited diseases.

Tomando en consideración los retos y desafíos que enfrentan las asociaciones dedicadas a la actividad agrícola y en específico a la piscícola, se plantean los factores que influyen en la toma de decisiones en unidades asociativas piscícolas, considerando las características organizacionales que desempeñan un papel fundamental en este proceso, en particular, la socialización de los miembros de estas unidades y la evaluación del entorno. A través de un enfoque cuantitativo y encuestas para recopilar datos de estas unidades asociativas piscícolas en el departamento de Sucre, Colombia, se obtuvo evidencia que la socialización de los miembros de las unidades piscícolas, así como la evaluación del entorno, desempeñan un papel crítico en la obtención de resultados organizaciones, específicamente en la toma de decisiones. Lo anterior proporciona una comprensión más profunda de cómo ciertas características organizacionales, en particular la socialización y la evaluación del entorno, influyen en la toma de decisiones de las unidades asociativas piscícolas complementando así los hallazgos de la literatura previa.

The evolution towards Smart Cities is the process that many urban centers are following in their quest for efficiency, resource optimization and sustainable growth. This step forward in the continuous improvement of cities is closely linked to the quality of life they want to offer their citizens. One of the key issues that can have the greatest impact on the quality of life of all city dwellers is the quality of the air they breathe, which can lead to illnesses caused by pollutants in the air. The application of new technologies, such as the Internet of Things, Big Data and Artificial Intelligence, makes it possible to obtain increasingly abundant and accurate data on what is happening in cities, providing more information to take informed action based on scientific data. This article studies the evolution of pollutants in the main cities of Castilla y León, using Generative Additive Models (GAM), which have proven to be the most efficient for making predictions with detailed historical data and which have very strong seasonalities. The results of this study conclude that during the COVID-19 pandemic containment period, there was an overall reduction in the concentration of pollutants.

Physical aggression is a serious and widespread problem in society, affecting people worldwide. It impacts nearly every aspect of life. While some studies explore the root causes of violent behavior, others focus on urban planning in high-crime areas. Real-time violence detection, powered by artificial intelligence, offers a direct and efficient solution, reducing the need for extensive human supervision and saving lives. This paper is a continuation of a systematic mapping study and its objective is to provide a comprehensive and up-to-date review of AI-based video violence detection, specifically in physical assaults. Regarding violence detection, the following have been grouped and categorized from the review of the selected papers: 21 challenges that remain to be solved, 28 datasets that have been created in recent years, 21 keyframe extraction methods, 16 types of algorithm inputs, as well as a wide variety of algorithm combinations and their corresponding accuracy results. Given the lack of recent reviews dealing with the detection of violence in video, this study is considered necessary and relevant.

Abstract Charcot-Marie-Tooth disease is a chronic hereditary motor and sensory polyneuropathy targeting Schwann cells and/or motor neurons. Its multifactorial and polygenic origin portrays a complex clinical phenotype of the disease with a wide range of genetic inheritance patterns. The disease-associated gene GDAP1 encodes for a mitochondrial outer membrane protein. Mouse and insect models with mutations in Gdap1 have reproduced several traits of the human disease. However, the precise function in the cell types affected by the disease remains unknown. Here, we use induced-pluripotent stem cells derived from a Gdap1 knockout mouse model to better understand the molecular and cellular phenotypes of the disease caused by the loss-of-function of this gene. Gdap1-null motor neurons display a fragile cell phenotype prone to early degeneration showing (1) altered mitochondrial morphology, with an increase in the fragmentation of these organelles, (2) activation of autophagy and mitophagy, (3) abnormal metabolism, characterized by a downregulation of Hexokinase 2 and ATP5b proteins, (4) increased reactive oxygen species and elevated mitochondrial membrane potential, and (5) increased innate immune response and p38 MAP kinase activation. Our data reveals the existence of an underlying Redox-inflammatory axis fueled by altered mitochondrial metabolism in the absence of Gdap1. As this biochemical axis encompasses a wide variety of druggable targets, our results may have implications for developing therapies using combinatorial pharmacological approaches and improving therefore human welfare. A Redox-immune axis underlying motor neuron degeneration caused by the absence of Gdap1. Our results show that Gdap1 –/– motor neurons have a fragile cellular phenotype that is prone to degeneration. Gdap1 –/– iPSCs differentiated into motor neurons showed an altered metabolic state: decreased glycolysis and increased OXPHOS. These alterations may lead to hyperpolarization of mitochondria and increased ROS levels. Excessive amounts of ROS might be the cause of increased mitophagy, p38 activation and inflammation as a cellular response to oxidative stress. The p38 MAPK pathway and the immune response may, in turn, have feedback mechanisms, leading to the induction of apoptosis and senescence, respectively. CAC, citric acid cycle; ETC, electronic transport chain; Glc, glucose; Lac, lactate; Pyr, pyruvate.

The global evolution of the Internet is experiencing a notable and inevitable change towards a convergent scenario known as the Internet of Things (IoT), where a large number of devices with heterogeneous characteristics and requirements have to be interconnected to serve different verticals, such as smart cities, intelligent transportation systems, smart grids, (ITS) or e-health [...]

El panorama competitivo actual en las organizaciones, caracterizado por presentar consumidores altamente exigentes respecto a productos y servicios que atiendan sus necesidades, ha generado retos y desafíos cada vez más cambiantes y dinámicos, llevando a las organizaciones a fortalecer sus equipos comerciales, adaptándose a estas nuevas exigencias, sin embargo, en muchos casos estas organizaciones no tienen un panorama amplio respecto a cuales son las estrategias que les permitan atender oportunamente las cambiantes necesidades de sus consumidores. Es por lo anterior que se propone una revisión sistemática de la literatura que permita dilucidar algunas estrategias que incidan en el posicionamiento de las organizaciones. En ese orden de ideas, la presente propuesta analiza 33 artículos científicos publicados desde el año 2016 hasta marzo de 2022 que tienen como temática central estrategias para equipos comerciales de las organizaciones y su relación con el desempeño organizacional. Los hallazgos clave sugieren que tener un cuerpo de teoría y práctica respaldado por evidencia empírica puede ayudar a las organizaciones a enfrentar las limitaciones y los desafíos actuales, aumentando así el posicionamiento en el mercado. Los hallazgos proponen un valor agregado para ser incorporados a las estrategias sugiriendo futuras líneas de investigación, abordando análisis empíricos.

Communication systems and networks are evolving as an integral part of not only of our everyday life but also as a part of the industry, fundamental infrastructures, companies, etc. Current directions and concepts, such as the Internet of Things (IoT), promise the enhanced quality of life, greater business opportunities, cost-effective manufacturing, and efficient operation management through ubiquitous connectivity and deployment of smart physical objects. IoT networks can collect, preprocess, and transmit vast amounts of data. A considerable portion of this data is security- and privacy-critical data, which makes IoT networks a tempting option for attackers. Given that these networks deal with the actual aspects of our lives and fundamental infrastructures (e.g. smart grids), security in such networks is crucial. The large scale of these networks and their unique characteristics and complexity bring further vulnerabilities. In this study, we focus on the IoT application layer, security requirements, threats, and countermeasures in this layer, and some of the open issues and future research lines.

El presente artículo expone el ejercicio del planeamiento estratégico y la prospectiva como una herramienta imprescindible en el ejercicio de la gerencia moderna esto dado por los escenarios de incertidumbre y complejidad que se vislumbran en los diferentes sectores económicos. Algunos aspectos que se consideran al estudiar estas incertidumbres son las dimensiones ambientales, económicas, sociales, políticas y aquellas intrínsecas asociadas a las propias características del ser humano. Lo expresado en este documentos forma parte de un trabajo de investigación que se viene realizando por los autores en cooperación con la cámara de comercio de Cartagena de indias y la gobernación de Bolívar ; en el que se pretende demostrar la importancia del estudio de los escenarios futuros que coadyuven a tomar mejores decisiones en el ejercicio de la toma de decisiones y la gerencia en PYMES; resalta la importancia de esta metodología y la utilización de alternativas estratégicas de carácter contingencial para definir políticas institucionales en momentos de crisis que coadyuvan al desarrollo económico y social de la región.

Underwater cultural heritage (UCH) is a crucial asset for our knowledge of human history and traditions [...]

It is widely believed that cellular senescence plays a critical role in both aging and cancer, and that senescence is a fundamental, permanent growth arrest that somatic cells cannot avoid. Here we show that Myc plays an important role in self-renewal of esophageal epithelial cells, contributing to their resistance to cellular senescence. Myc is homogeneously expressed in basal cells of the esophageal epithelium and Myc positively regulates their self-renewal by maintaining their undifferentiated state. Indeed, Myc knockout induced a loss of the undifferentiated state of esophageal epithelial cells resulting in cellular senescence while forced MYC expression promoted oncogenic cell proliferation. A superoxide scavenger counteracted Myc knockout-induced senescence, therefore suggesting that a mitochondrial superoxide takes part in inducing senescence. Taken together, these analyses reveal extremely low levels of cellular senescence and senescence-associated phenotypes in the esophageal epithelium, as well as a critical role for Myc in self-renewal of basal cells in this organ. This provides new avenues for studying and understanding the links between stemness and resistance to cellular senescence.

Anthropometrical profile is one of the indicators associated to optimal performance of futsal players. However, no studies have analyzed these factors in both sexes neither created an anthropometrical profile of each sex. For these reasons, the goals of this study were: to describe and compare the anthropometric and conditional profiles of sub-elite futsal players, and to analyze possible correlations between anthropometric and conditional parameters. 11 female and 8 male sub-elite futsal players participated in the study. Several tests were performed: an anthropometric and body composition analysis, leg power with squat jump (SJ) and countermovement jump (CMJ) tests, and psoas and major gluteus flexibility test. Male futsal players reported a better performance in SJ and CMJ (p0.05). Fat percentage presents a reversal correlation (r=-0.84; ES very large), as well as muscular performance, a direct correlation (r=0.73; ES very large) with explosive performance. There are significant differences between sexes regarding anthropometric and leg power parameters, not in flexibility values. Finally, the training methods and conditional goals along the season should be adapted to anthropometric and conditional profile of each competitive level, with special focus in neuromuscular performance.

Con la complejidad del mundo globalizado actual resulta importante comprender las dinámicas de las organizaciones y como estas contribuyen a la dinámica económica. Es por esto que se pretende plantear una revisión de los artículos recientes que se han desarrollado en torno al Emprendimiento, la dinámica empresarial y empleo, desde la óptica del crecimiento económico. Para tales fnes se comienza por dilucidar algunas teorías vinculadas con el emprendimiento y el crecimiento económico plateadas por los pensadores más importantes en cada campo, y a partir de allí se recopilan las investigaciones con mayor relevancia durante los últimos años que vinculen estas temáticas. Los hallazgos principales radican en una importancia vital del emprendimiento para el crecimiento económico, sin embargo, el aumento del empleo depende en gran medida de en qué sectores económicos se creen las empresas. Bajo este enfoque se plantean algunas conclusiones y se proponen discusiones que podrían dar origen a investigaciones futuras en la temática.

Dar a conocer los productos y servicios a los clientes, así como la calidad y la satisfacción obtenida de los mismos, es uno de los principales factores de éxito para cualquier organización actualmente, sobre todo en una empresa del sector servicios, sin embargo, en las pequeñas y medianas sociedades, en donde la gerencia debe cumplir múltiples funciones, es probable que las estrategias de marketing se ejecuten sin herramientas técnicas ni planeación y “sobre la marcha” o inclusive, estas ni siquiera existan o se tengan contempladas para un futuro, llevando a que se cometan equivocaciones anclando el éxito de la organización. Es por este motivo que se hace necesario conceder a los pequeños y medianos empresarios del sector servicios unas herramientas técnicas y estructuradas de tal manera que estos puedan llevar un plan de mercadeo que les permita incrementar las ventas y comenzar una senda de expansión de la organización. Para estos fnes se diseño un plan de marketing de forma sencilla y fácil entendimiento que contempla las etapas necesarias para encaminar las estrategias de marketing. El valor añadido es este plan de marketing se encuentra dirigido al sector servicios, el cual por su naturaleza presenta características específcas que se deben tener en cuenta para dar a conocer a sus clientes la organización.

This paper investigates distributed continuous-time fault estimation for multiple devices in the Internet-of-Things (IoT) networks by using a hybrid between cooperative control and state prediction techniques. First, a mode-dependent intermediate temperature matrix is designed, which constructs an intermediate estimator to estimate faulty temperature values obtained by the IoT network. Second, the continuous-time Markov chains transition matrix and output temperatures and the sufficient conditions of stability for auto-correct error of the IoT network temperatures are considered. Moreover, faulty devices are replaced by virtual devices to ensure continuous and robust monitoring of the IoT network, preventing in this way false data collection. Finally, the efficiency of the presented approach is verified with the results obtained in the conducted case study.

Summary: Cell reprogramming is thought to be associated with a full metabolic switch from an oxidative- to a glycolytic-based metabolism. However, neither the dynamics nor the factors controlling this metabolic switch are fully understood. By using cellular, biochemical, protein array, metabolomic, and respirometry analyses, we found that c-MYC establishes a robust bivalent energetics program early in cell reprogramming. Cells prone to undergo reprogramming exhibit high mitochondrial membrane potential and display a hybrid metabolism. We conclude that MYC proteins orchestrate a rewiring of somatic cell metabolism early in cell reprogramming, whereby somatic cells acquire the phenotypic plasticity necessary for their transition to pluripotency in response to either intrinsic or external cues. : Torres and colleagues describe an MYC-dependent remodeling of mitochondrial dynamics and metabolism during the first stage of cell reprogramming. Endogenous MYC activity was found to be necessary for cell reprogramming, likely by establishing a hybrid metabolic state characterized by elevated glycolytic flux and a somatic oxidative metabolic rate. MYC polarized mitochondria by increasing ATPIF1 and labeled cells prone to cell reprogramming. Keywords: cell reprogramming, metabolism, mitochondrial dynamics, cell signaling

Blockchain technology is used as a distributed ledger to store and secure data and perform transactions between entities in smart grids. This paper proposes a platform based on blockchain technology and the multi-agent system paradigm to allow for the creation of an automated peer-to-peer electricity market in micro-grids. The use of a permissioned blockchain network has multiple benefits as it reduces transaction costs and enables micro-transactions. Moreover, an improvement in security is obtained, eliminating the single point of failure in the control and management of the platform along with creating the possibility to trace back the actions of the participants and a mechanism of identification. Furthermore, it provides the opportunity to create a decentralized and democratic energy market while complying with the current legislation and regulations on user privacy and data protection by incorporating Zero-Knowledge Proof protocols and ring signatures.

El propósito de este artículo es realizar una revisión de la teoría de las representaciones sociales, diversos autores que han desarrollado el tema, su evolución y aplicabilidad en diversas áreas de conocimiento. Se hace un acercamiento a esta teoría a través de una búsqueda bibliográfica en plataformas como WOS (Web of Science) y Scopus, decantando por temas, autores y año de publicación, esto como un intento para ubicar un escenario de difusión para esta teoría. Finalmente, se hacen conclusiones sobre perspectiva general de la revisión y el estado de desarrollo.

This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques.

Reprogramming of somatic cells is a stepwise process where cells must overcome several barriers before reaching the pluripotent state. Here the authors show that mitochondrial fission in response to ERK1/2 signalling is an important early step during reprogramming to pluripotency.

Camelina is a low input crop than can be cultivated in rotation with cereals to provide vegetable oil suitable for bioenergy production, industrial applications and even as source of food for livestock. At large scale farming, camelina seeds are currently harvested using a combine harvester, equipped with a cereal header, but the literature still lacks the knowledge of the performance of the machine, the harvesting cost and the related loss of seeds. The present study aims to fulfill that gap by reporting the results obtained from an ad hoc harvest field test. Camelina seed yield was 0.95 Mg ha−1 which accounted for the 18.60% of the total above ground biomass. Theoretical field capacity, effective field capacity and field efficiency were 3.38 ha h−1, 3.17 ha h−1 and 93.7% respectively, albeit the seed loss was 80.1 kg ha−1 FM (7.82% w/w of the potential seed yield). The presence of material other than grain was rather high, 31.77% w/w, which implies a second step of cleaning to avoid undesired modification of the seed quality. Harvesting cost was estimated in 65.97 € ha−1. Our findings provide evidence on the suitability to use a conventional combine harvester equipped with a cereal header for the harvesting of camelina seeds, although some improvements are required to reduce both seed loss and impurities.

This paper analyses customers’ demand flexibility in a local power trading scenario through an Ising spin-based model. We look at quantitative information on the two-way relationships between power exchanges and spin dynamics. To this end, a modified version of the Metropolis-Hastings algorithm was implemented, including a gradient descent through the constraint surface. This allowed us to analyse the system on a large scale (considering the cumulated benefit of all the actors involved) and also from the perspective of total aggregation. In a maximum flexibility scenario, the total aggregation profit increases with the number of aggregators. We also investigate numerically the effect of aggregator boundaries on the spin dynamics.

Se realizó un ensayo de campo con camelina (Camelina sativa (L.) Crantz para estudiar su comportamiento en rotación de cultivo con un ensayo de fitorremediación con cardo (Cynara cardunculus L.), en un suelo representativo de un agroecosistema semiárido. El diseño experimental constó de parcelas sembradas con Camelina sativa (L.) Crantz, aprovechando la fertilización residual de enmiendas con dosis de lodo secado térmicamente (ST50) y (ST100) y de lodo compostado con resto de poda (CP50) y (CP100) comparados con un suelo control (T), en rotación de cultivo con un ensayo de fitorremediación con cardo. En términos generales, la fertilización residual con el lodo secado térmicamente (ST50) mejora la respuesta del cultivo, aumentando los valores de producción respecto del control y de la fertilización residual con lodo compostado con resto de poda. También con el efecto residual del lodo secado térmicamente (ST50) se consigue un aprovechamiento más eficaz del nitrógeno aplicado (proteína) y un mayor contenido en grasa. Respecto de las propiedades físico-químicas del suelo los resultados obtenidos muestran que los suelos fertilizados con lodos experimentaron un incremento de pH, materia orgánica, P, K, Ca, Mg y Na. La concentración de micronutrientes Cu, Zn y Ni y metales pesados Cr, Cd y Pb aumentó respecto del testigo, pero no hubo riesgos de contaminación.

Somatic cells can be reprogrammed into a pluripotent cellular state similar to that of embryonic stem cells. Given the significant physiological differences between the somatic and pluripotent cells, cell reprogramming is associated with a profound reorganization of the somatic phenotype at all levels. The remodeling of mitochondrial morphology is one of these dramatic changes that somatic cells have to undertake during cell reprogramming. Somatic cells transform their tubular and interconnected mitochondrial network to the fragmented and isolated organelles found in pluripotent stem cells early during cell reprogramming. Accordingly, mitochondrial fission, the process whereby the mitochondria divide, plays an important role in the cell reprogramming process. Here, we present an overview of the importance of mitochondrial fission in both cell reprogramming and cellular transformation.

Internet of Things (IoT) is the paradigm that has largely contributed to the development of smart buildings in our society. This technology makes it possible to monitor all aspects of the smart building and to improve its operation. One of the main challenges encountered by IoT networks is that the the data they collect may be unreliable since IoT devices can lose accuracy for several reasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is to study the evolution of IoT networks over time in smart buildings. The hypothesis we have tested is that, by amplifying the Lotka−Volterra equations as a community of living organisms (an ecosystem model), the reliability of the system and its components can be predicted. This model comprises a set of differential equations that describe the relationship between an IoT network and multiple IoT devices. Based on the Lotka−Volterra model, in this article, we propose a model in which the predators are the non-precision IoT devices and the prey are the precision IoT devices. Furthermore, a third species is introduced, the maintenance staff, which will impact the interaction between both species, helping the prey to survive within the ecosystem. This is the first Lotka−Volterra model that is applied in the field of IoT. Our work establishes a proof of concept in the field and opens a wide spectrum of applications for biology models to be applied in IoT.

The flux of high-energy protons slow-extracted from the CERN Super Proton Synchrotron (SPS) is limited by the induced radioactivity caused by the beam loss intrinsic to the extraction process. Methods to substantially increase the efficiency of the extraction process are of great interest to fulfill requests for an increasing flux of 400 GeV protons to the present experiments, located in the North Area of the SPS, and also for potential future experiments with very high demanded protons on target. A crystal shadowing technique to significantly reduce the beam scattered and lost on the electrostatic extraction septum during the third-integer resonant slow extraction process has been developed and a prototype system tested with beam. The technique is based on the use of a thin, bent silicon crystal to coherently channel or volume reflect the portion of beam that would otherwise impinge the wire array of the electrostatic septum and instead eject it into the transfer line toward the production targets of the experiments. In this paper, the concept is described and applied to the SPS machine in order to specify the requirements of the prototype crystal shadowing system. Beam dynamics simulations of the prototype system are compared and benchmarked to the results obtained through beam tests, before being exploited to understand the characteristics of the present system and the potential performance reach of an optimized, future operational configuration. The remaining challenges faced to bring the system into operation, the optimization possibilities and other potential applications are discussed.

The beauty of the proportional-integral-derivative (PID) algorithm for feedback control is its simplicity and efficiency. Those are the main reasons why PID controller is the most common form of feedback. PID combines the three natural ways of taking into account the error: the actual (proportional), the accumulated (integral), and the predicted (derivative) values; the three gains depend on the magnitude of the error, the time required to eliminate the accumulated error, and the prediction horizon of the error. This paper explores the new meaning of integral and derivative actions, and gains, derived by the consideration of non-integer integration and differentiation orders, i.e., for fractional order PID controllers. The integral term responds with selective memory to the error because of its non-integer order λ , and corresponds to the area of the projection of the error curve onto a plane (it is not the classical area under the error curve). Moreover, for a fractional proportional-integral (PI) controller scheme with automatic reset, both the velocity and the shape of reset can be modified with λ . For its part, the derivative action refers to the predicted future values of the error, but based on different prediction horizons (actually, linear and non-linear extrapolations) depending on the value of the differentiation order, μ . Likewise, in case of a proportional-derivative (PD) structure with a noise filter, the value of μ allows different filtering effects on the error signal to be attained. Similarities and differences between classical and fractional PIDs, as well as illustrative control examples, are given for a best understanding of new possibilities of control with the latter. Examples are given for illustration purposes.

End-users are more active because of demand response programs and the penetration of distributed energy resources in the bottom-layer of the power systems. This paper presents a virtual organization of agents of the power distribution grid for local energy trade. An iterative algorithm is proposed; it enables interaction between end-users and the Distribution Company (DisCo). Then, the performance of the proposed algorithm is evaluated in a 33-bus distribution network; its effectiveness is measured in terms of its impact on the energy trading scenarios and, thus, of its contribution to the energy management problem. According to the simulation results, although aggregators do not play the role of decision makers in the proposed model, our iterative algorithm is profitable for them.

The monitoring of the Internet of things networks depends to a great extent on the availability and correct functioning of all the network nodes that collect data. This network nodes all of which must correctly satisfy their purpose to ensure the efficiency and high quality of monitoring and control of the internet of things networks. This paper focuses on the problem of fault-tolerant maintenance of a networked environment in the domain of the internet of things. Based on continuous-time Markov chains, together with a cooperative control algorithm, a novel feedback model-based predictive hybrid control algorithm is proposed to improve the maintenance and reliability of the internet of things network. Virtual sensors are substituted for the sensors that the algorithm predicts will not function properly in future time intervals; this allows for maintaining reliable monitoring and control of the internet of things network. In this way, the internet of things network improves its robustness since our fault tolerant control algorithm finds the malfunction nodes that are collecting incorrect data and self-correct this issue replacing malfunctioning sensors with new ones. In addition, the proposed model is capable of optimising sensor positioning. As a result, data collection from the environment can be kept stable. The developed continuous-time control model is applied to guarantee reliable monitoring and control of temperature in a smart supermarket. Finally, the efficiency of the presented approach is verified with the results obtained in the conducted case study.

Unobtrusive indoor location systems must rely on methods that avoid the deployment of large hardware infrastructures or require information owned by network administrators. Fingerprinting methods can work under these circumstances by comparing the real-time received RSSI values of a smartphone coming from existing Wi-Fi access points with a previous database of stored values with known locations. Under the fingerprinting approach, conventional methods suffer from large indoor scenarios since the number of fingerprints grows with the localization area. To that aim, fingerprinting-based localization systems require fast machine learning algorithms that reduce the computational complexity when comparing real-time and stored values. In this paper, popular machine learning (ML) algorithms have been implemented for the classification of real time RSSI values to predict the user location and propose an intelligent indoor positioning system (I-IPS). The proposed I-IPS has been integrated with multi-agent framework for betterment of context-aware service (CAS). The obtained results have been analyzed and validated through established statistical measurements and superior performance achieved.

La evaluación por competencias aparece como prioridad en los últimos marcos legislativos que regulan la educación obligatoria en España, pero a nivel operativo no está resuelta satisfactoriamente en ninguno de ellos. En este artículo presentamos una propuesta de integración de competencias en el diseño de secuencias de aprendizaje. Ésta ha surgido fruto de un proceso de investigación-acción llevado a cabo a lo largo de dos años por un equipo de tres investigadores liderado por un profesor de Tecnología de Educación Secundaria Obligatoria. La propuesta se realizó en el contexto de la LOE, pero tal y como discute el artículo, se adapta a las propuesta de la LOMCE y supera alguna de sus dificultades. La reflexión sobre el proceso de diseño y aplicación de la propuesta muestra que es necesario desglosar los estándares de aprendizaje definidos en la LOMCE para facilitar su evaluación, y que la evaluación de los aprendizajes debe ser continua, basada en la observación y diferenciada según su objetivo.La evaluación por competencias aparece como prioridad en los últimos marcos legislativos que regulan la educación en España, pero a nivel operativo no está resuelta satisfactoriamente en ninguno de ellos.En este artículo presentamos una propuesta de integración de las competencias básicas en el diseño de secuencias de aprendizaje.Dicha propuesta surgió como fruto de un proceso de investigación-acción llevado a cabo a lo largo de dos años por un profesor de Tecnología de Educación Secundaria Obligatoria. Con el fin último de mejorar el grado de aprendizaje de los alumnos, el proceso de investigación-acción se concretó en el perfeccionamiento del diseño y gestión de las actividades en la etapa de educación secundaria.La propuesta se realizó en el contexto de la LOE, pero tal y como discute el artículo, se adapta a las propuesta de la LOMCE y supera alguna de sus dificultades.La reflexión sobre el proceso de diseño y aplicación de la propuesta muestra que es necesario desglosar los estándares de aprendizaje definidos en la LOMCE para facilitar su evaluación, y que la evaluación de los aprendizajes debe ser continua, basada en la observación y diferenciada según su objetivo.

Context-awareness in wireless sensor networks (WSNs) relies mainly on the position of objects and humans. The provision of this positional information becomes challenging in the harsh environmental conditions where WSNs are commonly deployed. With an antagonistic philosophy of design, fingerprinting and ranging have emerged as the key technologies underpinning wireless localization in harsh environments. Fingerprinting primarily focuses on accurate estimation at the expense of exhaustive calibration. Ranging mainly pursues an easy-to-deploy solution at the expense of moderate performance. In this paper, we present a resilient framework for sustained localization based on accurate fingerprinting in critical areas and light ranging in noncritical spaces. Such framework is conceived from the Bayesian perspective that facilitates the specification of recursive algorithms for real-time operation. In comparison to conventional implementations, we assessed the proposed framework in an indoor scenario with measurements gathered by commercial devices. The presented techniques noticeably outperform current approaches, enabling a flexible adaptation to the fluctuating conditions of harsh environments.

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.

This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead and real time. A hybrid method is defined for the first time in this paper to model the uncertainty of the PV power generation based on its power prediction. In the day-ahead stage, the uncertainty is modeled by interval bands. On the other hand, the uncertainty of PV power generation is modeled through a stochastic scenario-based method in the real-time stage. The performance of the proposed hybrid Interval-Stochastic (InterStoch) method is compared with the Modified Stochastic Predicted Band (MSPB) method. Moreover, the impacts of energy flexibility and the demand response program on the expected profit and transacted electrical energy of the system are assessed in the case study presented in this paper.

Real-time Localization Systems have been postulated as one of the most appropriated technologies for the development of applications that provide customized services. These systems provide us with the ability to locate and trace users and, among other features, they help identify behavioural patterns and habits. Moreover, the implementation of policies that will foster energy saving in homes is a complex task that involves the use of this type of systems. Although there are multiple proposals in this area, the implementation of frameworks that combine technologies and use Social Computing to influence user behaviour have not yet reached any significant savings in terms of energy. In this work, the CAFCLA framework (Context-Aware Framework for Collaborative Learning Applications) is used to develop a recommendation system for home users. The proposed system integrates a Real-Time Localization System and Wireless Sensor Networks, making it possible to develop applications that work under the umbrella of Social Computing. The implementation of an experimental use case aided efficient energy use, achieving savings of 17%. Moreover, the conducted case study pointed to the possibility of attaining good energy consumption habits in the long term. This can be done thanks to the system’s real time and historical localization, tracking and contextual data, based on which customized recommendations are generated.

In this work we show how a simple model based on chemical signaling can reduce the exploration times in urban environments. The problem is relevant for smart city navigation where electric vehicles try to find recharging stations with unknown locations. To this end we have adapted the classical ant foraging swarm algorithm to urban morphologies. A perturbed Markov chain model is shown to qualitatively reproduce the observed behaviour. This consists of perturbing the lattice random walk with a set of perturbing sources. As the number of sources increases the exploration times decrease consistently with the swarm algorithm. This model provides a better understanding of underlying process dynamics. An experimental campaign with real prototypes provided experimental validation of our models. This enables us to extrapolate conclusions to optimize electric vehicle routing in real city topologies.

The ability to direct differentiation of mouse embryonic stem (ES) cells into specific lineages not only provides new insights into the pathways that regulate lineage selection but also has translational applications, for example in drug discovery. We set out to develop a method of differentiating ES cells into mesodermal cells at high efficiency without first having to induce embryoid body formation. ES cells were plated on a feeder layer of PA6 cells, which have membrane-associated stromal-derived inducing activity (SDIA), the molecular basis of which is currently unknown. Stimulation of ES/PA6 co-cultures with Bone Morphogenetic Protein 4 (BMP4) both favoured self-renewal of ES cells and induced differentiation into a Desmin and Nestin double positive cell population. Combined stimulation with BMP4 and all-trans Retinoic Acid (RA) inhibited self-renewal and resulted in 90% of cells expressing Desmin and Nestin. Quantitative reverse transcription-polymerase chain reaction (qPCR) analysis confirmed that the cells were of mesodermal origin and expressed markers of mesenchymal and smooth muscle cells. BMP4 activation of a MAD-homolog (Smad)-dependent reporter in undifferentiated ES cells was attenuated by co-stimulation with RA and co-culture with PA6 cells. The Notch ligand Jag1 was expressed in PA6 cells and inhibition of Notch signalling blocked the differentiation inducing activity of PA6 cells. Our data suggest that mesodermal differentiation is regulated by the level of Smad activity as a result of inputs from BMP4, RA and the Notch pathway.

The presence of (Non line of Sight) NLOS propagation paths has been considered the main drawback for localization schemes to estimate the position of a (Mobile User) MU in an indoor environment. This paper presents a comprehensive wireless localization system based on (Round-Trip Time) RTT measurements in an unmodified IEEE 802.11 wireless network. It overcomes the NLOS impairment by implementing the (Prior NLOS Measurements Correction) PNMC technique. At first, the RTT measurements are performed with a novel electronic circuit avoiding the need for time synchronization between wireless nodes. At second, the distance between the MU and each reference device is estimated by using a simple linear regression function that best relates the RTT to the distance in (Line of Sight) LOS. Assuming that LOS in an indoor environment is a simplification of reality hence, the PNMC technique is applied to correct the NLOS effect. At third, assuming known the position of the reference devices, a multilateration technique is implemented to obtain the MU position. Finally, the localization system coupled with measurements demonstrates that the system outperforms the conventional time-based indoor localization schemes without using any tracking technique such as Kalman filters or Bayesian methods.