Development of Smart Irrigation Equipment for Soilless Crops Based on the Current Most Representative Water-Demand Sensors.

Due to the edaphoclimatic conditions in southeast Spain, which are expected to worsen due to climate change, more efficient ways of using water must be found to maintain sustainable agriculture. Due to the current high price of irrigation control systems in southern Europe, 60-80% of soilless crops are still irrigated, based on the experience of the grower or advisor. The hypothesis of this work is that the development of a low-cost, high-performance control system will allow small farmers to improve the efficiency of water use by obtaining better control of soilless crops. The objective of the present study was to design and develop a cost-effective control system for the optimization of soilless crop irrigation after evaluating the three most commonly used irrigation control systems to determine the most efficient. Based on the agronomic results comparing these methods, a prototype of a commercial smart gravimetric tray was developed. The device records the irrigation and drainage volumes and drainage pH and EC. It also offers the possibility of determining the temperature, EC, and humidity of the substrate. This new design is scalable thanks to the use of an implemented data acquisition system called SDB and the development of software in the Codesys programming environment based on function blocks and variable structures. The reduced wiring achieved by the Modbus-RTU communication protocols means the system is cost-effective even with multiple control zones. It is also compatible with any type of fertigation controller through external activation. Its design and features solve the problems in similar systems available on the market at an affordable cost. The idea is to allow farmers to increase their productivity without having to make a large outlay. The impact of this work will make it possible for small-scale farmers to have access to affordable, state-of-the-art technology for soilless irrigation management leading to a considerable improvement in productivity.

A Multirobot System in an Assisted Home Environment to Support the Elderly in Their Daily Lives.

The increasing isolation of the elderly both in their own homes and in care homes has made the problem of caring for elderly people who live alone an urgent priority. This article presents a proposed design for a heterogeneous multirobot system consisting of (i) a small mobile robot to monitor the well-being of elderly people who live alone and suggest activities to keep them positive and active and (ii) a domestic mobile manipulating robot that helps to perform household tasks. The entire system is integrated in an automated home environment (AAL), which also includes a set of low-cost automation sensors, a medical monitoring bracelet and an Android application to propose emotional coaching activities to the person who lives alone. The heterogeneous system uses ROS, IoT technologies, such as Node-RED, and the Home Assistant Platform. Both platforms with the home automation system have been tested over a long period of time and integrated in a real test environment, with good results. The semantic segmentation of the navigation and planning environment in the mobile manipulator for navigation and movement in the manipulation area facilitated the tasks of the later planners. Results about the interactions of users with the applications are presented and the use of artificial intelligence to predict mood is discussed. The experiments support the conclusion that the assistance robot correctly proposes activities, such as calling a relative, exercising, etc., during the day, according to the user's detected emotional state, making this is an innovative proposal aimed at empowering the elderly so that they can be autonomous in their homes and have a good quality of life.

Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities.

The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot's autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.

Data Analysis and Forecasting of the COVID-19 Spread: A Comparison of Recurrent Neural Networks and Time Series Models.

To understand and approach the spread of the SARS-CoV-2 epidemic, machine learning offers fundamental tools. This study presents the use of machine learning techniques for projecting COVID-19 infections and deaths in Mexico. The research has three main objectives: first, to identify which function adjusts the best to the infected population growth in Mexico; second, to determine the feature importance of climate and mobility; third, to compare the results of a traditional time series statistical model with a modern approach in machine learning. The motivation for this work is to support health care providers in their preparation and planning. The methods compared are linear, polynomial, and generalized logistic regression models to describe the growth of COVID-19 incidents in Mexico. Additionally, machine learning and time series techniques are used to identify feature importance and perform forecasting for daily cases and fatalities. The study uses the publicly available data sets from the John Hopkins University of Medicine in conjunction with the mobility rates obtained from Google's Mobility Reports and climate variables acquired from the Weather Online API. The results suggest that the logistic growth model fits best the pandemic's behavior, that there is enough correlation of climate and mobility variables with the disease numbers, and that the Long short-term memory network can be exploited for predicting daily cases. Given this, we propose a model to predict daily cases and fatalities for SARS-CoV-2 using time series data, mobility, and weather variables.

Quantifying the publication preferences of leading research universities.

Research universities have a strong devotion and advocacy for research in their core academic mission. This is why they are widely recognized for their excellence in research which make them take the most renowned positions in the different worldwide university leagues. In order to examine the uniqueness of this group of universities we analyze the scientific production of a sample of them in a 5 year period of time. On the one hand, we analyze their preferences in research measured with the relative percentage of publications in the different subject areas, and on the other hand, we calculate the similarity between them in research preferences. In order to select a set of research universities, we studied the leading university rankings of Shanghai, QS, Leiden, and Times Higher Education (THE). Although the four rankings own well established and developed methodologies and hold great prestige, we choose to use THE because data were readily available for doing the study we had in mind. Having done that, we selected the twenty academic institutions ranked with the highest score in the last edition of THE World University Rankings 2020 and to contrast their impact, we also, we compared them with the twenty institutions with the lowest score in this ranking. At the same time, we extracted publication data from Scopus database for each university and we applied bibliometrics indicators from Elsevier's SciVal. We applied the statistical techniques cosine similarity and agglomerative hierarchical clustering analysis to examine and compare affinities in research preferences among them. Moreover, a cluster analysis through VOSviewer was done to classify the total scientific production in the four major fields (health sciences, physical sciences, life sciences and social sciences). As expected, the results showed that top universities have strong research profiles, becoming the leaders in the world in those areas and cosine similarity pointed out that some are more affine among them than others. The results provide clues for enhancing existing collaboration, defining and re-directing lines of research, and seeking for new partnerships to face the current pandemic to find was to tackle down the covid-19 outbreak.

[1,2-Bis(diiso-propyl-phosphan-yl)ethane-κ2 P,P'](2-fluoro-N-{[(2-fluoro-phen-yl)aza-nid-yl]carbon-yl}anilinido-κ2 N,N')nickel(II).

The mol-ecular structure of the title complex, [Ni(C13H8F2N2O)(C14H32P2)] or Ni(oFPU)(dippe), where oFPU is the dianion of bis-(2-fluoro-phen-yl)urea and dippe is 1,2-bis-(di-iso-propyl-phosphino)ethane, comprises an NiII atom with a distorted square-planar coordination environment (geometry index τ4 = 0.195). One of the fluoro-phenyl rings of the oFPU ligand is disordered over two sets of sites in an 0.832 (7):0.168 (7) ratio. The crystal structure displays C-H⋯O and C-H⋯F hydrogen-bonding inter-actions, leading to chains with R 2 2(12) motifs extending parallel to [100]. The title compound might be of inter-est with respect to the production of urea and carbamate derivatives of nickel(II).

Smart Industrial IoT Monitoring and Control System Based on UAV and Cloud Computing Applied to a Concrete Plant.

Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besides quantifying production and helping to make decisions. UAVs are a highly consistent technological platform for efficient and cost-effective data collection and event monitoring. The industrial Internet of things (IIoT) sends data from systems that monitor and control the physical world to data processing systems that cloud computing has shown to be important tools for meeting processing requirements. In fog computing, the IoT gateway links different objects to the internet. It can operate as a joint interface for different networks and support different communication protocols. A great deal of effort has been put into developing UAVs and multi-UAV systems. This paper introduces a smart IIoT monitoring and control system based on an unmanned aerial vehicle that uses cloud computing services and exploits fog computing as the bridge between IIoT layers. Its novelty lies in the fact that the UAV is automatically integrated into an industrial control system through an IoT gateway platform, while UAV photos are systematically and instantly computed and analyzed in the cloud. Visual supervision of the plant by drones and cloud services is integrated in real-time into the control loop of the industrial control system. As a proof of concept, the platform was used in a case study in an industrial concrete plant. The results obtained clearly illustrate the feasibility of the proposed platform in providing a reliable and efficient system for UAV remote control to improve product quality and reduce waste. For this, we studied the communication latency between the different IIoT layers in different IoT gateways.

[Autism]. / Autismo.

Autism is a static, neuro-developmental disorder, that is life-long and comprises a wide range of behavioral disorders. It has a prevalence of 1-2 per 1,000 with a broad range of severity. Multiple causes have been put forward and genetics plays the major role. According to DSM-IV the main clinical manifestations include impaired social skills, language and non-verbal communication and changes in range of interests and activities. Cognitive deficits are frequent but not universal. Perseveration, affective flatness and lack of insight into other people's thinking and feelings is conspicuous. The neurobiological basis of autism is unknown, but histopathological and biochemical findings suggest a diffuse disorder of neuronal development, most severe in the fronto-temporal cortex, some limbic structures and in the cerebellum. At a biochemical level, abnormalities in serotonin and other neurotransmitters have been reported.

Autismo / Autism

El autismo es un trastorno estático del desarrollo neurológico que persiste toda la vida y que incluye un amplio margen de alteraciones conductuales. Afecta entre 1 a 2/1000 personas y varía mucho en cuanto a severidad. Sus causas son múltiples y la genética juega un papel mayor. De acuerdo al DSM-IV las manifestaciones clínicas distintivas son sociabilidad alterada, anormalidades en el lenguaje y la comunicación no verbal, así como alteraciones en el margen de intereses y actividades. La deficiencia mental es frecuente, pero no universal. La perseveración, el aplanamiento afectivo y la falta de comprensión de los pensamientos y sentimientos de otros es notable. Las bases neurobiológicas del autismo son desconocidas, pero los hallazgos histopatológicos y bioquímicos sugieren un trastorno difuso del desarrollo neuronal, que compromete sobre todo corteza bifronto temporal, algunas estructuras límbicas y el cerebelo. A nivel bioquímico se han descrito alteraciones en la transmisión serotoninérgica y de otros neurotransmisores.

Autism is a static, neuro developmental disorder, that is life long and comprises a wide range of behavioral disorders. It has a prevalence of 1-2 per 1,000 with a broad range of severity. Multiple causes have been put forward and genetics plays the major role. According to DSM IV the main clinical manifestations include impaired social skills, language and non verbal communication and changes in range of interests and activities. Cognitive deficits are frequent but not universal. Perseveration, affective flatness and lack of insight into other people's thinking and feelings is conspicuous. The neurobiological basis of autism is unknown, but histopathological and biochemical findings suggest a diffuse disorder of neuronal development, most severe in the fronto temporal cortex, some limbic structures and in the cerebellum. At a biochemical level, abnormalities in serotonin and other neurotransmitters have been reported.

[Unusual causes of chronic meningitis, report of 5 cases]. / Causas inusuales de meningitis crónica, reporte de 5 casos.

Chronic meningitis is a frequent disease; it constitutes a real diagnostic challenge because of different etiologic possibilities, the most important being infectious, chemical, inflammatory, tumoral, autoimmune and of unknown origin. Chronic meningitis, as a rule, needs the use of a wide and expensive battery of studies, but frequently despite all this, it is not possible to make a diagnosis. Biopsies of meninges and brain play a key role in the study of this type of patients. We present five cases of chronic meningitis; some important considerations are made in relation to diagnosis and therapeutic management.

Causas inusuales de meningitis crónica, reporte de 5 casos / Unusual causes of chronic meningitis, report of 5 cases

Chronic meningitis is a frequent disease; it constitutes a real diagnostic challenge because of different etiologic possibilities, the most important being infectious, chemical, inflammatory, tumoral, autoimmune and of unknown origin. Chronic meningitis, as a rule, needs the use of a wide and expensive battery of studies, but frequently despite all this, it is not possible to make a diagnosis. Biopsies of meninges and brain play a key role in the study of this type of patients. We present five cases of chronic meningitis; some important considerations are made in relation to diagnosis and therapeutic management.

Epilepsia del adulto: estudio prospectivo de 130 casos / Epilepsy in the adult: prospective study of 130 cases

Introducción: la aparición de crisis epilépticas después de los 20 años de edad (epilepsia tardía) sucede en 20 a 25 por ciento de pacientes epilépticos. La etiología es muy variada e incluye cisticercosis, tumores, infartos cerebrales, etc. Aproximadamente 50 por ciento de estos pacientes presentan lesión cerebral estructural. Material y métodos: estudio prospectivo de 130 pacientes adultos con inicio de epilepsia después de los 20 años de edad, atendidos desde febrero de 1989 a junio de 1997. Todos los pacientes tuvieron TAC de cráneo y en aquellos que se consideró necesaria resonancia nuclear magnética cerebral. Resultados: se demostró lesión cerebral estructural en 51 por ciento de pacientes. La causa más frecuente fue la neurocisticercosis presente en 28 por ciento de casos, seguida de infarto cerebral (11 por ciento) y la atrofia cerebral (11 por ciento). Conclusiones. En nuestro medio la causa más frecuente de epilepsia del adulto sigue siendo la neurocisticercosis. Debido a la alta probabilidad de lesión estructural, todos estos pacientes deben estudiarse con TAC

Epilepsia mioclónica juvenil / Juvenile myoclonic epilepsy

La epilepsia mioclónica juvenil (EMJ) se presenta con una frecuencia alrededor de 4 a 10 por ciento de los pacientes con epilepsia; se caracteriza por su inicio en la adolescencia y por la presencia de crisis generalizadas de varios tipos: tónico-clónicas, ausencias y mioclónicas, en pacientes con un desarrollo neurológico normal. Esta forma de epilepsia fue descrita por janz hace 30 años y a pesar del tiempo transcurrido y de su frecuencia, es practicamante desconocida por el médico general, así como también por un alto porcentaje de especialistas. Estudiamos la presencia de EMJ en 20 pacientes, puntualizando sus características clínicas y su respuesta al tratamiento y hacemos una comparación con los datos publicados en la literatura. El objetivo del trabajo es llamar la atención hacia esta enfermedad y dar información para el diagnóstico y el tratamiento adecuados de la misma.