Responding to the challenges of Water and Global Warming: Environmental Hydrogeology and Global Change Research Group (HYGLO-Lab)

[EN] The current Global Warming of planet Earth is probably the most important geological phenomenon in the last 20,000 years of its history and for human race. This process is having nowadays notable effects on the climate, ecosystems and natural resources. Possibly the most important renewable geological resource is water. One of the most strategic phases of the water cycle is groundwater. Despite its low visibility, quantitatively (and qualitatively too) it is essential for life on Planet Earth. Foreseeable consequences on groundwater due to climate change and sea level rise will be very significant. Hydrogeology can provide answers to many of the questions that are beginning to be raised in relation to these impacts and their effects. Environmental hydrogeology is a way of understanding the set of disciplines mixed in Hydrogeology as a Science of Nature. The HYGLO-Lab Research Group of the IGME-CSIC National Center attempts, through its lines of research, with a double global and local component, to provide answers to some of these questions.Peer reviewe

Subsurface Geophysics and Geology (GEOFSU

[EN] The geophysics line at the IGME began in 1927 as a Geophysics Sectiondedicated to subsurface exploration. During all this time, it has been developed in order to support and give expert service in all IGME’s activities both as a geological service and public research institution, as well as a research and development work itself. On the other hand, in recent years the IGME has promoted a line of research aimed at the characterization and 3D modeling of geological structures and formations, the development of dedicated software and the evolution and sophistication of computer equipment. The new scenario of incorporation of the IGME to the CSIC as a national reference center in the field of Earth Sciences has allowed the establishment of the GEOFSUB Research Group (Subsurface Geophysics and Geology). It is constituted by 21 members who had been collaborating regularly of the IGME former scientific-technic areas Geophysics and remote sensing (Área de Geofísica y Teledetección) and Subsurface geology and 3D geological modelling (Área de Geología del Subsuelo y Modelización Geológica 3D). Our main differentiating element is our extensive knowledge of geophysical and geological techniques, which allows us to characterize the subsoil in an optimal waPeer reviewe

Diabetes Mellitus Glucose Prediction by Linear and Bayesian Ensemble Modeling

Diabetes Mellitus is a chronic disease of impaired blood glucose control due to degraded or absent bodily-specific insulin production, or utilization. To the affected, this in many cases implies relying on insulin injections and blood glucose measurements, in order to keep the blood glucose level within acceptable limits. Risks of developing short- and long-term complications, due to both too high and too low blood glucose concentrations are severalfold, and, generally, the glucose dynamics are not easy too fully comprehend for the affected individual—resulting in poor glucose control. To reduce the burden this implies to the patient and society, in terms of physiological and monetary costs, different technical solutions, based on closed or semi-closed loop blood glucose control, have been suggested. To this end, this thesis investigates simplified linear and merged models of glucose dynamics for the purpose of short-term prediction, developed within the EU FP7 DIAdvisor project. These models could, e.g., be used, in a decision support system, to alert the user of future low and high glucose levels, and, when implemented in a control framework, to suggest proactive actions. The simplified models were evaluated on 47 patient data records from the first DIAdvisor trial. Qualitatively physiological correct responses were imposed, and model-based prediction, up to two hours ahead, and specifically for low blood glucose detection, was evaluated. The glucose raising, and lowering effect of meals and insulin were estimated, together with the clinically relevant carbohydrate-to-insulin ratio. The model was further expanded to include the blood-to-interstitial lag, and tested for one patient data set. Finally, a novel algorithm for merging of multiple prediction models was developed and validated on both artificial data and 12 datasets from the second DIAdvisor trial

A real-time data mining technique applied for critical ECG rhythm on handheld device

Sudden cardiac arrest is often caused by ventricular arrhythmias and these episodes can lead to death for patients with chronic heart disease. Hence, detection of such arrhythmia is crucial in mobile ECG monitoring. In this research, a systematic study is carried out to investigate the possible limitations that are preventing the realisation of a real-time ECG arrhythmia data-mining algorithm suitable for application on mobile devices. Based on the findings, a computationally lightweight algorithm is devised and tested. Ventricular tachycardia (VT) is the most common type of ventricular arrhythmias and is also the deadliest.. A ventricular tachycardia (VT) episode is due to a disorder ofthe regular contractions ofthe heart. It occurs when the human heart ventricles generate a rapid heartbeat which disrupts the regular physiology cycle. The normal sinus rhythm (NSR) of a regular human heart beat signal has its signature PQRST waveform and in regular pattern. Whereas, the characteristics of a ventricular tachycardia (VT) signal waveforms are short R-R intervals, widen QRS duration and the absence of P-waves. Each type of ECG arrhythmia previously mentioned has a unique waveform signature that can be exploited as features to be used for the realization of an automated ECG analysis application. In order to extract this known ECG waveform feature, a time-domain analysis is proposed for feature extraction. Cross-correlation allows the computation of a co-efficient that quantifies the similarity between two times-series. Hence, by cross-correlating known ECG waveform templates with an unknown ECG signal, the coefficient can indicate the similarities. In previous published work, a preliminary study was carried out. The cross-correlation coefficient wave (CCW) technique was introduced for feature extraction. The outcome ofthis work presents CCW as a promising feature to differentiate between NSR, VT and Vfib signals. Moreover, cross-correlation computation does not require high computational overhead. Next, an automated detection algorithm requires a classification mechanism to make sense of the feature extracted. A further study is conducted and published, a fuzzy set k-NN classifier was introduced for the classification of CCW feature extracted from ECG signal segments. A training set of size 180 is used. The outcome of the study indicates that the computationally light-weight fuzzy k-NN classifier can reliably classify between NSR and VT signals, the class detection rate is low for classifying Vfib signal using the fuzzy k-NN classifier. Hence, a modified algorithm known as fuzzy hybrid classifier is proposed. By implementing an expert knowledge based fuzzy inference system for classification of ECG signal; the Vfib signal detection rate was improved. The comparison outcome was that the hybrid fuzzy classifier is able to achieve 91.1% correct rate, 100% sensitivity and 100% specificity. The previously mentioned result outperforms the compared classifiers. The proposed detection and classification algorithm is able to achieve high accuracy in analysing ECG signal feature of NSR, VT and Vfib nature. Moreover, the proposed classifier is successfully implemented on a smart mobile device and it is able to perform data-mining of the ECG signal with satisfiable results

Assessment of the flat-pannel membrane photobioreactor technology for wastewater treatment: Outdoor application to treat the effluent of an anaerobic membrane bioreactor

Tesis por compendio[ES] La combinación de reactores anaerobios de membranas (AnMBRs) con el cultivo de microalgas en un fotobiorreactor de membranas (MPBR) aparece como una opción ideal dentro del marco de tecnologías sostenibles para la depuración de aguas residuales. Con esta combinación de tecnologías, se puede obtener biogás a partir de la materia orgánica presente en el agua residual, mientras que los nutrientes del efluente de AnMBR se recuperan con la biomasa algal. Además, la tecnología de membranas permite obtener un efluente limpio y apto para su reutilización. Estudios previos han demostrado la capacidad de un cultivo de microalgas para recuperar los nutrientes presentes en el efluente de un sistema AnMBR a escala laboratorio. Sin embargo, el traslado de esta tecnología a condiciones controladas de laboratorio a condiciones ambientales variables puede suponer una limitación en su aplicación industrial. Este trabajo consiste en la evaluación del proceso de cultivo de microalgas en una planta piloto MPBR alimentada con el efluente de un sistema AnMBR. Para ello se han evaluado las condiciones óptimas de operación de la planta, teniendo en cuenta tanto el proceso biológico de microalgas como la velocidad de ensuciamiento de las membranas. También se ha estudiado el efecto de otros parámetros que influyen en el proceso, como la intensidad de luz aplicada a los fotobiorreactores (PBRs), temperatura, concentración de materia orgánica, presencia de otros organismos, etc.; así como el peso específico de cada parámetro dentro del proceso. Otro objetivo consiste en la búsqueda de nuevos parámetros de control del proceso que faciliten la operación en continuo del sistema. El sistema MPBR utilizado en este estudio se mostró capaz de tratar un efluente de AnMBR, cumpliendo con los límites legales de vertido. Sin embargo, esta operación se consiguió únicamente cuando se cumplían una serie de condiciones: i) El espesor de los fotobiorreactores era estrecho (10 cm). ii) Las condiciones de operación (BRT y HRT) se mantenían dentro del rango adecuado. iii) Temperatura se mantenía habitualmente debajo del límite máximo de 30 ºC. iv) No existía acumulación de nitrito. v) La fuente principal de nitrógeno era amonio. vi) La materia orgánica presente en el cultivo no era excesiva.[CA] La combinació de reactors anaerobis de membranes (AnMBRs) amb el cultiu de microalgues en un fotobioreactor de membranes (MPBR) apareix com una opció ideal dins el marc de tecnologies sostenibles per a la depuració d'aigües residuals. Amb aquesta combinació de tecnologies, es pot obtenir biogàs a partir de la matèria orgànica present en l'aigua residual, mentre que els nutrients de l'efluent de AnMBR es recuperen amb la biomassa algal. A més, la tecnologia de membranes permet obtenir un efluent net i apte per a la seua reutilització. Estudis previs han demostrat la capacitat d'un cultiu de microalgues per recuperar els nutrients presents en l'efluent d'un sistema AnMBR a escala laboratori. No obstant això, el trasllat d'aquesta tecnologia de condicions controlades de laboratori a condicions ambientals variables pot suposar una limitació en la seua aplicació industrial. Aquest treball consisteix en l'avaluació del procés de cultiu de microalgues en una planta pilot MPBR alimentada amb l'efluent d'un sistema AnMBR. Per a això s'han avaluat les condicions òptimes d'operació de la planta, tenint en compte tant el procés biològic de microalgues com la velocitat d'embrutiment de les membranes. També s'ha estudiat l'efecte d'altres paràmetres que influeixen en el procés, com la intensitat de llum aplicada als fotobioreactors (PBRs), temperatura, concentració de matèria orgànica, presència d'altres organismes, etc .; així com el pes específic de cada paràmetre dins del procés. Un altre objectiu consisteix en la recerca de nous paràmetres de control del procés que facilitin l'operació en continu del sistema. El sistema MPBR utilitzat en aquest estudi es va mostrar capaç de tractar un efluent de AnMBR, complint amb els límits legals d'abocament. No obstant això, aquesta operació es va aconseguir únicament quan es complien una sèrie de condicions: i) El gruix dels fotobioreactors era estret (10 cm). ii) Les condicions d'operació (BRT i HRT) es mantenien dins del rang adequat. iii) La temperatura es mantenia habitualment baix del límit màxim de 30 ºC. iv) No existia acumulació de nitrit. v) La font principal de nitrogen era amoni. vi) La matèria orgànica present en el cultiu no era excessiva.[EN] The combination of anaerobic membrane reactors (AnMBRs) and microalgae membrane photobioreactor (MPBR) appears as an ideal option within the framework of sustainable technologies for wastewater treatment. This combination enables to produce biogas from the organic matter present in wastewater, while the nutrient content of the AnMBR effluent can be recovered from microalgae biomass. In addition, membrane technology allows obtaining a water effluent which can be suitable for reclamation. Previous studies have proved the capability of a microalgae culture to recover the nutrients present in AnMBR effluent at lab scale. However, up-scaling from controlled lab conditions to varying outdoor conditions could limit the industrial applications of this technology. This study consists of the assessment of a microalgae culture in an MPBR pilot plant fed by effluent of an AnMBR system. For this, optimal operating conditions of the MPBR plant were evaluated, considering both the microalgae biological process and the membrane fouling rate. The effect of other parameters that have an influence on the process such as light intensity applied to the photobioreactors (PBRs), temperature, organic matter concentration, presence of other organisms, etc., was also studied; as well as the specific weight of each parameter on the process. Another goal consisted of finding new controlling parameters that ease the continuous operation of the system. The MPBR system used in this study showed appeared to be capable of treating AnMBR effluent, successfully accomplishing legal discharge limits. However, this was only achieved when the following conditions were reached: i) PBR light path was as narrow as 10 cm. ii) Operating conditions (BRT and HRT) were in the appropriate range. iii) Temperature was under the máximum limit of around 30 ºC. iv) Nitrite was not accumulated. v) Ammonium was the main nitrogen source. vi) Organic matter concentration in the culture was not high.González Camejo, J. (2019). Assessment of the flat-pannel membrane photobioreactor technology for wastewater treatment: Outdoor application to treat the effluent of an anaerobic membrane bioreactor [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/133056TESISCompendi

Resource Management for Edge Computing in Internet of Things (IoT)

Die große Anzahl an Geräten im Internet der Dinge (IoT) und deren kontinuierliche Datensammlungen führen zu einem rapiden Wachstum der gesammelten Datenmenge. Die Daten komplett mittels zentraler Cloud Server zu verarbeiten ist ineffizient und zum Teil sogar unmöglich oder unnötig. Darum wird die Datenverarbeitung an den Rand des Netzwerks verschoben, was zu den Konzepten des Edge Computings geführt hat. Informationsverarbeitung nahe an der Datenquelle (z.B. auf Gateways und Edge Geräten) reduziert nicht nur die hohe Arbeitslast zentraler Server und Netzwerke, sondern verringer auch die Latenz für Echtzeitanwendungen, da die potentiell unzuverlässige Kommunikation zu Cloud Servern mit ihrer unvorhersehbaren Netzwerklatenz vermieden wird. Aktuelle IoT Architekturen verwenden Gateways, um anwendungsspezifische Verbindungen zu IoT Geräten herzustellen. In typischen Konfigurationen teilen sich mehrere IoT Edge Geräte ein IoT Gateway. Wegen der begrenzten verfügbaren Bandbreite und Rechenkapazität eines IoT Gateways muss die Servicequalität (SQ) der verbundenen IoT Edge Geräte über die Zeit angepasst werden. Nicht nur um die Anforderungen der einzelnen Nutzer der IoT Geräte zu erfüllen, sondern auch um die SQBedürfnisse der anderen IoT Edge Geräte desselben Gateways zu tolerieren. Diese Arbeit untersucht zuerst essentielle Technologien für IoT und existierende Trends. Dabei werden charakteristische Eigenschaften von IoT für die Embedded Domäne, sowie eine umfassende IoT Perspektive für Eingebettete Systeme vorgestellt. Mehrere Anwendungen aus dem Gesundheitsbereich werden untersucht und implementiert, um ein Model für deren Datenverarbeitungssoftware abzuleiten. Dieses Anwendungsmodell hilft bei der Identifikation verschiedener Betriebsmodi. IoT Systeme erwarten von den Edge Geräten, dass sie mehrere Betriebsmodi unterstützen, um sich während des Betriebs an wechselnde Szenarien anpassen zu können. Z.B. Energiesparmodi bei geringen Batteriereserven trotz gleichzeitiger Aufrechterhaltung der kritischen Funktionalität oder einen Modus, um die Servicequalität auf Wunsch des Nutzers zu erhöhen etc. Diese Modi verwenden entweder verschiedene Auslagerungsschemata (z.B. die übertragung von Rohdaten, von partiell bearbeiteten Daten, oder nur des finalen Ergebnisses) oder verschiedene Servicequalitäten. Betriebsmodi unterscheiden sich in ihren Ressourcenanforderungen sowohl auf dem Gerät (z.B. Energieverbrauch), wie auch auf dem Gateway (z.B. Kommunikationsbandbreite, Rechenleistung, Speicher etc.). Die Auswahl des besten Betriebsmodus für Edge Geräte ist eine Herausforderung in Anbetracht der begrenzten Ressourcen am Rand des Netzwerks (z.B. Bandbreite und Rechenleistung des gemeinsamen Gateways), diverser Randbedingungen der IoT Edge Geräte (z.B. Batterielaufzeit, Servicequalität etc.) und der Laufzeitvariabilität am Rand der IoT Infrastruktur. In dieser Arbeit werden schnelle und effiziente Auswahltechniken für Betriebsmodi entwickelt und präsentiert. Wenn sich IoT Geräte in der Reichweite mehrerer Gateways befinden, ist die Verwaltung der gemeinsamen Ressourcen und die Auswahl der Betriebsmodi für die IoT Geräte sogar noch komplexer. In dieser Arbeit wird ein verteilter handelsorientierter Geräteverwaltungsmechanismus für IoT Systeme mit mehreren Gateways präsentiert. Dieser Mechanismus zielt auf das kombinierte Problem des Bindens (d.h. ein Gateway für jedes IoT Gerät bestimmen) und der Allokation (d.h. die zugewiesenen Ressourcen für jedes Gerät bestimmen) ab. Beginnend mit einer initialen Konfiguration verhandeln und kommunizieren die Gateways miteinander und migrieren IoT Geräte zwischen den Gateways, wenn es den Nutzen für das Gesamtsystem erhöht. In dieser Arbeit werden auch anwendungsspezifische Optimierungen für IoT Geräte vorgestellt. Drei Anwendungen für den Gesundheitsbereich wurden realisiert und für tragbare IoT Geräte untersucht. Es wird auch eine neuartige Kompressionsmethode vorgestellt, die speziell für IoT Anwendungen geeignet ist, die Bio-Signale für Gesundheitsüberwachungen verarbeiten. Diese Technik reduziert die zu übertragende Datenmenge des IoT Gerätes, wodurch die Ressourcenauslastung auf dem Gerät und dem gemeinsamen Gateway reduziert wird. Um die vorgeschlagenen Techniken und Mechanismen zu evaluieren, wurden einige Anwendungen auf IoT Plattformen untersucht, um ihre Parameter, wie die Ausführungszeit und Ressourcennutzung, zu bestimmen. Diese Parameter wurden dann in einem Rahmenwerk verwendet, welches das IoT Netzwerk modelliert, die Interaktion zwischen Geräten und Gateway erfasst und den Kommunikationsoverhead sowie die erreichte Batterielebenszeit und Servicequalität der Geräte misst. Die Algorithmen zur Auswahl der Betriebsmodi wurden zusätzlich auf IoT Plattformen implementiert, um ihre Overheads bzgl. Ausführungszeit und Speicherverbrauch zu messen

Spatial statistics and analysis of earth's ionosphere

Thesis (Ph.D.)--Boston UniversityThe ionosphere, a layer of Earths upper atmosphere characterized by energetic charged particles, serves as a natural plasma laboratory and supplies proxy diagnostics of space weather drivers in the magnetosphere and the solar wind. The ionosphere is a highly dynamic medium, and the spatial structure of observed features (such as auroral light emissions, charge density, temperature, etc.) is rich with information when analyzed in the context of fluid, electromagnetic, and chemical models. Obtaining measurements with higher spatial and temporal resolution is clearly advantageous. For instance, measurements obtained with a new electronically-steerable incoherent scatter radar (ISR) present a unique space-time perspective compared to those of a dish-based ISR. However, there are unique ambiguities for this modality which must be carefully considered. The ISR target is stochastic, and the fidelity of fitted parameters (ionospheric densities and temperatures) requires integrated sampling, creating a tradeoff between measurement uncertainty and spatio-temporal resolution. Spatial statistics formalizes the relationship between spatially dispersed observations and the underlying process(es) they represent. A spatial process is regarded as a random field with its distribution structured (e.g., through a correlation function) such that data, sampled over a spatial domain, support inference or prediction of the process. Quantification of uncertainty, an important component of scientific data analysis, is a core value of spatial statistics. This research applies the formalism of spatial statistics to the analysis of Earth's ionosphere using remote sensing diagnostics. In the first part, we consider the problem of volumetric imaging using phased-array ISR based on optimal spatial prediction ("kriging"). In the second part, we develop a technique for reconstructing two-dimensional ion flow fields from line-of-sight projections using Tikhonov regularization. In the third part, we adapt our spatial statistical approach to global ionospheric imaging using total electron content (TEC) measurements derived from navigation satellite signals

Modelling heat transfer and respiration of occupants in indoor climate

Although the terms "Human Thermal Comfort" and "Indoor Air Quality (IAQ)" can be highly subjective, they still dictate the indoor climate design (HVAC design) of a building. In order to evaluate human thermal comfort and IAQ, one of three main tools are used, a) direct questioning the subjects about their thermal and air quality sensation (voting, sampling etc.), b) measuring the human thermal comfort by recording the physical parameters such as relative humidity, air and radiation temperature, air velocities and concentration gradients of pollutants or c) by using numerical simulations either including or excluding detailed thermo-physiological models. The application of the first two approaches can only take place in post commissioning and/or testing phases of the building. Use of numerical techniques can however be employed at any stage of the building design. With the rapid development in computational hard- and software technology, the costs involved in numerical studies has reduced compared to detailed tests. Employing numerical modelling to investigate human thermal comfort and IAQ however demand thorough verification and validation studies. Such studies are used to understand the limitations and application of numerical modelling of human thermal comfort and IAQ in indoor climates. This PhD research is an endeavour to verify, validate and apply, numerical simulation for modelling heat transfer and respiration of occupants in indoor climates. Along with the investigations concerning convective and radiation heat transfer between the occupants and their surroundings, the work focuses on detailed respiration modelling of sedentary human occupants. The objectives of the work have been to: verify the convective and radiation numerical models; validate them for buoyancy-driven flows due to human occupants in indoor climates; and apply these validated models for investigating human thermal comfort and IAQ in a real classroom for which field study data was available. On the basis of the detailed verification, validation and application studies, the findings are summarized as a set of guidelines for simulating human thermal comfort and IAQ in indoor climates. This PhD research involves the use of detailed human body geometries and postures. Modelling radiation and investigating the effect of geometrical posture has shown that the effective radiation area varies significantly with posture. The simulation results have shown that by using an effective radiation area factor of 0.725, estimated previously (Fanger, 1972) for a standing person, can lead to an underestimation of effective radiation area by 13% for the postures considered. Numerical modelling of convective heat transfer and respiration processes for sedentary manikins have shown that the SST turbulence model (Menter, 1994) with appropriate resolution of near wall region can simulate the local air velocity, temperature and heat transfer coefficients to a level of detail required for prediction of thermal comfort and IAQ. The present PhD work has shown that in a convection dominated environment, the detailed seated manikins give rise to an asymmetrical thermal plume as compared to the thermal plumes generated by simplified manikins or point sources. Validated simulation results obtained during the present PhD work have shown that simplified manikins can be used without significant limitations while investigating IAQ of complete indoor spaces. The use of simplified manikins however does not seem appropriate when simulating detailed respiration effects in the immediate vicinity of seated humans because of the underestimation in the amount of re-inhaled CO2 and pollutants from the surroundings. Furthermore, the results have shown that due to the simplification in geometrical form of the nostrils, the CO2 concentration is much higher near the face region (direct jet along the nostrils) as compared to a detailed geometry (sideways jet). Simulating the complete respiration cycle has shown that a pause between exhalation and inhalation has a significant effect on the amount of re-inhaled CO2. Previous results have shown the amount of re-inhaled CO2 to range between 10 - 19%. The present study has shown that by considering the pause, this amount of re-inhaled CO2 falls down to values lower than 1%. A comparison between the simplified and detailed geometry has shown that a simplified geometry can cause an underestimation in the amount of re-inhaled CO2 by more than 37% as compared to a detailed geometry. The major contribution to knowledge delivered by this PhD work is the provision of a validated seated computational thermal manikin. This PhD work follows a structured verification and validation approach for conducting CFD simulations to predict human thermal comfort and indoor air quality. The work demonstrates the application of the validated model to a classroom case with multiple occupancy and compares the measured results with the simulation results. The comparison of CFD results with measured data advocates the use of CFD and visualizes the importance of modelling thermal manikins in indoor HVAC design rather than designing the HVAC by considering empty spaces as the occupancy has a strong influence on the indoor air flow. This PhD work enables the indoor climate researchers and building designers to employ simplified thermal manikin to correctly predict the mean flow characteristics in indoor surroundings. The present work clearly demonstrates the limitation of the PIV measurement technique, the importance of using detailed CFD manikin geometry when investigating the phenomena of respiration in detail and the effect of thermal plume around the seated manikin. This computational thermal manikin used in this work is valid for a seated adult female geometry