Concise server-wide causality management for eventually consistent data stores

Large scale distributed data stores rely on optimistic replication to scale and remain highly available in the face of net work partitions. Managing data without coordination results in eventually consistent data stores that allow for concurrent data updates. These systems often use anti-entropy mechanisms (like Merkle Trees) to detect and repair divergent data versions across nodes. However, in practice hash-based data structures are too expensive for large amounts of data and create too many false conflicts. Another aspect of eventual consistency is detecting write conflicts. Logical clocks are often used to track data causality, necessary to detect causally concurrent writes on the same key. However, there is a nonnegligible metadata overhead per key, which also keeps growing with time, proportional with the node churn rate. Another challenge is deleting keys while respecting causality: while the values can be deleted, perkey metadata cannot be permanently removed without coordination. Weintroduceanewcausalitymanagementframeworkforeventuallyconsistentdatastores,thatleveragesnodelogicalclocks(BitmappedVersion Vectors) and a new key logical clock (Dotted Causal Container) to provides advantages on multiple fronts: 1) a new efficient and lightweight anti-entropy mechanism; 2) greatly reduced per-key causality metadata size; 3) accurate key deletes without permanent metadata.

Interrelationship between partition behavior of organic compounds and proteins in aqueous dextran-Polyethylene glycol and Polyethylene glycol-sodium sulfate two-phase systems

Partition behavior of adenosine and guanine mononucleotides was examined in aqueous dextran-polyethylene glycol (PEG) and PEG-sodium sulfate two-phase systems. The partition coefficients for each series of mononucleotides were analyzed as a functions of the number of phosphate groups and found to be dependent on the nature of nucleic base and on the type of \ATPS\ utilized. It was concluded that an average contribution of a phosphate group into logarithm of partition coefficient of a mononucleotide cannot be used to estimate the difference between the electrostatic properties of the coexisting phases of ATPS. The data obtained in this study were considered together with those for other organic compounds and proteins reported previously, and the linear interrelationship between logarithms of partition coefficients in dextran-PEG, PEG-Na2SO4 and PEG-Na2SO4-0.215 M NaCl (all in 0.01 M Na- or K/Na-phosphate buffer, pH 7.4 or 6.8) was established. Similar relationship was found for the previously reported data for proteins in Dex-PEG, PEG-600-Na2SO4, and PEG-8000-Na2SO4 ATPS. It is suggested that the linear relationships of the kind established in \ATPS\ may be observed for biological properties of compounds as well.

Sefficiency (sustainable efficiency) of water–energy–food entangled systems

Supplemental data for this article can be accessed at http://dx.doi.org/10.1080/07900627.2015.1070091. It includes an easy-to-use spreadsheet that calculates the efficiencies used in this paper, that is Sefficiency with energy considerations.

SOFHIA: a CAD environment to design digital control systems

"Series Title: IFIP - The International Federation for Information Processing, ISSN 1868-4238"

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

In-line rheo-optical microstructural characterization of complex polymer systems

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos.

Vapor - liquid equilibrium of systems containing perfluoromethyl-cyclohexane and hydrocarbons

Vapor - liquid equilibrium data for the binary systems: Perfluoromethylcyclohexane + n-Hexane and Perfluoromethylcyclohexane + 1-Hexene were determined at 93.3 KPa and 328.15 K. The vapor pressure for the pure components were also measured to calculate the Antoine constants. The data were correlated by using the Van-Laar, Margules, Wilson, NRTL and UNIQUAC equations. UNIFAC group-contribution parameters between CH, and CF,, and CH,=CH and CF, were also calculated.

Sistemas de Tipos para Verificación de Programas Concurrentes. Type Systems for Concurrent Programs Verification.

La programación concurrente es una tarea difícil aún para los más experimentados programadores. Las investigaciones en concurrencia han dado como resultado una gran cantidad de mecanismos y herramientas para resolver problemas de condiciones de carrera de datos y deadlocks, problemas que surgen por el mal uso de los mecanismos de sincronización. La verificación de propiedades interesantes de programas concurrentes presenta dificultades extras a los programas secuenciales debido al no-determinismo de su ejecución, lo cual resulta en una explosión en el número de posibles estados de programa, haciendo casi imposible un tratamiento manual o aún con la ayuda de computadoras. Algunos enfoques se basan en la creación de lenguajes de programación con construcciones con un alto nivel de abstración para expresar concurrencia y sincronización. Otros enfoques tratan de desarrollar técnicas y métodos de razonamiento para demostrar propiedades, algunos usan demostradores de teoremas generales, model-checking o algortimos específicos sobre un determinado sistema de tipos. Los enfoques basados en análisis estático liviano utilizan técnicas como interpretación abstracta para detectar ciertos tipos de errores, de una manera conservativa. Estas técnicas generalmente escalan lo suficiente para aplicarse en grandes proyectos de software pero los tipos de errores que pueden detectar es limitada. Algunas propiedades interesantes están relacionadas a condiciones de carrera y deadlocks, mientras que otros están interesados en problemas relacionados con la seguridad de los sistemas, como confidencialidad e integridad de datos. Los principales objetivos de esta propuesta es identificar algunas propiedades de interés a verificar en sistemas concurrentes y desarrollar técnicas y herramientas para realizar la verificación en forma automática. Para lograr estos objetivos, se pondrá énfasis en el estudio y desarrollo de sistemas de tipos como tipos dependientes, sistema de tipos y efectos, y tipos de efectos sensibles al flujo de datos y control. Estos sistemas de tipos se aplicarán a algunos modelos de programación concurrente como por ejemplo, en Simple Concurrent Object-Oriented Programming (SCOOP) y Java. Además se abordarán propiedades de seguridad usando sistemas de tipos específicos. Concurrent programming has remained a dificult task even for very experienced programmers. Concurrency research has provided a rich set of tools and mechanisms for dealing with data races and deadlocks that arise of incorrect use of synchronization. Verification of most interesting properties of concurrent programs is a very dificult task due to intrinsic non-deterministic nature of concurrency, resulting in a state explosion which make it almost imposible to be manually treat and it is a serious challenge to do that even with help of computers. Some approaches attempts create programming languages with higher levels of abstraction for expressing concurrency and synchronization. Other approaches try to develop reasoning methods to prove properties, either using general theorem provers, model-checking or specific algorithms on some type systems. The light-weight static analysis approach apply techniques like abstract interpretation to find certain kind of bugs in a conservative way. This techniques scale well to be applied in large software projects but the kind of bugs they may find are limited. Some interesting properties are related to data races and deadlocks, while others are interested in some security problems like confidentiality and integrity of data. The main goals of this proposal is to identify some interesting properties to verify in concurrent systems and develop techniques and tools to do full automatic verification. The main approach will be the application of type systems, as dependent types, type and effect systems, and flow-efect types. Those type systems will be applied to some models for concurrent programming as Simple Concurrent Object-Oriented Programming (SCOOP) and Java. Other goals include the analysis of security properties also using specific type systems.

Electroquímica de sustancias de interés en los sistemas agroalimentario y de sanidad animal. Desarrollo de biosensores electroquímicos. Aplicaciones analíticas.Electrochemistry of substances of interest in agroalimentary and animal health systems. Development of electrochemical biosensors. Analytical applications.

Se estudiarán los mecanismos de reacción electroquímica de las micotoxinas (metabolitos tóxicos generados por hongos) citrinina (CIT), patulina (PAT) y moniliformina (MON), de los antioxidantes naturales alfa, beta, gama y delta tocoferoles, de los flavonoides fisetina (FIS), morina (MOR), luteolina (LUT), rutina (RUT), buteina (BUT), naringenina (NAR) y miricetina (MIR) y de las hormonas esteroides estradiol (EDIOL), estrona (EONA) y estriol (ETRIOL). Por otra parte, se implementarán técnicas electroanalíticas para la detección y cuantificación de estos sustratos en muestras de matrices naturales que los contengan. Se realizará el diseño y caracterización de biosensores enzimáticos a partir de peroxidasas y/o fosfatasa alcalina para la determinación de la micotoxina CIT y de los flavonoides y, por otro, de inmunosensores para las micotoxinas ocratoxina A (OTA) y PAT y hormonas. Para el anclaje de enzimas y/o anticuerpos, se estudiarán las propiedades de electrodos modificados por monocapas autoensambladas, nanotubos de carbono y partículas magnéticas. Se usarán las técnicas de voltamperometría cíclica, de onda cuadrada y de redisolución con acumulación adsortiva, espectroscopías de impedancia electroquímica, electrólisis a potencial controlado, uv-vis e IR, microbalanza de cristal de cuarzo y microscopías de alta resolución (SEM, TEM, AFM). La importancia de este proyecto apunta a la obtención de nuevos datos electroquímicos de los sustratos indicados y conocimientos relacionados con la aplicación de electrodos modificados en la preparación de biosensores y en el desarrollo de técnicas alternativas para la determinación de los analitos mencionados precedentemente. Electrochemical reaction mechanisms of mycotoxins (toxic metabolites generated by fungi) citrinin (CIT), Patulin (PAT) and moniliformin (MON), natural antioxidants alpha, beta, gamma and delta tocopherols, flavonoids fisetin (FIS), morin (MOR), luteolin (LUT), rutin (RUT), butein (BUT), naringenin (NAR), miricetin (MIR) and steroid hormones estradiol (EDIOL), estrone (EONA) and estriole (ETRIOL) will be explored. On the other hand, electroanalytical techniques for the detection and quantification of these substrates in samples of natural matrices will be implemented. The design and characterization of enzymatic biosensors from peroxidases and/or from alkaline phosphatase for the determination of CIT and flavonoids, and also of inmunosensors for ochratoxin A (OTA) and PAT and hormones will be performed. For the anchor of enzymes and/or antibody, properties of electrodes modified by self assembled monolayers, carbon nanotubes and magnetic particles will be explored. Cyclic, square wave and adsorptive stripping voltammetries, electrochemical impedance spectroscopy, controlled potential electrolysis, uv-vis and IR, quartz crystal microbalance and high-resolution microcopies (SEM, TEM, AFM) will be used. The importance of this project is aimed at obtaining new electrochemical data for the indicated substrates and knowledge on the application of modified electrodes in preparation of biosensors and in the development of alternative techniques for the determination of the above-mentioned analytes.

Development of a data acquisition system to characterise sustainable energy technologies and to support Web-Based learning (DAQ-WBL)

Driven by concerns about rising energy costs, security of supply and climate change a new wave of Sustainable Energy Technologies (SET’s) have been embraced by the Irish consumer. Such systems as solar collectors, heat pumps and biomass boilers have become common due to government backed financial incentives and revisions of the building regulations. However, there is a deficit of knowledge and understanding of how these technologies operate and perform under Ireland’s maritime climate. This AQ-WBL project was designed to address both these needs by developing a Data Acquisition (DAQ) system to monitor the performance of such technologies and a web-based learning environment to disseminate performance characteristics and supplementary information about these systems. A DAQ system consisting of 108 sensors was developed as part of Galway-Mayo Institute of Technology’s (GMIT’s) Centre for the Integration of Sustainable EnergyTechnologies (CiSET) in an effort to benchmark the performance of solar thermal collectors and Ground Source Heat Pumps (GSHP’s) under Irish maritime climate, research new methods of integrating these systems within the built environment and raise awareness of SET’s. It has operated reliably for over 2 years and has acquired over 25 million data points. Raising awareness of these SET’s is carried out through the dissemination of the performance data through an online learning environment. A learning environment was created to provide different user groups with a basic understanding of a SET’s with the support of performance data, through a novel 5 step learning process and two examples were developed for the solar thermal collectors and the weather station which can be viewed at http://www.kdp 1 .aquaculture.ie/index.aspx. This online learning environment has been demonstrated to and well received by different groups of GMIT’s undergraduate students and plans have been made to develop it further to support education, awareness, research and regional development.

Computer integrated testing for the transport refrigeration systems industry.

This is a study of a state of the art implementation of a new computer integrated testing (CIT) facility within a company that designs and manufactures transport refrigeration systems. The aim was to use state of the art hardware, software and planning procedures in the design and implementation of three CIT systems. Typical CIT system components include data acquisition (DAQ) equipment, application and analysis software, communication devices, computer-based instrumentation and computer technology. It is shown that the introduction of computer technology into the area of testing can have a major effect on such issues as efficiency, flexibility, data accuracy, test quality, data integrity and much more. Findings reaffirm how the overall area of computer integration continues to benefit any organisation, but with more recent advances in computer technology, communication methods and software capabilities, less expensive more sophisticated test solutions are now possible. This allows more organisations to benefit from the many advantages associated with CIT. Examples of computer integration test set-ups and the benefits associated with computer integration have been discussed.

A nutrient balance model for typical Irish farming systems

The twin objectives of the work described were to construct nutrient balance models (NBM) for a range of Irish animal production systems and to evaluate their potential as a means of estimating the nutrient composition of farm wastes. The NBM has three components. The first is the intake of nutrients in the animal's diet. The second is retention or the nutrients the animal retains for the production of milk, meat or eggs. The third is the balance or the difference between the nutrient intake and retention. Data on the intake levels and their nutrient value for dairy cows, beef cattle, pigs and poultry systems were assembled. Literature searches and interviews with National experts were the primary sources of information. NBMs were then constructed for each production system. Summary tables of the nutrient values for the common diet constituents used in Irish animal production systems, the nutrient composition of the animal products and the NBMs (nutrient intake, retention and excretion) for a range of production systems were assembled. These represent the first comprehensive data set of this type for Irish animal production systems. There was generally good agreement between the derived NBMs values and those published in the literature. The NBMs were validated on a number of farms. Data on animal numbers, fertiliser use, concentrates inputs and production output were recorded on seven farms. Using the data a nutrient input/output balance was constructed for each farm. This was compared with the NBM estimate of the farm nutrient balance. The results showed good agreement between the measured balance and the NBM estimate particularly for the pig and poultry farms. However, the validation emphasised the inherent risks associated with NBMs. The average values used for feed intake and production parameters in the NEMs may result in the under or over estimate of actual nutrient balances on individual farms where these variables are substantially different. On the grassland farms there was a poor correlation between the input/output estimate and the NBM. This possibly results from the omission of the soil's contribution to the nutrient balance. However, the results indicate that the NBMs developed are a potentially useful tool for estimating nutrient balances. They also will serve to highlight the significant fraction of the nutrient inputs into farming systems that are retained on the farm. The potential of the NBM as a means of estimating the nutrient composition of farm wastes was evaluated on two farms. Feed intake and composition, animal production, slurry production was monitored during the indoor winter feeding period. Slurry samples were taken for analysis. The appropriates NBMs were used to estimate the nutrient balance for each farm. The nutrient content of the slurry produced was calculated. There was a good agreement between the NBM estimate and the measured values. This preliminary evaluation suggests that the NBM has a potential to provide the farmer with a simple means of estimating the nutrient value of his slurry.

Knowledge, networks of cities and growth in regional urban systems

The objective of this paper is to measure the impact of different kinds of knowledge and external economies on urban growth in an intraregional context. The main hypothesis is that knowledge leads to growth, and that this knowledge is related to the existence of agglomeration and network externalities in cities. We develop a three-tage methodology: first, we measure the amount and growth of knowledge in cities using the OCDE (2003) classification and employment data; second, we identify the spatial structure of the area of analysis (networks of cities); third, we combine the Glaeser - Henderson - De Lucio models with spatial econometric specifications in order to contrast the existence of spatially static (agglomeration) and spatially dynamic (network) external economies in an urban growth model. Results suggest that higher growth rates are associated to higher levels of technology and knowledge. The growth of the different kinds of knowledge is related to local and spatial factors (agglomeration and network externalities) and each knowledge intensity shows a particular response to these factors. These results have implications for policy design, since we can forecast and intervene on local knowledge development paths.