Assessment of CO2 adsorption capacity on activated carbons by a combination of batch and dynamic tests

In this work, batch and dynamic adsorption tests are coupled for an accurate evaluation of CO2 adsorption performance for three different activated carbons obtained from olives stones by chemical activation followed by physical activation with CO2 at varying times, i.e. 20, 40 and 60 h. Kinetic and thermodynamic CO2 adsorption tests from simulated flue-gas at different temperature and CO2 pressure are carried out both in batch (a manometric equipment operating with pure CO2) and dynamic (a lab-scale fixed-bed column operating with CO2/N2 mixture) conditions. The textural characterization of the activated carbon samples shows a direct dependence of both micropore and ultramicropore volume on the activation time, hence AC60 has the higher contribution. The adsorption tests conducted at 273 and 293 K showed that, when CO2 pressure is lower than 0.3 bar, the lower the activation time the higher CO2 adsorption capacity and a ranking ωeq(AC20)>ωeq(AC40)>ωeq(AC60) can be exactly defined when T= 293 K. This result can be likely ascribed to a narrower pore size distribution of the AC20 sample, whose smaller pores are more effective for CO2 capture at higher temperature and lower CO2 pressure, the latter representing operating conditions of major interest for decarbonation of a flue-gas effluent. Moreover, the experimental results obtained from dynamic tests confirm the results derived from the batch tests in terms of CO2 adsorption capacity. It is important to highlight that the adsorption of N2 on the synthesized AC samples can be considered negligible. Finally, the importance of a proper analysis of characterization data and adsorption experimental results is highlighted for a correct assessment of CO2 removal performances of activated carbons at different CO2 pressure and operating temperature.

On the existence of fractal strings whose set of dimensions of fractality is not perfect

In this paper we give an example of a nonlattice self-similar fractal string such that the set of real parts of their complex dimensions has an isolated point. This proves that, in general, the set of dimensions of fractality of a fractal string is not a perfect set.

Logic-Based Outer Approximation for the Design of Discrete-Continuous Dynamic Systems with Implicit Discontinuities

We address the optimization of discrete-continuous dynamic optimization problems using a disjunctive multistage modeling framework, with implicit discontinuities, which increases the problem complexity since the number of continuous phases and discrete events is not known a-priori. After setting a fixed alternative sequence of modes, we convert the infinite-dimensional continuous mixed-logic dynamic (MLDO) problem into a finite dimensional discretized GDP problem by orthogonal collocation on finite elements. We use the Logic-based Outer Approximation algorithm to fully exploit the structure of the GDP representation of the problem. This modelling framework is illustrated with an optimization problem with implicit discontinuities (diver problem).

On the Result of Invariance of the Closure Set of the Real Projections of the Zeros of an Important Class of Exponential Polynomials

In this paper we provide the proof of a practical point-wise characterization of the set RP defined by the closure set of the real projections of the zeros of an exponential polynomial P(z) = Σn j=1 cjewjz with real frequencies wj linearly independent over the rationals. As a consequence, we give a complete description of the set RP and prove its invariance with respect to the moduli of the c′ js, which allows us to determine exactly the gaps of RP and the extremes of the critical interval of P(z) by solving inequations with positive real numbers. Finally, we analyse the converse of this result of invariance.

A Belief System's Organization Based on a Computational Model of the Dynamic Context: First Approximation

In this article we present a model of organization of a belief system based on a set of binary recursive functions that characterize the dynamic context that modifies the beliefs. The initial beliefs are modeled by a set of two-bit words that grow, update, and generate other beliefs as the different experiences of the dynamic context appear. Reason is presented as an emergent effect of the experience on the beliefs. The system presents a layered structure that allows a functional organization of the belief system. Our approach seems suitable to model different ways of thinking and to apply to different realistic scenarios such as ideologies.

Design of online practical lessons in colorimetry

Applied colorimetry is an important module in the program of the elective subject "Colour Science: industrial applications”. This course is taught in the Optics and Optometry Degree and it has been used as a testing for the application of new teaching and assessment techniques consistent with the new European Higher Education Area. In particular, the main objective was to reduce the attendance to lessons and encourage the individual and collective work of students. The reason for this approach is based on the idea that students are able to work at their own learning pace. Within this dynamic work, we propose online lab practice based on Excel templates that our research group has developed ad-hoc for different aspects of colorimetry, such as conversion to different colour spaces, calculation of perceptual descriptors (hue, saturation, lightness), calculation of colour differences, colour matching dyes, etc. The practice presented in this paper is focused on the learning of colour differences. The session is based on a specific Excel template to compute the colour differences and to plot different graphs with these colour differences defined at different colour spaces: CIE ΔE, CIE ΔE94 and the CIELAB colour space. This template is implemented on a website what works by addressing the student work at a proper and organized way. The aim was to unify all the student work from a website, therefore the student is able to learn in an autonomous and sequential way and in his own pace. To achieve this purpose, all the tools, links and documents are collected for each different proposed activity to achieve guided specific objectives. In the context of educational innovation, this type of website is normally called WebQuest. The design of a WebQuest is established according to the criteria of usability and simplicity. There are great advantages of using WebQuests versus the toolbox “Campus Virtual” available in the University of Alicante. The Campus Virtual is an unfriendly environment for this specific purpose as the activities are organized in different sectors depending on whether the activity is a discussion, an activity, a self-assessment or the download of materials. With this separation, it is more difficult that the student follows an organized sequence. However, our WebQuest provides a more intuitive graphical environment, and besides, all the tasks and resources needed to complete them are grouped and organized according to a linear sequence. In this way, the student guided learning is optimized. Furthermore, with this simplification, the student focuses on learning and not to waste resources. Finally, this tool has a wide set of potential applications: online courses of colorimetry applied for postgraduate students, Open Course Ware, etc.

MDWEnet: a practical approach to achieving interoperability of model-driven web engineering methods

Current model-driven Web Engineering approaches (such as OO-H, UWE or WebML) provide a set of methods and supporting tools for a systematic design and development of Web applications. Each method addresses different concerns using separate models (content, navigation, presentation, business logic, etc.), and provide model compilers that produce most of the logic and Web pages of the application from these models. However, these proposals also have some limitations, especially for exchanging models or representing further modeling concerns, such as architectural styles, technology independence, or distribution. A possible solution to these issues is provided by making model-driven Web Engineering proposals interoperate, being able to complement each other, and to exchange models between the different tools. MDWEnet is a recent initiative started by a small group of researchers working on model-driven Web Engineering (MDWE). Its goal is to improve current practices and tools for the model-driven development of Web applications for better interoperability. The proposal is based on the strengths of current model-driven Web Engineering methods, and the existing experience and knowledge in the field. This paper presents the background, motivation, scope, and objectives of MDWEnet. Furthermore, it reports on the MDWEnet results and achievements so far, and its future plan of actions.

Effects of static stretching following a dynamic warm-up on speed, agility and power

Static stretching prior to sport has been shown to decrease force production in comparison to the increasing popularity of dynamic warm-up methods. However some athletes continue to use a bout of static stretching following dynamic methods. The purpose of this study was to investigate the effects on speed, agility and power following a period of additional static stretching following a dynamic warm-up routine. Twenty-five male University students who participated in team sports performed two warm-up protocols concentrating on the lower body one week apart through a randomised cross over design. The dynamic warm-up (DW) protocol used a series of specific progressive exercises lasting 10 minutes over a distance of 20m. The dynamic warm-up plus static stretching (DWS) protocol used the same DW protocol followed by a 5 minute period during which 7 muscle groups were stretched. Following each warm-up the subjects performed a countermovement vertical jump, 20m sprint and Illinois agility test, 1 minute apart. The results demonstrated no significant differences in speed, agility and jump performance following the two protocols DW and DWS. The study concludes that performing static stretching following a dynamic warm-up prior to performance does not significantly affect speed, agility and vertical jump performance.

Lower semicontinuity of the feasible set mapping of linear systems relative to their domains

This paper deals with stability properties of the feasible set of linear inequality systems having a finite number of variables and an arbitrary number of constraints. Several types of perturbations preserving consistency are considered, affecting respectively, all of the data, the left-hand side data, or the right-hand side coefficients.

Construction of Intelligent Virtual Worlds Using a Grammatical Framework

The potential of integrating multiagent systems and virtual environments has not been exploited to its whole extent. This paper proposes a model based on grammars, called Minerva, to construct complex virtual environments that integrate the features of agents. A virtual world is described as a set of dynamic and static elements. The static part is represented by a sequence of primitives and transformations and the dynamic elements by a series of agents. Agent activation and communication is achieved using events, created by the so-called event generators. The grammar defines a descriptive language with a simple syntax and a semantics, defined by functions. The semantics functions allow the scene to be displayed in a graphics device, and the description of the activities of the agents, including artificial intelligence algorithms and reactions to physical phenomena. To illustrate the use of Minerva, a practical example is presented: a simple robot simulator that considers the basic features of a typical robot. The result is a functional simple simulator. Minerva is a reusable, integral, and generic system, which can be easily scaled, adapted, and improved. The description of the virtual scene is independent from its representation and the elements that it interacts with.

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.

From community approaches to single-cell genomics: the discovery of ubiquitous hyperhalophilic Bacteroidetes generalists

The microbiota of multi-pond solar salterns around the world has been analyzed using a variety of culture-dependent and molecular techniques. However, studies addressing the dynamic nature of these systems are very scarce. Here we have characterized the temporal variation during 1 year of the microbiota of five ponds with increasing salinity (from 18% to >40%), by means of CARD-FISH and DGGE. Microbial community structure was statistically correlated with several environmental parameters, including ionic composition and meteorological factors, indicating that the microbial community was dynamic as specific phylotypes appeared only at certain times of the year. In addition to total salinity, microbial composition was strongly influenced by temperature and specific ionic composition. Remarkably, DGGE analyses unveiled the presence of most phylotypes previously detected in hypersaline systems using metagenomics and other molecular techniques, such as the very abundant Haloquadratum and Salinibacter representatives or the recently described low GC Actinobacteria and Nanohaloarchaeota. In addition, an uncultured group of Bacteroidetes was present along the whole range of salinity. Database searches indicated a previously unrecognized widespread distribution of this phylotype. Single-cell genome analysis of five members of this group suggested a set of metabolic characteristics that could provide competitive advantages in hypersaline environments, such as polymer degradation capabilities, the presence of retinal-binding light-activated proton pumps and arsenate reduction potential. In addition, the fairly high metagenomic fragment recruitment obtained for these single cells in both the intermediate and hypersaline ponds further confirm the DGGE data and point to the generalist lifestyle of this new Bacteroidetes group.

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.