Organismal duplication, inclusive fitness theory, and altruism: understanding the evolution of endosperm and the angiosperm reproductive syndrome.

For almost a century, events relating to the evolutionary origin of endosperm, a unique embryo-nourishing tissue that is essential to the reproductive process in flowering plants, have remained a mystery. Integration of recent advances in phylogenetic reconstruction, comparative reproductive biology, and genetic theory can be used to elucidate the evolutionary events and forces associated with the establishment of endosperm. Endosperm is shown to be derived from one of two embryos formed during a rudimentary process of "double fertilization" that evolved in the ancestors of angiosperms. Acquisition of embryo-nourishing behavior (with accompanying loss of individual fitness) by this supernumerary fertilization product was dependent upon compensatory gains in the inclusive fitness of related embryos. The result of the loss of individual fitness by one of the two original products of double fertilization was the establishment of endosperm, a highly modified embryo/organism that reproduces cryptically through behavior that enhances the fitness of its associated embryo within a seed. Finally, although triploid endosperm remains a synapomorphy of angiosperms, inclusive fitness analysis demonstrates that the embryo-nourishing properties of endosperm initially evolved in a diploid condition.

Rapid Scan Electron Paramagnetic Resonance (EPR) and Digital EPR Development

Rapid scan electron paramagnetic resonance (EPR) was developed in the Eaton laboratory at the University of Denver. Applications of rapid scan to wider spectra, such as for immobilized nitroxides, spin-labeled proteins, irradiated tooth and fingernail samples were demonstrated in this dissertation. The scan width has been increased from 55 G to 160 G. The signal to noise (S/N) improvement for slowly tumbling spin-labeled protein samples that is provided by rapid scan EPR will be highly advantageous for biophysical studies. With substantial improvement in S/N by rapid scan, the dose estimation for irradiated tooth enamels became more reliable than the traditional continuous wave (CW) EPR. An alternate approach of rapid scan, called field-stepped direct detection EPR, was developed to reconstruct wider EPR signals. A Mn2+ containing crystal was measured by field-stepped direct detection EPR, which had a spectrum more than 6000 G wide. Since the field-stepped direct detection extends the advantages of rapid scan to much wider scan ranges, this methodology has a great potential to replace the traditional CW EPR. With recent advances in digital electronics, a digital rapid scan spectrometer was built based on an arbitrary waveform generator (AWG), which can excite spins and detect EPR signals with a fully digital system. A near-baseband detection method was used to acquire the in-phase and quadrature signals in one physical channel. The signal was analyzed digitally to generate ideally orthogonal quadrature signals. A multiharmonic algorithm was developed that employed harmonics of the modulation frequencies acquired in the spectrometer transient mode. It was applied for signals with complicated lineshapes, and can simplify the selection of modulation amplitude. A digital saturation recovery system based on an AWG was built at X-band (9.6 GHz). To demonstrate performance of the system, the spin-lattice relaxation time of a fused quartz rod was measured at room temperature with fully digital excitation and detection.

Hybrid system for plagiarism detection

The Internet boom in recent years has increased the interest in the field of plagiarism detection. A lot of documents are published on the Net everyday and anyone can access and plagiarize them. Of course, checking all cases of plagiarism manually is an unfeasible task. Therefore, it is necessary to create new systems that are able to automatically detect cases of plagiarism produced. In this paper, we introduce a new hybrid system for plagiarism detection which combines the advantages of the two main plagiarism detection techniques. This system consists of two analysis phases: the first phase uses an intrinsic detection technique which dismisses much of the text, and the second phase employs an external detection technique to identify the plagiarized text sections. With this combination we achieve a detection system which obtains accurate results and is also faster thanks to the prefiltering of the text.

Evaluating the robustness of EmotiBlog for sentiment analysis and opinion mining

Preliminary research demonstrated the EmotiBlog annotated corpus relevance as a Machine Learning resource to detect subjective data. In this paper we compare EmotiBlog with the JRC Quotes corpus in order to check the robustness of its annotation. We concentrate on its coarse-grained labels and carry out a deep Machine Learning experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC Quotes corpus demonstrating the EmotiBlog validity as a resource for the SA task.

A comparative study of open domain and opinion question answering systems for factual and opinionated queries

The development of the Web 2.0 led to the birth of new textual genres such as blogs, reviews or forum entries. The increasing number of such texts and the highly diverse topics they discuss make blogs a rich source for analysis. This paper presents a comparative study on open domain and opinion QA systems. A collection of opinion and mixed fact-opinion questions in English is defined and two Question Answering systems are employed to retrieve the answers to these queries. The first one is generic, while the second is specific for emotions. We comparatively evaluate and analyze the systems’ results, concluding that opinion Question Answering requires the use of specific resources and methods.

Event ordering through temporal expression resolution

In this paper a multilingual method for event ordering based on temporal expression resolution is presented. This method has been implemented through the TERSEO system which consists of three main units: temporal expression recognizing, resolution of the coreference introduced by these expressions, and event ordering. By means of this system, chronological information related to events can be extracted from documental databases. This information is automatically added to the documental database in order to allow its use by question answering systems in those cases referring to temporality. The system has been evaluated obtaining results of 91 % precision and 71 % recall. For this, a blind evaluation process has been developed guaranteing a reliable annotation process that was measured through the kappa factor.

Architecture of a multi-modal dialogue system oriented to multilingual question-answering

In this paper, a proposal of a multi-modal dialogue system oriented to multilingual question-answering is presented. This system includes the following ways of access: voice, text, avatar, gestures and signs language. The proposal is oriented to the question-answering task as a user interaction mechanism. The proposal here presented is in the first stages of its development phase and the architecture is presented for the first time on the base of the experiences in question-answering and dialogues previously developed. The main objective of this research work is the development of a solid platform that will permit the modular integration of the proposed architecture.

An hybrid parallel algorithm for solving tridiagonal linear systems versus the Wang’s method in a Cray T3D BSP computer

In this paper we describe an hybrid algorithm for an even number of processors based on an algorithm for two processors and the Overlapping Partition Method for tridiagonal systems. Moreover, we compare this hybrid method with the Partition Wang’s method in a BSP computer. Finally, we compare the theoretical computation cost of both methods for a Cray T3D computer, using the cost model that BSP model provides.

A neural network algorithm to simplify 2D meshes

In this paper we propose a neural network model to simplify and 2D meshes. This model is based on the Growing Neural Gas model and is able to simplify any mesh with different topologies and sizes. A triangulation process is included with the objective to reconstruct the mesh. This model is applied to some problems related to urban networks.

Efectos y respuestas de la costra biológica del suelo en ecosistemas áridos: avances recientes a nivel de especie

La costra biológica del suelo (CBS) es un componente complejo del ecosistema que engloba diferentes organismos (líquenes, musgos, hepáticas, cianobacterias, hongos, algas) presentes en las primeras capas de suelo. La CBS se encuentra en una amplia variedad de ecosistemas, aunque generalmente es más abundante en ecosistemas donde la cobertura de plantas vasculares es escasa, como los ecosistemas áridos. En estos ecosistemas, la CBS contribuye considerablemente a su biodiversidad y funcionamiento. Debido a la gran dificultad para la identificación de especies de estas comunidades, la mayoría de la investigación sobre la CBS se ha desarrollado a escala de comunidad y grupo morfológico. A este nivel, se ha podido observar el gran potencial de estas comunidades de contribuir a la estructura y dinámica del ecosistema: interaccionan con las primeras capas del suelo y con otros organismos, participan en la fijación de carbono y nitrógeno, así como en procesos hidrológicos y en el ciclo de nutrientes. Sin embargo, avances recientes en el conocimiento de la CBS arrojan interesantes y marcadas diferencias en la ecología y el papel funcional de las distintas especies que la componen, con las consecuentes implicaciones en la gestión y conservación de estas comunidades y de los ecosistemas que habitan. En particular, se han observado respuestas específicas en términos de presencia, abundancia y frecuencia ante diversos factores ambientales (variables climáticas, tipo de sustrato, presencia de plantas vasculares y perturbación por pastoreo – recuperación natural), así como un efecto a nivel de especie sobre las propiedades del suelo.

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

Selective SWIFT-R. A Flexible Software-Based Technique for Soft Error Mitigation in Low-Cost Embedded Systems

Commercial off-the-shelf microprocessors are the core of low-cost embedded systems due to their programmability and cost-effectiveness. Recent advances in electronic technologies have allowed remarkable improvements in their performance. However, they have also made microprocessors more susceptible to transient faults induced by radiation. These non-destructive events (soft errors), may cause a microprocessor to produce a wrong computation result or lose control of a system with catastrophic consequences. Therefore, soft error mitigation has become a compulsory requirement for an increasing number of applications, which operate from the space to the ground level. In this context, this paper uses the concept of selective hardening, which is aimed to design reduced-overhead and flexible mitigation techniques. Following this concept, a novel flexible version of the software-based fault recovery technique known as SWIFT-R is proposed. Our approach makes possible to select different registers subsets from the microprocessor register file to be protected on software. Thus, design space is enriched with a wide spectrum of new partially protected versions, which offer more flexibility to designers. This permits to find the best trade-offs between performance, code size, and fault coverage. Three case studies have been developed to show the applicability and flexibility of the proposal.

Population synthesis of isolated neutron stars with magneto-rotational evolution

We revisit the population synthesis of isolated radio-pulsars incorporating recent advances on the evolution of the magnetic field and the angle between the magnetic and rotational axes from new simulations of the magneto-thermal evolution and magnetosphere models, respectively. An interesting novelty in our approach is that we do not assume the existence of a death line. We discuss regions in parameter space that are more consistent with the observational data. In particular, we find that any broad distribution of birth spin periods with P0 ≲ 0.5 s can fit the data, and that if the alignment angle is allowed to vary consistently with the torque model, realistic magnetospheric models are favoured compared to models with classical magneto-dipolar radiation losses. Assuming that the initial magnetic field is given by a lognormal distribution, our optimal model has mean strength 〈log B0[G]〉 ≈ 13.0–13.2 with width σ(log B0) = 0.6–0.7. However, there are strong correlations between parameters. This degeneracy in the parameter space can be broken by an independent estimate of the pulsar birth rate or by future studies correlating this information with the population in other observational bands (X-rays and γ-rays).

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.

Mesoporous materials for clean energy technologies

Alternative energy technologies are greatly hindered by significant limitations in materials science. From low activity to poor stability, and from mineral scarcity to high cost, the current materials are not able to cope with the significant challenges of clean energy technologies. However, recent advances in the preparation of nanomaterials, porous solids, and nanostructured solids are providing hope in the race for a better, cleaner energy production. The present contribution critically reviews the development and role of mesoporosity in a wide range of technologies, as this provides for critical improvements in accessibility, the dispersion of the active phase and a higher surface area. Relevant examples of the development of mesoporosity by a wide range of techniques are provided, including the preparation of hierarchical structures with pore systems in different scale ranges. Mesoporosity plays a significant role in catalysis, especially in the most challenging processes where bulky molecules, like those obtained from biomass or highly unreactive species, such as CO2 should be transformed into most valuable products. Furthermore, mesoporous materials also play a significant role as electrodes in fuel and solar cells and in thermoelectric devices, technologies which are benefiting from improved accessibility and a better dispersion of materials with controlled porosity.