Percolation in soils at Different Bulk Densities: Porosity, Connectivity and Grey Threshold.

To improve percolation modelling on soils the geometrical properties of the pore space must be understood; this includes porosity, particle and pore size distribution and connectivity of the pores. A study was conducted with a soil at different bulk densities based on 3D grey images acquired by X-ray computed tomography. The objective was to analyze the effect in percolation of aspects of pore network geometry and discuss the influence of the grey threshold applied to the images. A model based on random walk algorithms was applied to the images, combining five bulk densities with up to six threshold values per density. This allowed for a dynamical perspective of soil structure in relation to water transport through the inclusion of percolation speed in the analyses. To evaluate separately connectivity and isolate the effect of the grey threshold, a critical value of 35% of porosity was selected for every density. This value was the smallest at which total-percolation walks appeared for the all images of the same porosity and may represent a situation of percolation comparable among bulks densities. This criterion avoided an arbitrary decision in grey thresholds. Besides, a random matrix simulation at 35% of porosity with real images was used to test the existence of pore connectivity as a consequence of a non-random soil structure.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Ionoluminescence as sensor of structural disorder in crystalline SiO2: determination of amorphization threshold by swift heavy ions

Ionoluminescence (IL) has been used in this work as a sensitive tool to probe the microscopic electronic processes and structural changes produced on quartz by the irradiation with swift heavy ions. The IL yields have been measured as a function of irradiation fluence and electronic stopping power. The results are consistent with the assignment of the 2.7 eV (460 nm) band to the recombination of self-trapped excitons at the damaged regions in the irradiated material. Moreover, it was possible to determine the threshold for amorphization by a single ion impact, as 1:7 keV/nm, which agrees well with the results of previous studies.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Responses to increasing exercise upon reaching the anaerobic threshold, and their control by the central nervous system

Sistema nervioso y ejercicio

Modeling sub-threshold slope and DIBL mismatch of sub-22nm FinFet

A great challenge for future information technologies is building reliable systems on top of unreliable components. Parameters of modern and future technology devices are affected by severe levels of process variability and devices will degrade and even fail during the normal lifeDme of the chip due to aging mechanisms. These extreme levels of variability are caused by the high device miniaturizaDon and the random placement of individual atoms. Variability is considered a "red brick" by the InternaDonal Technology Roadmap for Semiconductors. The session is devoted to this topic presenDng research experiences from the Spanish Network on Variability called VARIABLES. In this session a talk entlited "Modeling sub-threshold slope and DIBL mismatch of sub-22nm FinFet" was presented.

Variable threshold algorithm for division of labor analyzed as a dynamical system

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Written on the threshold

One of the most productive discoveries of art and architectural criticism is the comparative reading between different situations. It is an approach that does away with all conventions and destroys any attempt to codifing the future. It also reveals the futility of established styles or movements. In the early 20th century, the Russian Formalists spoke of the dissimilarity of the similar in literature and more than a few studies on the visual arts have used the comparative method, from Heinrich Wolfflin to Robert Venturi. But something more has to be added, personal biography. The involvement of the individual, their name and their life, in the history of art bursts in with all the force of what is real, with no need for credibility, because it merely is what it is. The histories of architecture and art tell things in a believable, perfectly connected manner, without the fits and starts of personal biography - when this appears we find ourselves in a different sort of situation.

Stability threshold approach for complex dynamical systems

Acknowledgments This paper was developed within the scope of the IRTG 1740/TRP 2011/50151-0, funded by the DFG/FAPESP, and supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS). The first author thanks Dr Roman Ovsyannikov for valuable discussions regarding estimation of the mistake probability.

Is blindsight like normal, near-threshold vision?

Blindsight is the rare and paradoxical ability of some human subjects with occipital lobe brain damage to discriminate unseen stimuli in their clinically blind field defects when forced-choice procedures are used, implying that lesions of striate cortex produce a sharp dissociation between visual performance and visual awareness. Skeptics have argued that this is no different from the behavior of normal subjects at the lower limits of conscious vision, at which such dissociations could arise trivially by using different response criteria during clinical and forced-choice tests. We tested this claim explicitly by measuring the sensitivity of a hemianopic patient independently of his response criterion in yes-no and forced-choice detection tasks with the same stimulus and found that, unlike normal controls, his sensitivity was significantly higher during the forced-choice task. Thus, the dissociation by which blindsight is defined is not simply due to a difference in the patients’ response bias between the two paradigms. This result implies that blindsight is unlike normal, near-threshold vision and that information about the stimulus is processed in blindsighted patients in an unusual way.

Electric Signaling and Pin2 Gene Expression on Different Abiotic Stimuli Depend on a Distinct Threshold Level of Endogenous Abscisic Acid in Several Abscisic Acid-Deficient Tomato Mutants1

Experiments were performed on three abscisic acid (ABA)-deficient tomato (Lycopersicon esculentum Mill.) mutants, notabilis, flacca, and sitiens, to investigate the role of ABA and jasmonic acid (JA) in the generation of electrical signals and Pin2 (proteinase inhibitor II) gene expression. We selected these mutants because they contain different levels of endogenous ABA. ABA levels in the mutant sitiens were reduced to 8% of the wild type, in notabilis they were reduced to 47%, and in flacca they were reduced to 21%. In wild-type and notabilis tomato plants the induction of Pin2 gene expression could be elicited by heat treatment, current application, or mechanical wounding. In flacca and sitiens only heat stimulation induced Pin2 gene expression. JA levels in flacca and sitiens plants also accumulated strongly upon heat stimulation but not upon mechanical wounding or current application. Characteristic electrical signals evolved in the wild type and in the notabilis and flacca mutants consisting of a fast action potential and a slow variation potential. However, in sitiens only heat evoked electrical signals; mechanical wounding and current application did not change the membrane potential. In addition, exogenous application of ABA to wild-type tomato plants induced transient changes in membrane potentials, indicating the involvement of ABA in the generation of electrical signals. Our data strongly suggest the presence of a minimum threshold value of ABA within the plant that is essential for the early events in electrical signaling and mediation of Pin2 gene expression upon wounding. In contrast, heat-induced Pin2 gene expression and membrane potential changes were not dependent on the ABA level but, rather, on the accumulation of JA.

A low threshold level of expression of mutant-template telomerase RNA inhibits human tumor cell proliferation

The ribonucleoprotein telomerase synthesizes telomeric DNA by copying an intrinsic RNA template. In most cancer cells, telomerase is highly activated. Here we report a telomerase-based antitumor strategy: expression of mutant-template telomerase RNAs in human cancer cells. We expressed mutant-template human telomerase RNAs in prostate (LNCaP) and breast (MCF-7) cancer cell lines. Even a low threshold level of expression of telomerase RNA gene constructs containing various mutant templates, but not the control wild-type template, decreased cellular viability and increased apoptosis. This occurred despite the retention of normal levels of the endogenous wild-type telomerase RNA and endogenous wild-type telomerase activity and unaltered stable telomere lengths. In vivo tumor xenografts of a breast cancer cell line expressing a mutant-template telomerase RNA also had decreased growth rates. Therefore, mutant-template telomerase RNAs exert a strongly dominant-negative effect on cell proliferation and tumor growth. These results support the potential use of mutant-template telomerase RNA expression as an antineoplastic strategy.

Maternal plasma human immunodeficiency virus type 1 RNA level: a determinant and projected threshold for mother-to-child transmission.

To prevent mother-to-child human immunodeficiency virus type 1 (HIV-1) transmission, it is important to identify its determinants. Because HIV-1 RNA levels can be reduced by antiviral therapy, we examined the role of maternal plasma HIV-1 RNA level in mother-to-child transmission. We used quantitative competitive PCR to measure HIV-RNA in 30 infected pregnant women and then followed their infants prospectively; 27% of the women transmitted HIV-1 to their infants and maternal plasma HIV-1 RNA level correlated strikingly with transmission. Eight of the 10 women with the highest HIV-1 RNA levels at delivery (190,400-1,664,100 copies per ml of plasma) transmitted, while none of the 20 women with lower levels (500-155,800 copies per ml) did (P = 0.0002). Statistical analysis of the distribution of HIV-1 RNA loads in these 30 women projected a threshold for mother-to-child transmission in a larger population; the probability of a woman with a viral RNA level of < or = 100,000 copies per ml not transmitting is predicted to be 97%. Examination of serial HIV-1 RNA levels during pregnancy showed that viral load was stable in women who did not initiate or change antiviral therapy. These data identify maternal plasma HIV-1-RNA level as a major determinant of mother-to-child transmission and suggest that quantitation of HIV-1 RNA may predict the risk of transmission.

Commercial applications of speech interface technology: an industry at the threshold.

Speech interface technology, which includes automatic speech recognition, synthetic speech, and natural language processing, is beginning to have a significant impact on business and personal computer use. Today, powerful and inexpensive microprocessors and improved algorithms are driving commercial applications in computer command, consumer, data entry, speech-to-text, telephone, and voice verification. Robust speaker-independent recognition systems for command and navigation in personal computers are now available; telephone-based transaction and database inquiry systems using both speech synthesis and recognition are coming into use. Large-vocabulary speech interface systems for document creation and read-aloud proofing are expanding beyond niche markets. Today's applications represent a small preview of a rich future for speech interface technology that will eventually replace keyboards with microphones and loud-speakers to give easy accessibility to increasingly intelligent machines.

Relatedness threshold for the production of female sexuals in colonies of a polygynous ant, Myrmica tahoensis, as revealed by microsatellite DNA analysis.

The genetic relationships of colony members in the ant Myrmica tahoensis were determined on the basis of highly polymorphic microsatellite DNA loci. These analyses show that colonies fall into one of two classes. In roughly half of the sampled colonies, workers and female offspring appear to be full sisters. The remaining colonies contain offspring produced by two or more queens. Colonies that produce female sexuals are always composed of highly related females, while colonies that produce males often show low levels of nestmate relatedness. These results support theoretical predictions that workers should skew sex allocation in response to relatedness asymmetries found within colonies. The existence of a relatedness threshold below which female sexuals are not produced suggests a possible mechanism for worker perception of relatedness. Two results indicate that workers use genetic cues, not queen number, in making sex-allocation decisions. (i) The number of queens in a colony was not significantly correlated with either the level of relatedness asymmetry or the sex ratio. (ii) Sex-ratio shifts consistent with a genetically based mechanism of relatedness assessment were seen in an experiment involving transfers of larvae among unrelated nests. Thus workers appear to make sex-allocation decisions on the basis of larval cues and appear to be able to adjust sex ratios long after egg laying.