A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Transitions in social complexity along elevational gradients reveal a combined impact of season length and development time on social evolution.

Eusociality is taxonomically rare, yet associated with great ecological success. Surprisingly, studies of environmental conditions favouring eusociality are often contradictory. Harsh conditions associated with increasing altitude and latitude seem to favour increased sociality in bumblebees and ants, but the reverse pattern is found in halictid bees and polistine wasps. Here, we compare the life histories and distributions of populations of 176 species of Hymenoptera from the Swiss Alps. We show that differences in altitudinal distributions and development times among social forms can explain these contrasting patterns: highly social taxa develop more quickly than intermediate social taxa, and are thus able to complete the reproductive cycle in shorter seasons at higher elevations. This dual impact of altitude and development time on sociality illustrates that ecological constraints can elicit dynamic shifts in behaviour, and helps explain the complex distribution of sociality across ecological gradients.

Destruction of invariant curves in the restricted circular planar three body problem using comparison of action

"Vegeu el resum a l'inici del document del fitxer adjunt."

The Brezis-Nirenberg type problem involving the square root of the Laplacian

We establish existence and non-existence results to the Brezis-Nirenberg type problem involving the square root of the Laplacian in a bounded domain with zero Dirichlet boundary condition.

A numerical algorithm for finding solutions of a generalized Nash equilibrium problem

A family of nonempty closed convex sets is built by using the data of the Generalized Nash equilibrium problem (GNEP). The sets are selected iteratively such that the intersection of the selected sets contains solutions of the GNEP. The algorithm introduced by Iusem-Sosa (2003) is adapted to obtain solutions of the GNEP. Finally some numerical experiments are given to illustrate the numerical behavior of the algorithm.

The Division problem with voluntary participation

The division problem consists of allocating a given amount of an homogeneous and perfectly divisible good among a group of agents with single-peaked preferences on the set of their potential shares. A rule proposes a vector of shares for each division problem. The literature has implicitly assumed that agents will find acceptable any share they are assigned to. In this paper we consider the division problem when agents' participation is voluntary. Each agent has an idiosyncratic interval of acceptable shares where his preferences are single-peaked. A rule has to propose to each agent either to not participate or an acceptable share because otherwise he would opt out and this would require to reassign some of the remaining agents' shares. We study a subclass of efficient and consistent rules and characterize extensions of the uniform rule that deal explicitly with agents' voluntary participation.

Thyroid hormone enhances transected axonal regeneration and muscle reinnervation following rat sciatic nerve injury.

Improvement of nerve regeneration and functional recovery following nerve injury is a challenging problem in clinical research. We have already shown that following rat sciatic nerve transection, the local administration of triiodothyronine (T3) significantly increased the number and the myelination of regenerated axons. Functional recovery is a sum of the number of regenerated axons and reinnervation of denervated peripheral targets. In the present study, we investigated whether the increased number of regenerated axons by T3-treatment is linked to improved reinnervation of hind limb muscles. After transection of rat sciatic nerves, silicone or biodegradable nerve guides were implanted and filled with either T3 or phosphate buffer solution (PBS). Neuromuscular junctions (NMJs) were analyzed on gastrocnemius and plantar muscle sections stained with rhodamine alpha-bungarotoxin and neurofilament antibody. Four weeks after surgery, most end-plates (EPs) of operated limbs were still denervated and no effect of T3 on muscle reinnervation was detected at this stage of nerve repair. In contrast, after 14 weeks of nerve regeneration, T3 clearly enhanced the reinnervation of gastrocnemius and plantar EPs, demonstrated by significantly higher recovery of size and shape complexity of reinnervated EPs and also by increased acetylcholine receptor (AChRs) density on post synaptic membranes compared to PBS-treated EPs. The stimulating effect of T3 on EP reinnervation is confirmed by a higher index of compound muscle action potentials recorded in gastrocnemius muscles. In conclusion, our results provide for the first time strong evidence that T3 enhances the restoration of NMJ structure and improves synaptic transmission.

Analysis of a finite volume element method for the Stokes problem

In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.

Discontinuous Galerkin methods for the Multi-dimensional Vlasov-Poisson problem

We introduce and analyze two new semi-discrete numerical methods for the multi-dimensional Vlasov-Poisson system. The schemes are constructed by combing a discontinuous Galerkin approximation to the Vlasov equation together with a mixed finite element method for the Poisson problem. We show optimal error estimates in the case of smooth compactly supported initial data. We propose a scheme that preserves the total energy of the system.

GWAS of human bitter taste perception identifies new loci and reveals additional complexity of bitter taste genetics.

Human perception of bitterness displays pronounced interindividual variation. This phenotypic variation is mirrored by equally pronounced genetic variation in the family of bitter taste receptor genes. To better understand the effects of common genetic variations on human bitter taste perception, we conducted a genome-wide association study on a discovery panel of 504 subjects and a validation panel of 104 subjects from the general population of São Paulo in Brazil. Correction for general taste-sensitivity allowed us to identify a SNP in the cluster of bitter taste receptors on chr12 (10.88- 11.24 Mb, build 36.1) significantly associated (best SNP: rs2708377, P = 5.31 × 10(-13), r(2) = 8.9%, β = -0.12, s.e. = 0.016) with the perceived bitterness of caffeine. This association overlaps with-but is statistically distinct from-the previously identified SNP rs10772420 influencing the perception of quinine bitterness that falls in the same bitter taste cluster. We replicated this association to quinine perception (P = 4.97 × 10(-37), r(2) = 23.2%, β = 0.25, s.e. = 0.020) and additionally found the effect of this genetic locus to be concentration specific with a strong impact on the perception of low, but no impact on the perception of high concentrations of quinine. Our study, thus, furthers our understanding of the complex genetic architecture of bitter taste perception.

Analyzing complexity in foreign language monologic oral production in a CLIL context

The study tested three analytic tools applied in SLA research (T-unit, AS-unit and Idea-unit) against FL learner monologic oral data. The objective was to analyse their effectiveness for the assessment of complexity of learners' academic production in English. The data were learners' individual productions gathered during the implementation of a CLIL teaching sequence on Natural Sciences in a Catalan state secondary school. The analysis showed that only AS-unit was easily applicable and highly effective in segmenting the data and taking complexity measures

Configuración de la entrada/salida paralela para el cómputo de altas prestaciones

La E/S Paralela es un área de investigación que tiene una creciente importancia en el cómputo de Altas Prestaciones. Si bien durante años ha sido el cuello de botella de los computadores paralelos en la actualidad, debido al gran aumento del poder de cómputo, el problema de la E/S se ha incrementado y la comunidad del Cómputo de Altas Prestaciones considera que se debe trabajar en mejorar el sistema de E/S de los computadores paralelos, para lograr cubrir las exigencias de las aplicaciones científicas que usan HPC. La Configuración de la Entrada/Salida (E/S) Paralela tiene una gran influencia en las prestaciones y disponibilidad, por ello es importante “Analizar configuraciones de E/S paralela para identificar los factores claves que influyen en las prestaciones y disponibilidad de la E/S de Aplicaciones Científicas que se ejecutan en un clúster”. Para realizar el análisis de las configuraciones de E/S se propone una metodología que permite identificar los factores de E/S y evaluar su influencia para diferentes configuraciones de E/S formada por tres fases: Caracterización, Configuración y Evaluación. La metodología permite analizar el computador paralelo a nivel de Aplicación Científica, librerías de E/S y de arquitectura de E/S, pero desde el punto de vista de la E/S. Los experimentos realizados para diferentes configuraciones de E/S y los resultados obtenidos indican la complejidad del análisis de los factores de E/S y los diferentes grados de influencia en las prestaciones del sistema de E/S. Finalmente se explican los trabajos futuros, el diseño de un modelo que de soporte al proceso de Configuración del sistema de E/S paralela para aplicaciones científicas. Por otro lado, para identificar y evaluar los factores de E/S asociados con la disponibilidad a nivel de datos, se pretende utilizar la Arquitectura Tolerante a Fallos RADIC.

Repeated Interaction and the Revelation of the Monitor's Type: A Principal-Monitor-Agent Problem

This paper studies a dynamic principal-monitor-agent relation where a strategic principal delegates the task of monitoring the effort of a strategic agent to a third party. The latter we call the monitor, whose type is initially unknown. Through repeated interaction the agent might learn his type. We show that this process damages the principal's payoffs. Compensation is assumed exogenous, limiting to a great extent the provision of incentives. We go around this difficulty by introducing costly replacement strategies, i.e. the principal replaces the monitor, thus disrupting the agent's learning. We found that even when replacement costs are null, if the revealed monitor is strictly preferred by both parties, there is a loss in efficiency due to the impossibility of bene…tting from it. Nonetheless, these strategies can partially recover the principal's losses. Additionally, we establish upper and lower bounds on the payoffs that the principal and the agent can achieve. Finally we characterize the equilibrium strategies under public and private monitoring (with communication) for different cost and impatience levels.

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.