Saliency computation via whitened frequency band selection

Many saliency computational models have been proposed to simulate bottom-up visual attention mechanism of human visual system. However, most of them only deal with certain kinds of images or aim at specific applications. In fact, human beings have the ability to correctly select attentive focuses of objects with arbitrary sizes within any scenes. This paper proposes a new bottom-up computational model from the perspective of frequency domain based on the biological discovery of non-Classical Receptive Field (nCRF) in the retina. A saliency map can be obtained according to the idea of Extended Classical Receptive Field. The model is composed of three major steps: firstly decompose the input image into several feature maps representing different frequency bands that cover the whole frequency domain by utilizing Gabor wavelet. Secondly, whiten the feature maps to highlight the embedded saliency information. Thirdly, select some optimal maps, simulating the response of receptive field especially nCRF, to generate the saliency map. Experimental results show that the proposed algorithm is able to work with stable effect and outstanding performance in a variety of situations as human beings do and is adaptive to both psychological patterns and natural images. Beyond that, biological plausibility of nCRF and Gabor wavelet transform make this approach reliable.     

Navigating abstract virtual environment: an eeg study

Perceptions of different environments are different for different people. An abstract designed environment, with a degree of freedom from any visual reference in the physical world requests a completely different perception than a fully or semi-designed environment that has some correlation with the physical world. Maximal evidence on the manner in which the human brain is involved/operates in dealing with such novel perception comes from neuropsychology. Harnessing the tools and techniques involved in the domain of neuropsychology, the paper presents nee evidence on the role of pre-central gyrus in the perception of abstract spatial environments. In order to do so, the research team developed three different categories of designed environment with different characteristics: (1) Abstract environment, (2) Semi-designed environment, (3) Fully designed environment, as experimental sample environments. Perception of Fully-designed and semi-designed environments is almost the same, [maybe] since the brain can find a correlation between designed environments and already experienced physical world. In addition to this, the response to questionnaires accompanied with a list of buzzwords that have been provided after the experiments, also describe the characteristics of the chosen sample environments. Additionally, these results confirm the suitability of continuous electroencephalography (EEG) for studying Perception from the perspective of architectural environments.     

A novel algorithm with differential evolution and coral reef optimization for extreme learning machine training

Extreme learning machine (ELM) is a novel and fast learning method to train single layer feed-forward networks. However due to the demand for larger number of hidden neurons, the prediction speed of ELM is not fast enough. An evolutionary based ELM with differential evolution (DE) has been proposed to reduce the prediction time of original ELM. But it may still get stuck at local optima. In this paper, a novel algorithm hybridizing DE and metaheuristic coral reef optimization (CRO), which is called differential evolution coral reef optimization (DECRO), is proposed to balance the explorative power and exploitive power to reach better performance. The thought and the implement of DECRO algorithm are discussed in this article with detail. DE, CRO and DECRO are applied to ELM training respectively. Experimental results show that DECRO-ELM can reduce the prediction time of original ELM, and obtain better performance for training ELM than both DE and CRO.     

Seasonal and altitude effects on the structure of arthropod communities associated with <Emphasis Type="Italic">Tillandsia violacea</Emphasis> Baker (Bromeliaceae) in a temperate forest of Mexico

The canopy of forests has been considered “the last biotic frontier,” and study of its elements is very important in explaining the global functionality in ecosystems. Epiphytic plants and arthropods are essential elements in canopy habitats, and their relationships have been studied in order to understand the high diversity in tropical forests. Nevertheless, there are few studies on this development in temperate forests. The arthropod community was studied during the rainy and dry seasons at two altitudes, and a total of 240 T. violacea plants of three sizes were collected from Abies religiosa and Quercus spp. host trees. A total of 163,043 arthropods were collected and about 200 morphospecies identified. The highest abundance was obtained during the dry season, while high diversity was found during the rainy season. There was a significant effect of plant size, host trees and collecting season on abundance and diversity, and there were seasonal variations in community composition. The community hosted on A. religiosa epiphytes showed higher abundance and density than that of Quercus.     

A semantic explanation for the External Argument Generalization

-Er nominals usually obey the External Argument Generalization: the argument of the nominal receives the thematic role that the verb assigns to its external argument. I argue that this syntactic generalization, as well as the exceptions to it, can be explained by semantics.Specifically, -er nominals usually express properties that are inherent in the subject; I argue that they therefore belong to the class of expressions that express such properties—dynamic modals. Crucially, dynamic modals are subject oriented; hence, the proposal that -er nominals are dynamic modals naturally provides an account of the External Argument Generalization.     

<Superscript>1</Superscript>H, <Superscript>13</Superscript>C and <Superscript>15</Superscript>N resonance assignments and secondary structure analysis of translation initiation factor 1 from <Emphasis Type="Italic">Pseudomonas aeruginosa</Emphasis>

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen and a primary cause of infection in humans. P. aeruginosa can acquire resistance against multiple groups of antimicrobial agents, including β-lactams, aminoglycosides and fluoroquinolones, and multidrug resistance is increasing in this organism which makes treatment of the infections difficult and expensive. This has led to the unmet need for discovery of new compounds distinctly different from present antimicrobials. Protein synthesis is an essential metabolic process and a validated target for the development of new antibiotics. Translation initiation factor 1 from P. aeruginosa (Pa-IF1) is the smallest of the three initiation factors that acts to establish the 30S initiation complex to initiate translation during protein biosynthesis, and its structure is unknown. Here we report the ¹H, ¹³C and ¹⁵N chemical shift assignments of Pa-IF1 as the basis for NMR structure determination and interaction studies. Secondary structure analyses deduced from the NMR chemical shift data have identified five β-strands with an unusually extended β-strand at the C-terminal end of the protein and one short α-helix arranged in the sequential order β1–β2–β3–α1–β4–β5. This is further supported by ¹⁵N–{¹H} hetero NOEs. These secondary structure elements suggest the Pa-IF1 adopts the typical β-barrel structure and is composed of an oligomer-binding motif.     

The dynamics of coupled populations subject to control

The dynamics of coupled populations have mostly been studied in the context of metapopulation viability with application to, for example, species at risk. However, when considering pests and pathogens, eradication, not persistence, is often the end goal. Humans may intervene to control nuisance populations, resulting in reciprocal interactions between the human and natural systems that can lead to unexpected dynamics. The incidence of these human-natural couplings has been increasing, hastening the need to better understand the emergent properties of such systems in order to predict and manage outbreaks of pests and pathogens. For example, the success of the growing aquaculture industry depends on our ability to manage pathogens and maintain a healthy environment for farmed and wild fish. We developed a model for the dynamics of connected populations subject to control, motivated by sea louse parasites that can disperse among salmon farms. The model includes exponential population growth with a forced decline when populations reach a threshold, representing control interventions. Coupling two populations with equal growth rates resulted in phase locking or synchrony in their dynamics. Populations with different growth rates had different periods of oscillation, leading to quasiperiodic dynamics when coupled. Adding small amounts of stochasticity destabilized quasiperiodic cycles to chaos, while stochasticity was damped for periodic or stable dynamics. Our analysis suggests that strict treatment thresholds, although well intended, can complicate parasite dynamics and hinder control efforts. Synchronizing populations via coordinated management among farms leads to more effective control that is required less frequently. Our model is simple and generally applicable to other systems where dispersal affects the management of pests and pathogens.     

Coexistence and emergent neutrality generate synchrony among competitors in fluctuating environments

Many competitive communities exhibit a puzzling amount of species diversity. In this study, we model a community of symmetric competitors in a fluctuating environment. We use biologically realistic temperature-dependent growth curves with a widely hypothesized trade-off between maximum growth and nice breadth to control the shapes of the curves of different species. We perform three analyses of the community dynamics to investigate the role of environmental fluctuations in community composition and species diversity. We initiate communities with equal abundances of all species and randomize the temperature fluctuations so that there is no correlation between species responses, only noise. We initiate single populations and allow other species to randomly invade the community. We also knock out extant species one by one from an established community and allow them to reinvade after the remaining species have adjusted. We find that competitors with sufficiently different temperature niches coexist via temporal niche differentiation. We also find long-term persistence of species that are very similar to a dominant competitor. This creates communities with species clumped along a temperature niche axis, with stable coexistence between groups and near neutrality within groups. The near neutrality results in interspecific synchrony within the groups, providing an explanation for the maintenance of high diversity in competitive communities where synchrony is commonly observed.     

Predation risk tradeoffs in prey: effects on energy and behaviour

The complexity of behavioural interactions in predator-prey systems has recently begun to capture trait-effects, or non-lethal effects, of predators on prey via induced behavioural changes. Non-lethal predation effects play crucial roles in shaping population and community dynamics, particularly by inducing changes to foraging, movement and reproductive behaviours of prey. Prey exhibit trade-offs in behaviours while minimizing predation risk. We use a novel evolutionary ecosystem simulation EcoSim to study such behavioural interactions and their effects on prey populations, thereby addressing the need for integrating multiple layers of complexity in behavioural ecology. EcoSim allows complex intra- and inter-specific interactions between behaviourally and genetically unique individuals called predators and prey, as well as complex predator-prey dynamics and coevolution in a tri-trophic and spatially heterogeneous world. We investigated the effects of predation risk on prey energy budgets and fitness. Results revealed that energy budgets, life history traits, allocation of energy to movements and fitness-related actions differed greatly between prey subjected to low-predation risk and high-predation risk. High-predation risk suppressed prey foraging activity, increased total movement and decreased reproduction relative to low-risk. We show that predation risk alone induces behavioural changes in prey which drastically affect population and community dynamics, and when interpreted within the evolutionary context of our simulation indicate that genetic changes accompanying coevolution have long-term effects on prey adaptability to the absence of predators.