Homology in a context dependent predatory behavior in spiders (Araneae)

Stereotyped behaviors have been routinely used as characters for phylogeny inference, but the same cannot be said of the plastic aspects of performance, which routinely are taken as a result of ecological processes. In this paper we examine the evolution of one of these plastic behavioral phenotypes, thus fostering a bridge between ecological and evolutionary processes. Foraging behavior in spiders is context dependent in many aspects, since it varies with prey type and size, spider nutritional and developmental state, previous experience and, in webweavers, is dependent on the structure of the web. Reeling is a predatory tactic typical of cobweb weavers (Theridiidae), in which the spider moves the prey toward her by pulling the capture thread (gumfoot) to which it is adhered. Predatory reeling is dependent on the gumfoot for its expression, and has not been previously reported in orbweavers. In order to investigate the evolution of this web dependent behavior, we built artificial, pseudogumfoot lines in orbwebs and registered parameters of the predatory tactics in this modified web. Aspects of the predatory tactics of 240 individuals (12 species in 4 families) were measured, and the resulting data were optimized on the phylogeny of Orbiculariae. All species perform predatory reeling with the pseudogumfoot lines. Thus, predatory reeling is homologous for the whole Orbiculariae group. In nature, holes made by insects in ecribellate orbs produce pseudogumfoot lines (similar to out experimentally modified webs), and thus reeling occurred naturally in ecribellates. Nevertheless, outside lab conditions, predatory reeling does not occur among cribellate orbweavers, so that this behavior could not have been selected for in the cribellate ancester of orbweavers. Cribellate spiders are flexible enough as to present novel and adaptive predatory responses (reeling) even when exposed for the first time to conditions outside their usual environment. Thus, the evolution of reeling suggests and alternative mechanism for the production of evolutionary novelties; that is, the exploration of unusual ecological conditions and of the regular effects these abnormal conditions have on phenotype expression.

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

Physical model of PD behavior and relevant damage growth from micro-cavities in polyethylene-based material under AC voltage

In the framework of developing defect-based life models, in which breakdown is explicitly associated with partial discharge (PD)-induced damage growth from a defect, ageing tests and PD measurements were carried out in the lab on polyethylene (PE) layered specimens containing artificial cavities. PD activity was monitored continuously during aging. A quasi-deterministic series of stages can be observed in the behavior of the main PD parameters (i.e. discharge repetition rate and amplitude). Phase-resolved PD patterns at various ageing stages were reproduced by numerical simulation which is based on a physical discharge model devoid of adaptive parameters. The evolution of the simulation parameters provides insight into the physical-chemical changes taking place at the dielectric/cavity interface during the aging process. PD activity shows similar time behavior under constant cavity gas volume and constant cavity gas pressure conditions, suggesting that the variation of PD parameters may not be attributed to the variation of the gas pressure. Brownish PD byproducts, consisting of oxygen containing moieties, and degradation pits were found at the dielectric/cavity interface. It is speculated that the change of PD activity is related to the composition of the cavity gas, as well as to the properties of dielectric/cavity interface.

International Agricultural Trade under Regulatory Asymmetry: An Economic Analysis of SME Export Behavior

Over the last three decades, international agricultural trade has grown significantly. Technological advances in transportation logistics and storage have created opportunities to ship anything almost anywhere. Bilateral and multilateral trade agreements have also opened new pathways to an increasingly global market place. Yet, international agricultural trade is often constrained by differences in regulatory regimes. The impact of “regulatory asymmetry” is particularly acute for small and medium sized enterprises (SMEs) that lack resources and expertise to successfully operate in markets that have substantially different regulatory structures. As governments seek to encourage the development of SMEs, policy makers often confront the critical question of what ultimately motivates SME export behavior. Specifically, there is considerable interest in understanding how SMEs confront the challenges of regulatory asymmetry. Neoclassical models of the firm generally emphasize expected profit maximization under uncertainty, however these approaches do not adequately explain the entrepreneurial decision under regulatory asymmetry. Behavioral theories of the firm offer a far richer understanding of decision making by taking into account aspirations and adaptive performance in risky environments. This paper develops an analytical framework for decision making of a single agent. Considering risk, uncertainty and opportunity cost, the analysis focuses on the export behavior response of an SME in a situation of regulatory asymmetry. Drawing on the experience of fruit processor in Muzaffarpur, India, who must consider different regulatory environments when shipping fruit treated with sulfur dioxide, the study dissects the firm-level decision using @Risk, a Monte Carlo computational tool.

Maternal modulation of natal dispersal in a passerine bird: An adaptive strategy to cope with parasitism?

The decision of how far to disperse from the natal territory has profound and long-lasting consequences for young animals, yet the optimal dispersal behavior often depends on environmental factors that are difficult or impossible to assess by inexperienced juveniles. Natural selection thus favors mechanisms that allow the adaptive and flexible adjustment of the offspring's dispersal behavior by their parents via either paternal or maternal effects. Here we show that different dispersal strategies maximize the reproductive success of young great tits (Parus major) originating from a parasite-infested or a parasite-free nest and demonstrate that differential transfer of maternal yolk androgens in response to parasitism can result in a modification of the offspring's dispersal behavior that appears adaptive. It demonstrates that prenatal maternal effects are an important yet so far neglected determinant of natal dispersal and highlights the potential importance of maternal effects in mediating coevolutionary processes in host-parasite systems.

Swimming and diving behavior in apes (Pan troglodytes and Pongo pygmaeus): first documented report

Extant hominoids, including humans, are well known for their inability to swim instinctively. We report swimming and diving in two captive apes using visual observation and video recording. One common chimpanzee and one orangutan swam repeatedly at the water surface over a distance of 2-6 m; both individuals submerged repeatedly. We show that apes are able to overcome their negative buoyancy by deliberate swimming, using movements which deviate from the doggy-paddle pattern observed in other primates. We suggest that apes' poor swimming ability is due to behavioral, anatomical, and neuromotor changes related to an adaptation to arboreal life in their early phylogeny. This strong adaptive focus on arboreal life led to decreased opportunities to interact with water bodies and consequently to a reduction of selective pressure to maintain innate swimming behavior. As the doggy paddle is associated with quadrupedal walking, a deviation from terrestrial locomotion might have interfered with the fixed rhythmic action patterns responsible for innate swimming.

CAOR: Context-aware Adaptive Opportunistic Routing in Mobile Ad-hoc Networks

Opportunistic routing (OR) employs a list of candidates to improve wireless transmission reliability. However, conventional list-based OR restricts the freedom of opportunism, since only the listed nodes are allowed to compete for packet forwarding. Additionally, the list is generated statically based on a single network metric prior to data transmission, which is not appropriate for mobile ad-hoc networks (MANETs). In this paper, we propose a novel OR protocol - Context-aware Adaptive Opportunistic Routing (CAOR) for MANETs. CAOR abandons the idea of candidate list and it allows all qualified nodes to participate in packet transmission. CAOR forwards packets by simultaneously exploiting multiple cross-layer context information, such as link quality, geographic progress, energy, and mobility.With the help of the Analytic Hierarchy Process theory, CAOR adjusts the weights of context information based on their instantaneous values to adapt the protocol behavior at run-time. Moreover, CAOR uses an active suppression mechanism to reduce packet duplication. Simulation results show that CAOR can provide efficient routing in highly mobile environments. The adaptivity feature of CAOR is also validated.

Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

Cooperative off-policy prediction of markov decision processes in adaptive networks

We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in large state spaces. We provide a mean-square-error performance analysis under constant step-sizes. The gain of cooperation in the form of more stability and less bias and variance in the prediction error, is illustrated in the context of a classical model. We show that the improvement in performance is especially significant when the behavior policy of the agents is different from the target policy under evaluation.

Adaptive protection scheme for MVC-encoded stereoscopic video streaming in IP-based networks

We present an adaptive unequal error protection (UEP) strategy built on the 1-D interleaved parity Application Layer Forward Error Correction (AL-FEC) code for protecting the transmission of stereoscopic 3D video content encoded with Multiview Video Coding (MVC) through IP-based networks. Our scheme targets the minimization of quality degradation produced by packet losses during video transmission in time-sensitive application scenarios. To that end, based on a novel packet-level distortion model, it selects in real time the most suitable packets within each Group of Pictures (GOP) to be protected and the most convenient FEC technique parameters, i.e., the size of the FEC generator matrix. In order to make these decisions, it considers the relevance of the packet, the behavior of the channel, and the available bitrate for protection purposes. Simulation results validate both the distortion model introduced to estimate the importance of packets and the optimization of the FEC technique parameter values.

Subjective quality assessment of an adaptive video streaming model

With the recent increased popularity and high usage of HTTP Adaptive Streaming (HAS) techniques, various studies have been carried out in this area which generally focused on the technical enhancement of HAS technology and applications. However, a lack of common HAS standard led to multiple proprietary approaches which have been developed by major Internet companies. In the emerging MPEG-DASH standard the packagings of the video content and HTTP syntax have been standardized; but all the details of the adaptation behavior are left to the client implementation. Nevertheless, to design an adaptation algorithm which optimizes the viewing experience of the enduser, the multimedia service providers need to know about the Quality of Experience (QoE) of different adaptation schemes. Taking this into account, the objective of this experiment was to study the QoE of a HAS-based video broadcast model. The experiment has been carried out through a subjective study of the end user response to various possible clients’ behavior for changing the video quality taking different QoE-influence factors into account. The experimental conclusions have made a good insight into the QoE of different adaptation schemes which can be exploited by HAS clients for designing the adaptation algorithms.

Rapid, local adaptation of zooplankton behavior to changes in predation pressure in the absence of neutral genetic changes

Organisms producing resting stages provide unique opportunities for reconstructing the genetic history of natural populations. Diapausing seeds and eggs often are preserved in large numbers, representing entire populations captured in an evolutionary inert state for decades and even centuries. Starting from a natural resting egg bank of the waterflea Daphnia, we compare the evolutionary rates of change in an adaptive quantitative trait with those in selectively neutral DNA markers, thus effectively testing whether the observed genetic changes in the quantitative trait are driven by natural selection. The population studied experienced variable and well documented levels of fish predation over the past 30 years and shows correlated genetic changes in phototactic behavior, a predator-avoidance trait that is related to diel vertical migration. The changes mainly involve an increased plasticity response upon exposure to predator kairomone, the direction of the changes being in agreement with the hypothesis of adaptive evolution. Genetic differentiation through time was an order of magnitude higher for the studied behavioral trait than for neutral markers (DNA microsatellites), providing strong evidence that natural selection was the driving force behind the observed, rapid, evolutionary changes.

The association of feeding behavior with the resistance and tolerance to parasites in recently diverged sticklebacks

Divergent natural selection regimes can contribute to adaptive population divergence, but can be sensitive to human-mediated environmental change. Nutrient loading of aquatic ecosystems, for example, might modify selection pressures by altering the abundance and distribution of resources and the prevalence and infectivity of parasites. Here, we used a mesocosm experiment to test for interactive effects of nutrient loading and parasitism on host condition and feeding ecology. Specifically, we investigated whether the common fish parasite Gyrodactylus sp. differentially affected recently diverged lake and stream ecotypes of three-spined stickleback (Gasterosteus aculeatus). We found that the stream ecotype had a higher resistance to Gyrodactylus sp. infections than the lake ecotype, and that both ecotypes experienced a cost of parasitism, indicated by negative relationships between parasite load and both stomach fullness and body condition. Overall, our results suggest that in the early stages of adaptive population divergence of hosts, parasites can affect host resistance, body condition, and diet.