The Consequences of Phenotypic Plasticity in Cyclically Varying Environments: A Genetic Algorithm Study

By “phenotypic plasticity” we refer to the capacity of a genotype to exhibit different phenotypes, whether in the same or in different environments. We have previously demonstrated that phenotypic plasticity can improve the degree of adaptation achieved via natural selection (Behera & Nanjundiah, 1995). That result was obtained from a genetic algorithm model of haploid genotypes (idealized as one-dimensional strings of genes) evolving in a fixed environment. Here, the dynamics of evolution is examined under conditions of a cyclically varying environment. We find that the rate of evolution, as well as the extent of adaptation (as measured by mean population fitness) is lowered because of environmental cycling. The decrease is adaptation caused by a varying environment can, however, be partly or wholly compensated by an increase in the degree of plasticity that a genotype is capable of. Also, the reduction of population fitness caused by a variable environment can be partially offset by decreasing the total number of genetic loci. We conjecture that an increase in genome size may have been among the factors responsible for the evolution of phenotypic plasticity.

Neural networks for time-varying data

This paper reviews some basic issues and methods involved in using neural networks to respond in a desired fashion to a temporally-varying environment. Some popular network models and training methods are introduced. A speech recognition example is then used to illustrate the central difficulty of temporal data processing: learning to notice and remember relevant contextual information. Feedforward network methods are applicable to cases where this problem is not severe. The application of these methods are explained and applications are discussed in the areas of pure mathematics, chemical and physical systems, and economic systems. A more powerful but less practical algorithm for temporal problems, the moving targets algorithm, is sketched and discussed. For completeness, a few remarks are made on reinforcement learning.

Efficient multiple relay selection for cooperative communication using alamouti-coded virtual transmit antenna systems

An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.

Is the sun too bright in Queensland? An approach to robust outdoor colour beacon detection

Using cameras onboard a robot for detecting a coloured stationary target outdoors is a difficult task. Apart from the complexity of separating the target from the background scenery over different ranges, there are also the inconsistencies with direct and reflected illumination from the sun,clouds, moving and stationary objects. They can vary both the illumination on the target and its colour as perceived by the camera. In this paper, we analyse the effect of environment conditions, range to target, camera settings and image processing on the reported colours of various targets. The analysis indicates the colour space and camera configuration that provide the most consistent colour values over varying environment conditions and ranges. This information is used to develop a detection system that provides range and bearing to detected targets. The system is evaluated over various lighting conditions from bright sunlight, shadows and overcast days and demonstrates robust performance. The accuracy of the system is compared against a laser beacon detector with preliminary results indicating it to be a valuable asset for long-range coloured target detection.

Real Time Eye Tracking and Blink Detection with USB Cameras

A human-computer interface (HCI) system designed for use by people with severe disabilities is presented. People that are severely paralyzed or afflicted with diseases such as ALS (Lou Gehrig's disease) or multiple sclerosis are unable to move or control any parts of their bodies except for their eyes. The system presented here detects the user's eye blinks and analyzes the pattern and duration of the blinks, using them to provide input to the computer in the form of a mouse click. After the automatic initialization of the system occurs from the processing of the user's involuntary eye blinks in the first few seconds of use, the eye is tracked in real time using correlation with an online template. If the user's depth changes significantly or rapid head movement occurs, the system is automatically reinitialized. There are no lighting requirements nor offline templates needed for the proper functioning of the system. The system works with inexpensive USB cameras and runs at a frame rate of 30 frames per second. Extensive experiments were conducted to determine both the system's accuracy in classifying voluntary and involuntary blinks, as well as the system's fitness in varying environment conditions, such as alternative camera placements and different lighting conditions. These experiments on eight test subjects yielded an overall detection accuracy of 95.3%.

Studies on the common penaeid prawns of the Kerala coast

Very little is known about the tolerance of the pensoid prawns in Indian waters under varying environment conditions ,except for a note on the salinityon The growth of the juvenile papacus indicus by sreekumaran nair and krishnankutty there seems to be no work on this aspect besides the oxygen consumption of metsponecus dobsoni which is a major constituent of prawn fishery in this region has not been studied so far.T he present work comprises studies on the occurrence and abudance of penacid prawnsin two major estuaries in Kerala the kayamkulam lake and cochin backwaters the salinity and tempeture tolerance the effect of salinity on the growth of three comercially important prawns of kerala namely pensecus indicus, ,metaponaeus dobsoni, M monoceros and the respiratory metabolism of M. dobsoni.

Inference From Aging Information

For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps.

Acid-base regulation in the Dungeness crab (Metacarcinus magister)

Homeostatic regulation allows organisms to secure basic physiological processes in a varying environment. To counteract fluctuations in ambient carbonate system speciation due to elevated seawater pCO2 (hypercapnia), many aquatic crustaceans excrete/accumulate acid-base equivalents through their gills; however, not much is known about the role of ammonia in this response. The present study investigated the effects of hypercapnia on acid-base and ammonia regulation in the Dungeness crab, Metacarcinus magister on the whole animal and isolated gill levels. Hemolymph pCO2 and [HCO3]- increased in M. magister acclimated to elevated pCO2 (330 Pa), while pH remained stable. Additionally, hemolymph [Na+], [Ca2+], and [SO4]2- were significantly increased. When challenged with varying pH during gill perfusion, the pH of the artificial hemolymph remained relatively unchanged. Overall, ammonia production and excretion, as well as oxygen consumption, were reduced in crabs acclimated to elevated pCO2, demonstrating that either (amino acid) oxidation is reduced in response to this particular stress, or nitrogenous wastes are excreted in an alternative form.

Extremes of Bivariate Geometric Variables with Application to Bisexual Branching Processes

2000 Mathematics Subject Classification: 60J80, 60G70.

Dynamic variability in adaptive systems

One of the reasons for using variability in the software product line (SPL) approach (see Apel et al., 2006; Figueiredo et al., 2008; Kastner et al., 2007; Mezini & Ostermann, 2004) is to delay a design decision (Svahnberg et al., 2005). Instead of deciding on what system to develop in advance, with the SPL approach a set of components and a reference architecture are specified and implemented (during domain engineering, see Czarnecki & Eisenecker, 2000) out of which individual systems are composed at a later stage (during application engineering, see Czarnecki & Eisenecker, 2000). By postponing the design decisions in such a manner, it is possible to better fit the resultant system in its intended environment, for instance, to allow selection of the system interaction mode to be made after the customers have purchased particular hardware, such as a PDA vs. a laptop. Such variability is expressed through variation points which are locations in a software-based system where choices are available for defining a specific instance of a system (Svahnberg et al., 2005). Until recently it had sufficed to postpone committing to a specific system instance till before the system runtime. However, in the recent years the use and expectations of software systems in human society has undergone significant changes.Today's software systems need to be always available, highly interactive, and able to continuously adapt according to the varying environment conditions, user characteristics and characteristics of other systems that interact with them. Such systems, called adaptive systems, are expected to be long-lived and able to undertake adaptations with little or no human intervention (Cheng et al., 2009). Therefore, the variability now needs to be present also at system runtime, which leads to the emergence of a new type of system: adaptive systems with dynamic variability.

Evaluation of contact and non-contact trapping efficiencies of human scent chemical profiles and their stabilities under different environmental conditions

Establishing an association between the scent a perpetrator left at a crime scene to the odor of the suspect of that crime is the basis for the use of human scent identification evidence in a court of law. Law enforcement agencies gather evidence through the collection of scent from the objects that a perpetrator may have handled during the execution of the criminal act. The collected scent evidence is consequently presented to the canines for identification line-up procedures with the apprehended suspects. Presently, canine scent identification is admitted as expert witness testimony, however, the accurate behavior of the dogs and the scent collection methods used are often challenged by the court system. The primary focus of this research project entailed an evaluation of contact and non-contact scent collection techniques with an emphasis on the optimization of collection materials of different fiber chemistries to evaluate the chemical odor profiles obtained using varying environment conditions to provide a better scientific understanding of human scent as a discriminative tool in the identification of suspects. The collection of hand odor from female and male subjects through both contact and non-contact sampling approaches yielded new insights into the types of VOCs collected when different materials are utilized, which had never been instrumentally performed. Furthermore, the collected scent mass was shown to be obtained in the highest amounts for both gender hand odor samples on cotton sorbent materials. Compared to non-contact sampling, the contact sampling methods yielded a higher number of volatiles, an enhancement of up to 3 times, as well as a higher scent mass than non-contact methods by more than an order of magnitude. The evaluation of the STU-100 as a non-contact methodology highlighted strong instrumental drawbacks that need to be targeted for enhanced scientific validation of current field practices. These results demonstrated that an individual's human scent components vary considerably depending on the method used to collect scent from the same body region. This study demonstrated the importance of collection medium selection as well as the collection method employed in providing a reproducible human scent sample that can be used to differentiate individuals.

Surfing the high energy output branch of nonlinear energy harvesters

Hysteresis and multistability are fundamental phenomena of driven nonlinear oscillators, which, however, restrict many applications such as mechanical energy harvesting. We introduce an electrical control mechanism to switch from the low to the high energy output branch of a nonlinear energy harvester by exploiting the strong interplay between its electrical and mechanical degrees of freedom. This method improves the energy conversion efficiency over a wide bandwidth in a frequency-amplitude-varying environment using only a small energy budget. The underlying effect is independent of the device scale and the transduction method and is explained using a modified Duffing oscillator model.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.