A hybrid cuckoo search and variable neighborhood descent for single and multiobjective scheduling problems

Cuckoo search (CS) is a relatively new meta-heuristic that has proven its strength in solving continuous optimization problems. This papers applies cuckoo search to the class of sequencing problems by hybridizing it with a variable neighborhood descent local search for enhancing the quality of the obtained solutions. The Lévy flight operator proposed in the original CS is modified to address the discrete nature of scheduling problems. Two well-known problems are used to demonstrate the effectiveness of the proposed hybrid CS approach. The first is the NP-hard single objective problem of minimizing the weighted total tardiness time (Formula presented.) and the second is the multiobjective problem of minimizing the flowtime ¯ and the maximum tardiness Tmaxfor single machine (Formula presented.). For the first problem, computational results show that the hybrid CS is able to find the optimal solutions for all benchmark test instances with 40, 50, and 100 jobs and for most instances with 150, 200, 250, and 300 jobs. For the second problem, the hybrid CS generated solutions on and very close to the exact Pareto fronts of test instances with 10, 20, 30, and 40 jobs. In general, the results reveal that the hybrid CS is an adequate and robust method for tackling single and multiobjective scheduling problems.

Ecosystem relevance of variable jellyfish biomass in the Irish Sea between years, regions and water types

Monitoring the abundance and distribution of taxa is essential to assess their contribution to ecosystem processes. For marine taxa that are difficult to study or have long been perceived of little ecological importance, quantitative information is often lacking. This is the case for jellyfish (medusae and other gelatinous plankton). In the present work, 4 years of scyphomedusae by-catch data from the 2007-2010 Irish Sea juvenile gadoid fish survey were analysed with three main objectives: (1) to provide quantitative and spatially-explicit species-specific biomass data, for a region known to have an increasing trend in jellyfish abundance; (2) to investigate whether year-to-year changes in catch-biomass are due to changes in the numbers or in the size of medusa (assessed as the mean mass per individual), and (3) to determine whether inter-annual variation patterns are consistent between species and water masses. Scyphomedusae were present in 97% of samples (N=306). Their overall annual median catch-biomass ranged from 0.19 to 0.92gm-3 (or 8.6 to 42.4gm-2). Aurelia aurita and Cyanea spp. (Cyanea lamarckii and Cyanea capillata) made up 77.7% and 21.5% of the total catch-biomass respectively, but species contributions varied greatly between sub-regions and years. No consistent pattern was detected between the distribution and inter-annual variations of the two genera, and contrasting inter-annual patterns emerged when considering abundance either as biomass or as density. Significantly, A.aurita medusae were heavier in stratified than in mixed waters, which we hypothesize may be linked to differences in timing and yield of primary and secondary productions between water masses. These results show the vulnerability of time-series from bycatch datasets to phenological changes and highlight the importance of taking species- and population-specific distribution patterns into account when integrating jellyfish into ecosystem models.

Paradox lost: variable colour-pattern geometry is associated with differences in movement in aposematic frogs

Aposematic signal variation is a paradox: predators are better at learning and retaining the association between conspicuousness and unprofitability when signal variation is low. Movement patterns and variable colour patterns are linked in non-aposematic species: striped patterns generate illusions of altered speed and direction when moving linearly, affecting predators' tracking ability; blotched patterns benefit instead from unpredictable pauses and random movement. We tested whether the extensive colour-pattern variation in an aposematic frog is linked to movement, and found that individuals moving directionally and faster have more elongated patterns than individuals moving randomly and slowly. This may help explain the paradox of polymorphic aposematism: variable warning signals may reduce protection, but predator defence might still be effective if specific behaviours are tuned to specific signals. The interacting effects of behavioural and morphological traits may be a key to the evolution of warning signals. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

New variable step-sizes minimizing mean-square deviation for the lms-type algorithms

The least-mean-square-type (LMS-type) algorithms are known as simple and effective adaptation algorithms. However, the LMS-type algorithms have a trade-off between the convergence rate and steady-state performance. In this paper, we investigate a new variable step-size approach to achieve fast convergence rate and low steady-state misadjustment. By approximating the optimal step-size that minimizes the mean-square deviation, we derive variable step-sizes for both the time-domain normalized LMS (NLMS) algorithm and the transform-domain LMS (TDLMS) algorithm. The proposed variable step-sizes are simple quotient forms of the filtered versions of the quadratic error and very effective for the NLMS and TDLMS algorithms. The computer simulations are demonstrated in the framework of adaptive system modeling. Superior performance is obtained compared to the existing popular variable step-size approaches of the NLMS and TDLMS algorithms. © 2014 Springer Science+Business Media New York.

Using occupancy as a state variable for monitoring the critically endangered Alaotran gentle lemur Hapalemur alaotrensis

Although monitoring is an essential tool for biodiversity conservation, monitoring programmes are often poorly designed and thus unlikely to produce results that are meaningful for management. Monitoring is especially challenging when dealing with rare and elusive species in areas where conservation resources are particularly limited. In such cases, monitoring techniques aimed at estimating occupancy represent an attractive alternative to traditional methods concerned with estimating population size, as the collection of detection/non-detection data is in general less costly and easier to implement. In this study, we evaluated the use of occupancy as a state variable for the monitoring of the Alaotran gentle lemur Hapalemur alaotrensis, a Critically Endangered primate exclusively inhabiting the dense marshes around Lake Alaotra in Madagascar. We used a likelihood-based modelling approach that explicitly accounts for detectability. This showed that the probability of detection of H. alaotrensis was extremely low and depended on site characteristics that can vary in space and time, confirming the need to account for imperfect detection when monitoring this species. We used our models to explore factors affecting the probability of occupancy and detection to identify management implications, and also developed recommendations for the ongoing monitoring of this species. The method applied in this study provides an efficient tool for the monitoring of an elusive species and has the potential to provide a flexible sampling framework for local community based monitoring initiatives.

Variable environmental effects on a multicomponent sexually selected trait

Multicomponent signals are made up of interacting elements that generate a functional signaling unit. The interactions between signal components and their effects on individual fitness are not well understood, and the effect of environment is even less so. It is usually assumed that color patterns appear the same in all light environments and that the effects of each color are additive. Using guppies, Poecilia reticulata, we investigated the effect of water color on the interactions between components of sexually selected male coloration. Through behavioral mate choice trials in four different water colors, we estimated the attractiveness of male color patterns, using multivariate fitness estimates and overall signal contrast. Our results show that females exhibit preferences that favor groups of colors rather than individual colors independently and that each environment favors different color combinations. We found that these effects are consistent with female guppies selecting entire color patterns on the basis of overall visual contrast. This suggests that both individuals and populations inhabiting different light environments will be subject to divergent, multivariate selection. Although the appearance of color patterns changes with light environment, achromatic components change little, suggesting that these could function in species recognition or other aspects of communication that must work across environments. Consequently, we predict different phylogenetic patterns between chromatic and achromatic signals within the same clades.

The double sensor-a non-invasive device to continuously monitor core temperature in humans on earth and in space

The objective of our study was to establish whether rectal temperature recordings in humans could be replaced by a non-invasive skin temperature sensor combined with a heat flux sensor (Double Sensor) located at the forehead to monitor core body temperature changes due to circadian rhythms. Rectal and Double Sensor data were collected continuously for 24h in seven men undertaking strict head-down tilt bed-rest. Individual differences between the two techniques varied between -0.72 and +0.55 degrees C. Nonetheless, when temperature data were approximated by cosinor analysis in order to compare circadian rhythm profiles between methods, it was observed that there were no significant differences between mesor, amplitude, and acrophase (P>0.310). It was therefore concluded that the Double Sensor technology is presently not accurate enough for performing single individual core body temperature measurements under resting conditions at normal ambient room temperature. Yet, it seems to be a valid, non-invasive alternative for monitoring circadian rhythm profiles.

Avian influenza infection dynamics under variable climatic conditions, viral prevalence is rainfall driven in waterfowl from temperate, south-east Australia

Understanding Avian Influenza Virus (AIV) infection dynamics in wildlife is crucial because of possible virus spill over to livestock and humans. Studies from the northern hemisphere have suggested several ecological and environmental drivers of AIV prevalence in wild birds. To determine if the same drivers apply in the southern hemisphere, where more irregular environmental conditions prevail, we investigated AIV prevalence in ducks in relation to biotic and abiotic factors in south-eastern Australia. We sampled duck faeces for AIV and tested for an effect of bird numbers, rainfall anomaly, temperature anomaly and long-term ENSO (El-Niño Southern Oscillation) patterns on AIV prevalence. We demonstrate a positive long term effect of ENSO-related rainfall on AIV prevalence. We also found a more immediate response to rainfall where AIV prevalence was positively related to rainfall in the preceding 3-7 months. Additionally, for one duck species we found a positive relationship between their numbers and AIV prevalence, while prevalence was negatively or not affected by duck numbers in the remaining four species studied. In Australia largely non-seasonal rainfall patterns determine breeding opportunities and thereby influence bird numbers. Based on our findings we suggest that rainfall influences age structures within populations, producing an influx of immunologically naïve juveniles within the population, which may subsequently affect AIV infection dynamics. Our study suggests that drivers of AIV dynamics in the northern hemisphere do not have the same influence at our south-east Australian field site in the southern hemisphere due to more erratic climatological conditions.

Functional observer design with application to pre-compensated multi-variable systems

Partial state estimation of dynamical systems provides significant advantages in practical applications. Likewise, pre-compensator design for multi variable systems invokes considerable increase in the order of the original system. Hence, applying functional observer to pre-compensated systems can result in lower computational costs and more practicability in some applications such as fault diagnosis and output feedback control of these systems. In this note, functional observer design is investigated for pre-compensated systems. A lower order pre-compensator is designed based on a H2 norm optimization that is designed as the solution of a set of linear matrix inequalities (LMIs). Next, a minimum order functional observer is designed for the pre-compensated system. An LTI model of an irreversible chemical reactor is used to demonstrate our design algorithm, and to highlight the benefits of the proposed schemes.