SPATIAL-ORGANIZATION OF FORAGING ACTIVITY AND COLONIZATION BY COLONY EMIGRATION IN THE PHARAOH ANT, MONOMORIUM-PHARAONIS

Using food bait stations and colony trap nests, the spatial relation between the foraging activity of established colonies of the polygynous and unicolonial exotic pharaoh's ant, Monomorium pharaonis, and colonization by colony fragments was studied over an 8 month period in a large institutional setting in Brazil. Both foraging activity and colonizations demonstrated significant spatial clumping. However, colonizations were significantly negatively clumped spatially with respect to foraging activity. This suggests that the colonization strategy of this species under the studied conditions was that of complete habitat domination.

Estimating the number of whales entering trade using DNA profiling and capture-recapture analysis of market products

Surveys of commercial markets combined with molecular taxonomy (i.e. molecular monitoring) provide a means to detect products from illegal, unregulated and/or unreported (IUU) exploitation, including the sale of fisheries bycatch and wild meat (bushmeat). Capture-recapture analyses of market products using DNA profiling have the potential to estimate the total number of individuals entering the market. However, these analyses are not directly analogous to those of living individuals because a ‘market individual’ does not die suddenly but, instead, remains available for a time in decreasing quantities, rather like the exponential decay of a radioactive isotope. Here we use mitochondrial DNA (mtDNA) sequences and microsatellite genotypes to individually identify products from North Pacific minke whales (Balaenoptera acutorostrata ssp.) purchased in 12 surveys of markets in the Republic of (South) Korea from 1999 to 2003. By applying a novel capture-recapture model with a decay rate parameter to the 205 unique DNA profiles found among 289 products, we estimated that the total number of whales entering trade across the five-year survey period was 827 (SE, 164; CV, 0.20) and that the average ‘half-life’ of products from an individual whale on the market was 1.82 months (SE, 0.24; CV, 0.13). Our estimate of whales in trade (reflecting the true numbers killed) was significantly greater than the officially reported bycatch of 458 whales for this period. This unregulated exploitation has serious implications for the survival of this genetically distinct coastal population. Although our capture-recapture model was developed for specific application to the Korean whale-meat markets, the exponential decay function could be modified to improve the estimates of trade in other wildmeat or fisheries markets or abundance of living populations by noninvasive genotyping.

Portfolio optimization in the energy market

Let’s put ourselves in the shoes of an energy company. Our fleet of electricity production plants mainly includes gas, hydroelectric and waste-to-energy plants. We also sold contracts for the supply of gas and electricity. For each year we have to plan the trading of the volumes needed by the plants and customers: better to fix the price of these volumes in advance with the so-called forward contracts, instead of waiting for the delivery months, exposing ourselves to price uncertainty. Here’s the thing: trying to keep uncertainty under control in a market that has never shown such extreme scenarios as in recent years: a pandemic, a worsening climate crisis and a war that is affecting economies around the world have made the energy market more volatile than ever. How to make decisions in such uncertain contexts? There is an optimization problem: given a year, we need to choose the optimal planning of volume trading times, to meet the needs of our portfolio at the best prices, taking into account the liquidity constraints given by the market and the risk constraints imposed by the company. Algorithms are needed for the generation of market scenarios over a finite time horizon, that is, a probabilistic distribution that allows a view of all the dates between now and the end of the year of interest. Algorithms are needed to solve the optimization problem: we have proposed more than one and compared them; a very simple one, which avoids considering part of the complexity, moving on to a scenario approach and finally a reinforcement learning approach.

Description of the immatures of the ant, Myrmelachista catharinae

The Neotropical ant genus Myrmelachista Roger comprises 69 described species and subspecies, and still is a poorly studied group. Larvae play a paramount role in colony nutrition in social hymenopterans and bear considerable value in the reconstruction of group phylogenies, however, they are generally neglected. Larvae of different instars of Myrmelachista catharinae Mayr (Hymenoptera: Formicidae) are herein described in detail by light and scanning electron microscopy. The number of larval instars was estimated as three based on the frequency distribution of maximum head capsule widths. The described larvae confirmed some traits typical of the genus: general shape of body and mandibles, general aspect and distribution of body hairs, and the number of sensilla on the palps and galea. Differently from other Myrmelachista larvae previously described, M. catharinae presented two distinct kinds of second instars, some additional types of body hairs, different number of antennal sensilla, and a distinct labrum shape. M. catharinae presented ten pairs of spiracles, which is the first record for this genus.

A novel multiobjective optimization algorithm based on bacterial chemotaxis

In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

Sampled Control for Mean-Variance Hedging in a Jump Diffusion Financial Market

In this technical note we consider the mean-variance hedging problem of a jump diffusion continuous state space financial model with the re-balancing strategies for the hedging portfolio taken at discrete times, a situation that more closely reflects real market conditions. A direct expression based on some change of measures, not depending on any recursions, is derived for the optimal hedging strategy as well as for the ""fair hedging price"" considering any given payoff. For the case of a European call option these expressions can be evaluated in a closed form.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Worker demography in a large-colony, swarm-founding wasp

Neotropical swarm-founding wasps build nests enclosed in a covering envelope, which makes it difficult to count individual births and deaths. Thus, knowledge of worker demography is very limited for swarm-founding species compared with that for independent-founding species. In this study, we explored the worker demography of the swarm-founding wasp Polybia paulista, the colony size of which usually exceeds several thousand adults. We considered each wasp colony as an open-population and estimated the survival probability, recruitment rate, and population size of workers using the developments of the Cormack-Jolly-Seber model. We found that capture probability varied considerably among the workers, probably due to age polyethism and/or task specialization. The daily survival rate of workers was high (around 0.97) throughout the season and was not related to the phase of colony development. On the other hand, the recruitment rate ranged from 0 to 0.37, suggesting that worker production was substantially less important than worker survival in determining worker population fluctuations. When we compared survival rates among worker groups of one colony, the mean daily survival rate was lower for founding workers than for progeny workers and tended to be higher in progeny workers that emerged in winter. These differences in survivorship patterns among worker cohorts would be related to worker foraging activity and/or level of parasitism.

Decision rules for egg recognition are related to functional roles and chemical cues in the queenless ant Dinoponera quadriceps

The capacity to distinguish colony members from strangers is a key component in social life. In social insects, this extends to the brood and involves discrimination of queen eggs. Chemical substances communicate colony affiliation for both adults and brood; thus, in theory, all colony members should be able to recognize fellow nestmates. In this study, we investigate the ability of Dinoponera quadriceps workers to discriminate nestmate and non-nestmate eggs based on cuticular hydrocarbon composition. We analyzed whether cuticular hydrocarbons present on the eggs provide cues of discrimination. The results show that egg recognition in D. quadriceps is related to both age and the functional role of workers. Brood care workers were able to distinguish nestmate from non-nestmate eggs, while callow and forager workers were unable to do so.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

What drives corporate default risk premia? Evidence from the CDS market

This paper studies the evolution of the default risk premia for European firms during the years surrounding the recent credit crisis. We employ the information embedded in Credit Default Swaps (CDS) and Moody’s KMV EDF default probabilities to analyze the common factors driving this risk premia. The risk premium is characterized in several directions: Firstly, we perform a panel data analysis to capture the relationship between CDS spreads and actual default probabilities. Secondly, we employ the intensity framework of Jarrow et al. (2005) in order to measure the theoretical effect of risk premium on expected bond returns. Thirdly, we carry out a dynamic panel data to identify the macroeconomic sources of risk premium. Finally, a vector autoregressive model analyzes which proportion of the co-movement is attributable to financial or macro variables. Our estimations report coefficients for risk premium substantially higher than previously referred for US firms and a time varying behavior. A dominant factor explains around 60% of the common movements in risk premia. Additionally, empirical evidence suggests a public-to-private risk transfer between the sovereign CDS spreads and corporate risk premia.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

Energy and ancillary services joint market simulation

In order to develop a flexible simulator, a variety of models for Ancillary Services (AS) negotiation has been implemented in MASCEM – a multi-agent system competitive electricity markets simulator. In some of these models, the energy and the AS are addressed simultaneously while in other models they are addressed separately. This paper presents an energy and ancillary services joint market simulation. This paper proposes a deterministic approach for solving the energy and ancillary services joint market. A case study based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve, and Non-Spinning Reserve services is used to demonstrate that the use of the developed methodology is suitable for solving this kind of optimization problem. The presented case study is based on CAISO real AS market data considers fifteen bids.