Life span and reproductive cost explain interspecific variation in the optimal onset of reproduction.

Fitness can be profoundly influenced by the age at first reproduction (AFR), but to date the AFR-fitness relationship only has been investigated intraspecifically. Here, we investigated the relationship between AFR and average lifetime reproductive success (LRS) across 34 bird species. We assessed differences in the deviation of the Optimal AFR (i.e., the species-specific AFR associated with the highest LRS) from the age at sexual maturity, considering potential effects of life history as well as social and ecological factors. Most individuals adopted the species-specific Optimal AFR and both the mean and Optimal AFR of species correlated positively with life span. Interspecific deviations of the Optimal AFR were associated with indices reflecting a change in LRS or survival as a function of AFR: a delayed AFR was beneficial in species where early AFR was associated with a decrease in subsequent survival or reproductive output. Overall, our results suggest that a delayed onset of reproduction beyond maturity is an optimal strategy explained by a long life span and costs of early reproduction. By providing the first empirical confirmations of key predictions of life-history theory across species, this study contributes to a better understanding of life-history evolution.

The maximum voltage drop in an on-chip power distribution network: analysis of square, triangular and hexagonal power pad arrangements

A mathematical model of the voltage drop which arises in on-chip power distribution networks is used to compare the maximum voltage drop in the case of different geometric arrangements of the pads supplying power to the chip. These include the square or Manhattan power pad arrangement, which currently predominates, as well as equilateral triangular and hexagonal arrangements. In agreement with the findings in the literature and with physical and SPICE models, the equilateral triangular power pad arrangement is found to minimize the maximum voltage drop. This headline finding is a consequence of relatively simple formulas for the voltage drop, with explicit error bounds, which are established using complex analysis techniques, and elliptic functions in particular.

ALLOMETRIC MODELS FOR ESTIMATING ABOVEGROUND BIOMASS AND BIOMASS ALLOCATION OF CAPIXINGUI TREES (Croton floribundus Spreng.) IN AN AGRISILVICULTURAL SYSTEM

ABSTRACT The objective of this study was to select allometric models to estimate total and pooled aboveground biomass of 4.5-year-old capixingui trees established in an agrisilvicultural system. Aboveground biomass distribution of capixingui was also evaluated. Single- (diameter at breast height [DBH] or crown diameter or stem diameter as the independent variable) and double-entry (DBH or crown diameter or stem diameter and total height as independent variables) models were studied. The estimated total biomass was 17.3 t.ha-1, corresponding to 86.6 kg per tree. All models showed a good fit to the data (R2ad > 0.85) for bole, branches, and total biomass. DBH-based models presented the best residual distribution. Model lnW = b0 + b1* lnDBH can be recommended for aboveground biomass estimation. Lower coefficients were obtained for leaves (R2ad > 82%). Biomass distribution followed the order: bole>branches>leaves. Bole biomass percentage decreased with increasing DBH of the trees, whereas branch biomass increased.

Optimal design of 3R manipulators by using classical techniques and simulated annealin

In this paper, the optimum design of 3R manipulators is formulated and solved by using an algebraic formulation of workspace boundary. A manipulator design can be approached as a problem of optimization, in which the objective functions are the size of the manipulator and workspace volume; and the constrains can be given as a prescribed workspace volume. The numerical solution of the optimization problem is investigated by using two different numerical techniques, namely, sequential quadratic programming and simulated annealing. Numerical examples illustrate a design procedure and show the efficiency of the proposed algorithms.

Effect of plant regulators on growth and flowering of 'Meyer' zoysiagrass

This trial aimed to evaluate the effect of sequential applications of different plant regulators over growth and flower rachis emission of 'Meyer' zoysiagrass (Zoysia japonica). The study was conducted on 15-month old green turfgrass under a randomized complete block design with four replications. The following plant regulator and doses were tested: trinexapac-ethyl (113+113, 226+113, 226+226, 452+113, 452+226, 452+452, 678+339 e 904+452 g a.i./ha-1), prohexadione-calcium (100+100 e 200+200 g a.i. ha-1) and bispyribac-sodium (40+40 e 60+60 g a.i. ha-1), as well as an untreated control. The turfgrass was mowed again at 3.0 cm aboveground and the second plant regulator was applied when 'Meyer' zoysiagrass was between 5.0 and 6.0 cm high. The effect of the treatments was visually rated for visual injury, plant height, height and number of flower rachis, and total dry mass production of clippings. Only bispyribac-sodium had visual symptoms of injury on 'Meyer' zoysiagrass, and no intoxication was observed at 28 days after the second application (DAAB). The sequential applications of trinexapac-ethyl, prohexadione-calcium and bispyribac-sodium reduced by more than 80% the total clipping dry mass produced by 'Meyer' zoysiagrass. All the plant regulators tested also showed promising results in reducing the height and emission of rachis, especially when trinexapac-ethyl was applied at the doses 452+452, 678+339 and 904+452 g a.i. ha-1. 'Meyer' zoysiagrass turfgrass can be handled with the sequential application of a plant regulator, which reduces the need for mowing over a period up to 110 days after the application of the second plant regulator, and it also avoids deleterious visual effects over turfgrass.

Choosing the target loci : heat shock factors HSF1 and HSF2 as regulators of cell stress and development

Heat shock factors (HSFs) are an evolutionarily well conserved family of transcription factors that coordinate stress-induced gene expression and direct versatile physiological processes in eukaryote organisms. The essentiality of HSFs for cellular homeostasis has been well demonstrated, mainly through HSF1-induced transcription of heat shock protein (HSP) genes. HSFs are important regulators of many fundamental processes such as gametogenesis, metabolic control and aging, and are involved in pathological conditions including cancer progression and neurodegenerative diseases. In each of the HSF-mediated processes, however, the detailed mechanisms of HSF family members and their complete set of target genes have remained unknown. Recently, rapid advances in chromatin studies have enabled genome-wide characterization of protein binding sites in a high resolution and in an unbiased manner. In this PhD thesis, these novel methods that base on chromatin immunoprecipitation (ChIP) are utilized and the genome-wide target loci for HSF1 and HSF2 are identified in cellular stress responses and in developmental processes. The thesis and its original publications characterize the individual and shared target genes of HSF1 and HSF2, describe HSF1 as a potent transactivator, and discover HSF2 as an epigenetic regulator that coordinates gene expression throughout the cell cycle progression. In male gametogenesis, novel physiological functions for HSF1 and HSF2 are revealed and HSFs are demonstrated to control the expression of X- and Y-chromosomal multicopy genes in a silenced chromatin environment. In stressed human cells, HSF1 and HSF2 are shown to coordinate the expression of a wide variety of genes including genes for chaperone machinery, ubiquitin, regulators of cell cycle progression and signaling. These results highlight the importance of cell type and cell cycle phase in transcriptional responses, reveal the myriad of processes that are adjusted in a stressed cell and describe novel mechanisms that maintain transcriptional memory in mitotic cell division.

Mathematical modeling and optimal control of malaria

Malaria continues to infect millions and kill hundreds of thousands of people worldwide each year, despite over a century of research and attempts to control and eliminate this infectious disease. Challenges such as the development and spread of drug resistant malaria parasites, insecticide resistance to mosquitoes, climate change, the presence of individuals with subpatent malaria infections which normally are asymptomatic and behavioral plasticity in the mosquito hinder the prospects of malaria control and elimination. In this thesis, mathematical models of malaria transmission and control that address the role of drug resistance, immunity, iron supplementation and anemia, immigration and visitation, and the presence of asymptomatic carriers in malaria transmission are developed. A within-host mathematical model of severe Plasmodium falciparum malaria is also developed. First, a deterministic mathematical model for transmission of antimalarial drug resistance parasites with superinfection is developed and analyzed. The possibility of increase in the risk of superinfection due to iron supplementation and fortification in malaria endemic areas is discussed. The model results calls upon stakeholders to weigh the pros and cons of iron supplementation to individuals living in malaria endemic regions. Second, a deterministic model of transmission of drug resistant malaria parasites, including the inflow of infective immigrants, is presented and analyzed. The optimal control theory is applied to this model to study the impact of various malaria and vector control strategies, such as screening of immigrants, treatment of drug-sensitive infections, treatment of drug-resistant infections, and the use of insecticide-treated bed nets and indoor spraying of mosquitoes. The results of the model emphasize the importance of using a combination of all four controls tools for effective malaria intervention. Next, a two-age-class mathematical model for malaria transmission with asymptomatic carriers is developed and analyzed. In development of this model, four possible control measures are analyzed: the use of long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic, and screening and treatment of asymptomatic individuals. The numerical results show that a disease-free equilibrium can be attained if all four control measures are used. A common pitfall for most epidemiological models is the absence of real data; model-based conclusions have to be drawn based on uncertain parameter values. In this thesis, an approach to study the robustness of optimal control solutions under such parameter uncertainty is presented. Numerical analysis of the optimal control problem in the presence of parameter uncertainty demonstrate the robustness of the optimal control approach that: when a comprehensive control strategy is used the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the design of cost-effective strategies for disease control with multiple interventions, even under considerable uncertainty of model parameters. Finally, a separate work modeling the within-host Plasmodium falciparum infection in humans is presented. The developed model allows re-infection of already-infected red blood cells. The model hypothesizes that in severe malaria due to parasite quest for survival and rapid multiplication, the Plasmodium falciparum can be absorbed in the already-infected red blood cells which accelerates the rupture rate and consequently cause anemia. Analysis of the model and parameter identifiability using Markov chain Monte Carlo methods is presented.

Fair Production and Allocation of an Excludable Nonrival Good

We study fairness in economies with one private good and one partially excludable nonrival good. A social ordering function determines for each profile of preferences an ordering of all conceivable allocations. We propose the following Free Lunch Aversion condition: if the private good contributions of two agents consuming the same quantity of the nonrival good have opposite signs, reducing that gap improves social welfare. This condition, combined with the more standard requirements of Unanimous Indifference and Responsiveness, delivers a form of welfare egalitarianism in which an agent's welfare at an allocation is measured by the quantity of the nonrival good that, consumed at no cost, would leave her indifferent to the bundle she is assigned.

The Alberta Dilemma: Optimal Sharing of a Water Resource by an Agricultural and an Oil Sector

The purpose of this paper is to characterize the optimal time paths of production and water usage by an agricultural and an oil sector that have to share a limited water resource. We show that for any given water stock, if the oil stock is sufficiently large, it will become optimal to have a phase during which the agricultural sector is inactive. This may mean having an initial phase during which the two sectors are active, then a phase during which the water is reserved for the oil sector and the agricultural sector is inactive, followed by a phase during which both sectors are active again. The agricultural sector will always be active in the end as the oil stock is depleted and the demand for water from the oil sector decreases. In the case where agriculture is not constrained by the given natural inflow of water once there is no more oil, we show that oil extraction will always end with a phase during which oil production follows a pure Hotelling path, with the implicit price of oil net of extraction cost growing at the rate of interest. If the natural inflow of water does constitute a constraint for agriculture, then oil production never follows a pure Hotelling path, because its full marginal cost must always reflect not only the imputed rent on the finite oil stock, but also the positive opportunity cost of water.

Efficient Characterisation and Optimal Control of Open Quantum Systems - Mathematical Foundations and Physical Applications

Since no physical system can ever be completely isolated from its environment, the study of open quantum systems is pivotal to reliably and accurately control complex quantum systems. In practice, reliability of the control field needs to be confirmed via certification of the target evolution while accuracy requires the derivation of high-fidelity control schemes in the presence of decoherence. In the first part of this thesis an algebraic framework is presented that allows to determine the minimal requirements on the unique characterisation of arbitrary unitary gates in open quantum systems, independent on the particular physical implementation of the employed quantum device. To this end, a set of theorems is devised that can be used to assess whether a given set of input states on a quantum channel is sufficient to judge whether a desired unitary gate is realised. This allows to determine the minimal input for such a task, which proves to be, quite remarkably, independent of system size. These results allow to elucidate the fundamental limits regarding certification and tomography of open quantum systems. The combination of these insights with state-of-the-art Monte Carlo process certification techniques permits a significant improvement of the scaling when certifying arbitrary unitary gates. This improvement is not only restricted to quantum information devices where the basic information carrier is the qubit but it also extends to systems where the fundamental informational entities can be of arbitary dimensionality, the so-called qudits. The second part of this thesis concerns the impact of these findings from the point of view of Optimal Control Theory (OCT). OCT for quantum systems utilises concepts from engineering such as feedback and optimisation to engineer constructive and destructive interferences in order to steer a physical process in a desired direction. It turns out that the aforementioned mathematical findings allow to deduce novel optimisation functionals that significantly reduce not only the required memory for numerical control algorithms but also the total CPU time required to obtain a certain fidelity for the optimised process. The thesis concludes by discussing two problems of fundamental interest in quantum information processing from the point of view of optimal control - the preparation of pure states and the implementation of unitary gates in open quantum systems. For both cases specific physical examples are considered: for the former the vibrational cooling of molecules via optical pumping and for the latter a superconducting phase qudit implementation. In particular, it is illustrated how features of the environment can be exploited to reach the desired targets.

Optimal management of natural resources. Accounting for heterogeneity

Dynamic optimization methods have become increasingly important over the last years in economics. Within the dynamic optimization techniques employed, optimal control has emerged as the most powerful tool for the theoretical economic analysis. However, there is the need to advance further and take account that many dynamic economic processes are, in addition, dependent on some other parameter different than time. One can think of relaxing the assumption of a representative (homogeneous) agent in macro- and micro-economic applications allowing for heterogeneity among the agents. For instance, the optimal adaptation and diffusion of a new technology over time, may depend on the age of the person that adopted the new technology. Therefore, the economic models must take account of heterogeneity conditions within the dynamic framework. This thesis intends to accomplish two goals. The first goal is to analyze and revise existing environmental policies that focus on defining the optimal management of natural resources over time, by taking account of the heterogeneity of environmental conditions. Thus, the thesis makes a policy orientated contribution in the field of environmental policy by defining the necessary changes to transform an environmental policy based on the assumption of homogeneity into an environmental policy which takes account of heterogeneity. As a result the newly defined environmental policy will be more efficient and likely also politically more acceptable since it is tailored more specifically to the heterogeneous environmental conditions. Additionally to its policy orientated contribution, this thesis aims making a methodological contribution by applying a new optimization technique for solving problems where the control variables depend on two or more arguments --- the so-called two-stage solution approach ---, and by applying a numerical method --- the Escalator Boxcar Train Method --- for solving distributed optimal control problems, i.e., problems where the state variables, in addition to the control variables, depend on two or more arguments. Chapter 2 presents a theoretical framework to determine optimal resource allocation over time for the production of a good by heterogeneous producers, who generate a stock externalit and derives government policies to modify the behavior of competitive producers in order to achieve optimality. Chapter 3 illustrates the method in a more specific context, and integrates the aspects of quality and time, presenting a theoretical model that allows to determine the socially optimal outcome over time and space for the problem of waterlogging in irrigated agricultural production. Chapter 4 of this thesis concentrates on forestry resources and analyses the optimal selective-logging regime of a size-distributed forest.