Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

In-tube solid-phase microextraction coupled to liquid chromatography (in-tube SPME/LC) analysis of nontricyclic antidepressants in human plasma

A sensitive, selective, and reproducible in-tube solid-phase microextraction and liquid chromatographic (in-tube SPME/LC-UV) method for simultaneous determination of mirrazapine, citalopram, paroxetine, duloxetine, fluoxetine, and sertraline in human plasma was developed, validated and further applied to the analysis of plasma samples from elderly patients undergoing therapy with antidepressants. Important factors in the optimization of in-tube SPME efficiency are discussed, including the sample draw/eject volume, draw/eject cycle number, draw/eject flow-rate, sample pH, and influence of plasma proteins. The quantification limits of the in-tube SPME/LC method varied between 20 and 50 ng/mL, with a coefficient of variation lower than 10%. The response of the in-tube SPME/LC method for most of the drugs was linear over a dynamic range from 50 to 500 ng/mL, with correlation coefficients higher than 0.9985. The in-tube SPME/LC can be successfully used to analyze plasma samples from ageing patients undergoing therapy with nontricyclic antidepressants. (c) 2007 Elsevier B.V. All rights reserved.

Simultaneous analysis of parabens in cosmetic products by stir bar sorptive extraction and liquid chromatography

A sensitive and precise stir bar sorptive extraction (SBSE) combined with LC (SBSE/LC) analysis is described for simultaneous determination of methyl, ethyl, propyl, and butyl parabens in commercial cosmetic products in agreement with the European Union Cosmetics Directive 76/768/EEC. Important factors in the optimization of SB SE efficiency are discussed, such as time and temperature of extraction, pH, and ionic strength of the sample, matrix effects, and liquid desorption conditions by different modes (magnetic stirring, ultrasonic). The LOQs of the SBSE/LC method ranged from 30 to 200 ng/mg, with linear response over a dynamic range, from the LOQ to 2.5 mu g/mg, with a coefficient of determination higher than 0.993. The interday precision of the SBSE/LC method presented a coefficient of variation lower than 5%. The effectiveness of the proposed method was proven for analysis of commercial cosmetic products such as body creams, antiperspirant creams, and sunscreens.

Determination of fluoxetine and norfluoxetine enantiomers in human plasma by polypyrrole-coated capillary in-tube solid-phase microextraction coupled with liquid chromatography-fluorescence detection

A sensitive, selective, and reproducible in-tube polypyrrole-coated capillary (PPY) solid-phase microextraction and liquid chromatographic method for fluoxetine and norfluoxetine enantiomers analysis in plasma samples has been developed, validated, and further applied to the analysis of plasma samples from elderly patients undergoing therapy with antidepressants. Important factors in the optimization of in-tube SPME efficiency are discussed, including the sample draw/eject volume, draw/eject cycle number, draw/eject flow-rate, sample pH, and influence of plasma proteins. Separation of the analytes was achieved with a Chiralcel OD-R column and a mobile phase consisting of potassium hexafluorophosphate 7.5 mM and sodium phosphate 0.25 M solution, pH 3.0, and acetonitrile (75:25, v/v) in the isocratic mode, at a flow rate of 1.0 mL/min. Detection was carried out by fluorescence absorbance at Ex/Em 230/290 nm. The multifunctional porous surface structure of the PPY-coated film provided high precision and accuracy for enantiomers. Compared with other commercial capillaries, PPY-coated capillary showed better extraction efficiency for all the analytes. The quantification limits of the proposed method were 10 ng/mL for R- and S-fluoxetine, and 15 ng/mL for R- and S-norfluoxetine, with a coefficient of variation lower than 13%. The response of the method for enantiomers is linear over a dynamic range, from the limit of quantification to 700ng/mL, with correlation coefficients higher than 0.9940. The in-tube SPME/LC method can therefore be successfully used to analyze plasma samples from ageing patients undergoing therapy with fluoxetine. (C) 2009 Elsevier B.V. All rights reserved.

Dynamic strain measurement using piezoelectric polymer film

Piezoelectric polymers have been used to form the basis of dynamic strain gauges for the detection of stress waves. The linearity of response was tested using a split Hopkinson pressure bar arrangement. The results obtained illustrate the effectiveness of piezoelectric film strain gauges in the measurement of axial stress waves.

The Hus1 homologue of Leishmania major encodes a nuclear protein that participates in DNA damage response

The protozoan parasite Leishmania presents a dynamic and plastic genome in which gene amplification and chromosome translocations are common phenomena. Such plasticity hints at the necessity of dependable genome maintenance pathways. Eukaryotic cells have evolved checkpoint control systems that recognize altered DNA structures and halt cell cycle progression allowing DNA repair to take place. In these cells, the PCNA-related heterotrimeric complex formed by the proteins Hus1, Rad9, and Rad1 is known to participate in the early steps of replicative stress sensing and signaling. Here we show that the Hus1 homolog of Leishmania major is a nuclear protein that improves the cell capability to cope with replicative stress. Overexpression of LmHus1 confers resistance to the genotoxic drugs hydroxyurea (HU) and methyl methanesulfonate (MMS) and resistance to HU correlates to reduced net DNA damage upon LmHus1 expression. (C) 2011 Elsevier B.V. All rights reserved.

Lower Extremities Magnetic Resonance Angiography With Blood Pressure Cuff Compression: Quantitative Dynamic Analysis

Purpose: To quantitatively evaluate changes induced by the application of a femoral blood-pressure cuff (BPC) on run-off magnetic resonance angiography (MRA). which is a method generally previously proposed to reduce venous contamination in the leg. Materials and Methods: This study was Health Insurance Portability and Accountability Act (HIPAA)- and Institutional Review Board (IRB)-compliant, We used time-resolved gradient-echo gadolinium (Gd)-enhanced MRA to measure BPC effects on arterial, venous, and soft-tissue enhancement. Seven healthy volunteers (six men) were studied with the BPC applied at the mid-femoral level unilaterally using a 1.5T MR system after intravenous injection of Gd-BOPTA. Different statistical tools were used such as the Wilcoxon signed rank test and a cubic smoothing spline fit. Results: We found that BPC application induces delayed venous filling (as previously described), but also induces significant decreases in arterial inflow, arterial enhancement, vascular-soft tissue contrast, and delayed peak enhancement (which have not been previously measured). Conclusion: The potential benefits from using a BPC for run-off MRA must be balanced against the potential pitfalls, elucidated by our findings.

Age does not influence the bone response to treadmill exercise in female rats

Purpose: Because it is believed that bone may respond to exercise differently at different ages, we compared bone responses in immature and mature rats after 12 wk of treadmill running. Methods: Twenty-two immature (5-wk-old) and 21 mature (17-wk-old) female Sprague Dawley rats were randomized into a running (trained, N = 10 immature, 9 mature) or a control group (controls, N 12 immature, 12 mature) before sacrifice 12 wk later. Rats ran on a treadmill five times per week for 60-70 min at speeds up to 26 m.min(-1). Both at baseline and after intervention, we measured total body, lumbar spine, and proximal femoral bone mineral, as well as total body soft tissue composition using dual-energy x-ray absorptiometry (DXA) in vivo. After sacrificing the animals, we measured dynamic and static histomorphometry and three-point bending strength of the tibia. Results: Running training was associated with greater differences in tibial subperiosteal area, cortical cross-sectional area, peak load, stiffness, and moment of inertia in immature and mature rats (P < 0.05). The trained rats had greater periosteal bone formation rates (P < 0.01) than controls, but there was no difference in tibial trabecular bone histomorphometry. Similar running-related gains were seen in DXA lumbar spine area (P = 0.04) and bone mineral content (BMC; P = 0.03) at both ages. For total body bone area and BMC, the immature trained group increased significantly compared with controls (P < 0.05), whereas the mature trained group gained less than did controls (P < 0.01). Conclusion: In this in vivo model, where a similar physical training program was performed by immature and mature female rats, we demonstrated that both age groups were sensitive to loading and that bone strength gains appeared to result more from changes in bone geometry than from improved material properties.

Enhanced short wavelength response in laser-scanned-photodiode image sensor using an a-SiC : H/a-Si : H tandem structure

We report in this paper the recent advances we obtained in optimizing a color image sensor based on the laser-scanned-photodiode (LSP) technique. A novel device structure based on a a-SiC:H/a-Si:H pin/pin tandem structure has been tested for a proper color separation process that takes advantage on the different filtering properties due to the different light penetration depth at different wavelengths a-SM and a-SiC:H. While the green and the red images give, in comparison with previous tested structures, a weak response, this structure shows a very good recognition of blue color under reverse bias, leaving a good margin for future device optimization in order to achieve a complete and satisfactory RGB image mapping. Experimental results about the spectral collection efficiency are presented and discussed from the point of view of the color sensor applications. The physics behind the device functioning is explained by recurring to a numerical simulation of the internal electrical configuration of the device.

Large area image sensing structures based on a-SiC : H: a dynamic characterization

In recent works large area hydrogenated amorphous silicon p-i-n structures with low conductivity doped layers were proposed as single element image sensors. The working principle of this type of sensor is based on the modulation, by the local illumination conditions, of the photocurrent generated by a light beam scanning the active area of the device. In order to evaluate the sensor capabilities is necessary to perform a response time characterization. This work focuses on the transient response of such sensor and on the influence of the carbon contents of the doped layers. In order to evaluate the response time a set of devices with different percentage of carbon incorporation in the doped layers is analyzed by measuring the scanner-induced photocurrent under different bias conditions.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.