Spatial and temporal optimization in habitat placement for a threatened plant: the case of the western prairie fringed orchid

Treesearch

John Hof; Carolyn Hull Sieg; Michael Bevers

1999-01-01

This paper investigates an optimization approach to determining the placement and timing of habitat protection for the western prairie fringed orchid. This plant’s population dynamics are complex, creating a challenging optimization problem. The sensitivity of the orchid to random climate conditions is handled probabilistically. The plant’s seed, protocorm and above-...

Optimal control of multiplicative control systems arising from cancer therapy

NASA Technical Reports Server (NTRS)

Bahrami, K.; Kim, M.

1975-01-01

This study deals with ways of curtailing the rapid growth of cancer cell populations. The performance functional that measures the size of the population at the terminal time as well as the control effort is devised. With use of the discrete maximum principle, the Hamiltonian for this problem is determined and the condition for optimal solutions are developed. The optimal strategy is shown to be a bang-bang control. It is shown that the optimal control for this problem must be on the vertices of an N-dimensional cube contained in the N-dimensional Euclidean space. An algorithm for obtaining a local minimum of the performance function in an orderly fashion is developed. Application of the algorithm to the design of antitumor drug and X-irradiation schedule is discussed.

Constituents of Quality of Life and Urban Size

ERIC Educational Resources Information Center

Royuela, Vicente; Surinach, Jordi

2005-01-01

Do cities have an optimal size? In seeking to answer this question, various theories, including Optimal City Size Theory, the supply-oriented dynamic approach and the city network paradigm, have been forwarded that considered a city's population size as a determinant of location costs and benefits. However, the generalised growth in wealth that…

Collective influence in evolutionary social dilemmas

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2016-03-01

When evolutionary games are contested in structured populations, the degree of each player in the network plays an important role. If they exist, hubs often determine the fate of the population in remarkable ways. Recent research based on optimal percolation in random networks has shown, however, that the degree is neither the sole nor the best predictor of influence in complex networks. Low-degree nodes may also be optimal influencers if they are hierarchically linked to hubs. Taking this into account leads to the formalism of collective influence in complex networks, which as we show here, has far-reaching implications for the favorable resolution of social dilemmas. In particular, there exists an optimal hierarchical depth for the determination of collective influence that we use to describe the potency of players for passing their strategies, which depends on the strength of the social dilemma. Interestingly, the degree, which corresponds to the baseline depth zero, is optimal only when the temptation to defect is small. Our research reveals that evolutionary success stories are related to spreading processes which are rooted in favorable hierarchical structures that extend beyond local neighborhoods.

[Optimal cut-point of salivary cotinine concentration to discriminate smoking status in the adult population in Barcelona].

PubMed

Martínez-Sánchez, Jose M; Fu, Marcela; Ariza, Carles; López, María J; Saltó, Esteve; Pascual, José A; Schiaffino, Anna; Borràs, Josep M; Peris, Mercè; Agudo, Antonio; Nebot, Manel; Fernández, Esteve

2009-01-01

To assess the optimal cut-point for salivary cotinine concentration to identify smoking status in the adult population of Barcelona. We performed a cross-sectional study of a representative sample (n=1,117) of the adult population (>16 years) in Barcelona (2004-2005). This study gathered information on active and passive smoking by means of a questionnaire and a saliva sample for cotinine determination. We analyzed sensitivity and specificity according to sex, age, smoking status (daily and occasional), and exposure to second-hand smoke at home. ROC curves and the area under the curve were calculated. The prevalence of smokers (daily and occasional) was 27.8% (95% CI: 25.2-30.4%). The optimal cut-point to discriminate smoking status was 9.2 ng/ml (sensitivity=88.7% and specificity=89.0%). The area under the ROC curve was 0.952. The optimal cut-point was 12.2 ng/ml in men and 7.6 ng/ml in women. The optimal cut-point was higher at ages with a greater prevalence of smoking. Daily smokers had a higher cut-point than occasional smokers. The optimal cut-point to discriminate smoking status in the adult population is 9.2 ng/ml, with sensitivities and specificities around 90%. The cut-point was higher in men and in younger people. The cut-point increases with higher prevalence of daily smokers.

Automatic genetic optimization approach to two-dimensional blade profile design for steam turbines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trigg, M.A.; Tubby, G.R.; Sheard, A.G.

1999-01-01

In this paper a systematic approach to the optimization of two-dimensional blade profiles is presented. A genetic optimizer has been developed that modifies the blade profile and calculates its profile loss. This process is automatic, producing profile designs significantly faster and with significantly lower loss than has previously been possible. The optimizer developed uses a genetic algorithm to optimize a two-dimensional profile, defined using 17 parameters, for minimum loss with a given flow condition. The optimizer works with a population of two-dimensional profiles with varied parameters. A CFD mesh is generated for each profile, and the result is analyzed usingmore » a two-dimensional blade-to-blade solver, written for steady viscous compressible flow, to determine profile loss. The loss is used as the measure of a profile`s fitness. The optimizer uses this information to select the members of the next population, applying crossovers, mutations, and elitism in the process. Using this method, the optimizer tends toward the best values for the parameters defining the profile with minimum loss.« less

Hemodynamic guidelines for design and control of a turbodynamic pediatric ventricular assist device.

PubMed

Uber, Bronwyn E; Webber, Steven A; Morell, Victor O; Antaki, James F

2006-01-01

The design of mechanical circulatory support devices typically requires a priori knowledge of the hemodynamic requirements of their intended use. These requirements are difficult to determine because of limited clinical experience. This is especially true for the pediatric population, for whom there is a dearth of longitudinal data. This report aims to provide both engineers and physicians with benchmarks for determining the optimal flow requirements and settings for pediatric ventricular assist devices that are currently being developed. Criteria were developed on the basis of estimates derived from various sources. The potential patient population was estimated by using the prevalence of children on the heart transplant waiting list and those placed on extracorporeal membrane oxygenation. Cardiac outputs were determined for individual weights and body surface areas, using published values for healthy and sick pediatric patients. The recommended pump range was optimized to include the most patients, while considering the design constraints. This study identifies a significant population of patients who would benefit from a device providing 0.52 to 1.92 l/min.

Adaptive non-linear control for cancer therapy through a Fokker-Planck observer.

PubMed

Shakeri, Ehsan; Latif-Shabgahi, Gholamreza; Esmaeili Abharian, Amir

2018-04-01

In recent years, many efforts have been made to present optimal strategies for cancer therapy through the mathematical modelling of tumour-cell population dynamics and optimal control theory. In many cases, therapy effect is included in the drift term of the stochastic Gompertz model. By fitting the model with empirical data, the parameters of therapy function are estimated. The reported research works have not presented any algorithm to determine the optimal parameters of therapy function. In this study, a logarithmic therapy function is entered in the drift term of the Gompertz model. Using the proposed control algorithm, the therapy function parameters are predicted and adaptively adjusted. To control the growth of tumour-cell population, its moments must be manipulated. This study employs the probability density function (PDF) control approach because of its ability to control all the process moments. A Fokker-Planck-based non-linear stochastic observer will be used to determine the PDF of the process. A cost function based on the difference between a predefined desired PDF and PDF of tumour-cell population is defined. Using the proposed algorithm, the therapy function parameters are adjusted in such a manner that the cost function is minimised. The existence of an optimal therapy function is also proved. The numerical results are finally given to demonstrate the effectiveness of the proposed method.

Optimal sampling theory and population modelling - Application to determination of the influence of the microgravity environment on drug distribution and elimination

NASA Technical Reports Server (NTRS)

Drusano, George L.

1991-01-01

The optimal sampling theory is evaluated in applications to studies related to the distribution and elimination of several drugs (including ceftazidime, piperacillin, and ciprofloxacin), using the SAMPLE module of the ADAPT II package of programs developed by D'Argenio and Schumitzky (1979, 1988) and comparing the pharmacokinetic parameter values with results obtained by traditional ten-sample design. The impact of the use of optimal sampling was demonstrated in conjunction with NONMEM (Sheiner et al., 1977) approach, in which the population is taken as the unit of analysis, allowing even fragmentary patient data sets to contribute to population parameter estimates. It is shown that this technique is applicable in both the single-dose and the multiple-dose environments. The ability to study real patients made it possible to show that there was a bimodal distribution in ciprofloxacin nonrenal clearance.

Modelling optimal location for pre-hospital helicopter emergency medical services.

PubMed

Schuurman, Nadine; Bell, Nathaniel J; L'Heureux, Randy; Hameed, Syed M

2009-05-09

Increasing the range and scope of early activation/auto launch helicopter emergency medical services (HEMS) may alleviate unnecessary injury mortality that disproportionately affects rural populations. To date, attempts to develop a quantitative framework for the optimal location of HEMS facilities have been absent. Our analysis used five years of critical care data from tertiary health care facilities, spatial data on origin of transport and accurate road travel time catchments for tertiary centres. A location optimization model was developed to identify where the expansion of HEMS would cover the greatest population among those currently underserved. The protocol was developed using geographic information systems (GIS) to measure populations, distances and accessibility to services. Our model determined Royal Inland Hospital (RIH) was the optimal site for an expanded HEMS - based on denominator population, distance to services and historical usage patterns. GIS based protocols for location of emergency medical resources can provide supportive evidence for allocation decisions - especially when resources are limited. In this study, we were able to demonstrate conclusively that a logical choice exists for location of additional HEMS. This protocol could be extended to location analysis for other emergency and health services.

HIV epidemic control-a model for optimal allocation of prevention and treatment resources.

PubMed

Alistar, Sabina S; Long, Elisa F; Brandeau, Margaret L; Beck, Eduard J

2014-06-01

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.

Optimal cut-off of homeostasis model assessment of insulin resistance (HOMA-IR) for the diagnosis of metabolic syndrome: third national surveillance of risk factors of non-communicable diseases in Iran (SuRFNCD-2007).

PubMed

Esteghamati, Alireza; Ashraf, Haleh; Khalilzadeh, Omid; Zandieh, Ali; Nakhjavani, Manouchehr; Rashidi, Armin; Haghazali, Mehrdad; Asgari, Fereshteh

2010-04-07

We have recently determined the optimal cut-off of the homeostatic model assessment of insulin resistance for the diagnosis of insulin resistance (IR) and metabolic syndrome (MetS) in non-diabetic residents of Tehran, the capital of Iran. The aim of the present study is to establish the optimal cut-off at the national level in the Iranian population with and without diabetes. Data of the third National Surveillance of Risk Factors of Non-Communicable Diseases, available for 3,071 adult Iranian individuals aging 25-64 years were analyzed. MetS was defined according to the Adult Treatment Panel III (ATPIII) and International Diabetes Federation (IDF) criteria. HOMA-IR cut-offs from the 50th to the 95th percentile were calculated and sensitivity, specificity, and positive likelihood ratio for MetS diagnosis were determined. The receiver operating characteristic (ROC) curves of HOMA-IR for MetS diagnosis were depicted, and the optimal cut-offs were determined by two different methods: Youden index, and the shortest distance from the top left corner of the curve. The area under the curve (AUC) (95%CI) was 0.650 (0.631-0.670) for IDF-defined MetS and 0.683 (0.664-0.703) with the ATPIII definition. The optimal HOMA-IR cut-off for the diagnosis of IDF- and ATPIII-defined MetS in non-diabetic individuals was 1.775 (sensitivity: 57.3%, specificity: 65.3%, with ATPIII; sensitivity: 55.9%, specificity: 64.7%, with IDF). The optimal cut-offs in diabetic individuals were 3.875 (sensitivity: 49.7%, specificity: 69.6%) and 4.325 (sensitivity: 45.4%, specificity: 69.0%) for ATPIII- and IDF-defined MetS, respectively. We determined the optimal HOMA-IR cut-off points for the diagnosis of MetS in the Iranian population with and without diabetes.

Data-driven optimal binning for respiratory motion management in PET.

PubMed

Kesner, Adam L; Meier, Joseph G; Burckhardt, Darrell D; Schwartz, Jazmin; Lynch, David A

2018-01-01

Respiratory gating has been used in PET imaging to reduce the amount of image blurring caused by patient motion. Optimal binning is an approach for using the motion-characterized data by binning it into a single, easy to understand/use, optimal bin. To date, optimal binning protocols have utilized externally driven motion characterization strategies that have been tuned with population-derived assumptions and parameters. In this work, we are proposing a new strategy with which to characterize motion directly from a patient's gated scan, and use that signal to create a patient/instance-specific optimal bin image. Two hundred and nineteen phase-gated FDG PET scans, acquired using data-driven gating as described previously, were used as the input for this study. For each scan, a phase-amplitude motion characterization was generated and normalized using principle component analysis. A patient-specific "optimal bin" window was derived using this characterization, via methods that mirror traditional optimal window binning strategies. The resulting optimal bin images were validated by correlating quantitative and qualitative measurements in the population of PET scans. In 53% (n = 115) of the image population, the optimal bin was determined to include 100% of the image statistics. In the remaining images, the optimal binning windows averaged 60% of the statistics and ranged between 20% and 90%. Tuning the algorithm, through a single acceptance window parameter, allowed for adjustments of the algorithm's performance in the population toward conservation of motion or reduced noise-enabling users to incorporate their definition of optimal. In the population of images that were deemed appropriate for segregation, average lesion SUV max were 7.9, 8.5, and 9.0 for nongated images, optimal bin, and gated images, respectively. The Pearson correlation of FWHM measurements between optimal bin images and gated images were better than with nongated images, 0.89 and 0.85, respectively. Generally, optimal bin images had better resolution than the nongated images and better noise characteristics than the gated images. We extended the concept of optimal binning to a data-driven form, updating a traditionally one-size-fits-all approach to a conformal one that supports adaptive imaging. This automated strategy was implemented easily within a large population and encapsulated motion information in an easy to use 3D image. Its simplicity and practicality may make this, or similar approaches ideal for use in clinical settings. © 2017 American Association of Physicists in Medicine.

Determining Optimal College Locations

ERIC Educational Resources Information Center

Schofer, J. P.

1975-01-01

Location can be a critical determinant of the success of a college. Central Place Theory, as developed in geographic studies of population distribution patterns, can provide insights into the problem of evaluating college locations. In this way preferences of students can be balanced against economic, academic, and political considerations.…

Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4.

PubMed

Bouillon-Pichault, Marion; Jullien, Vincent; Bazzoli, Caroline; Pons, Gérard; Tod, Michel

2011-02-01

The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.

Determination of optimal parameters for dual-layer cathode of polymer electrolyte fuel cell using computational intelligence-aided design.

PubMed

Chen, Yi; Huang, Weina; Peng, Bei

2014-01-01

Because of the demands for sustainable and renewable energy, fuel cells have become increasingly popular, particularly the polymer electrolyte fuel cell (PEFC). Among the various components, the cathode plays a key role in the operation of a PEFC. In this study, a quantitative dual-layer cathode model was proposed for determining the optimal parameters that minimize the over-potential difference η and improve the efficiency using a newly developed bat swarm algorithm with a variable population embedded in the computational intelligence-aided design. The simulation results were in agreement with previously reported results, suggesting that the proposed technique has potential applications for automating and optimizing the design of PEFCs.

Programmed Evolution for Optimization of Orthogonal Metabolic Output in Bacteria

PubMed Central

Eckdahl, Todd T.; Campbell, A. Malcolm; Heyer, Laurie J.; Poet, Jeffrey L.; Blauch, David N.; Snyder, Nicole L.; Atchley, Dustin T.; Baker, Erich J.; Brown, Micah; Brunner, Elizabeth C.; Callen, Sean A.; Campbell, Jesse S.; Carr, Caleb J.; Carr, David R.; Chadinha, Spencer A.; Chester, Grace I.; Chester, Josh; Clarkson, Ben R.; Cochran, Kelly E.; Doherty, Shannon E.; Doyle, Catherine; Dwyer, Sarah; Edlin, Linnea M.; Evans, Rebecca A.; Fluharty, Taylor; Frederick, Janna; Galeota-Sprung, Jonah; Gammon, Betsy L.; Grieshaber, Brandon; Gronniger, Jessica; Gutteridge, Katelyn; Henningsen, Joel; Isom, Bradley; Itell, Hannah L.; Keffeler, Erica C.; Lantz, Andrew J.; Lim, Jonathan N.; McGuire, Erin P.; Moore, Alexander K.; Morton, Jerrad; Nakano, Meredith; Pearson, Sara A.; Perkins, Virginia; Parrish, Phoebe; Pierson, Claire E.; Polpityaarachchige, Sachith; Quaney, Michael J.; Slattery, Abagael; Smith, Kathryn E.; Spell, Jackson; Spencer, Morgan; Taye, Telavive; Trueblood, Kamay; Vrana, Caroline J.; Whitesides, E. Tucker

2015-01-01

Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields – evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation. PMID:25714374

Programmed evolution for optimization of orthogonal metabolic output in bacteria.

PubMed

Eckdahl, Todd T; Campbell, A Malcolm; Heyer, Laurie J; Poet, Jeffrey L; Blauch, David N; Snyder, Nicole L; Atchley, Dustin T; Baker, Erich J; Brown, Micah; Brunner, Elizabeth C; Callen, Sean A; Campbell, Jesse S; Carr, Caleb J; Carr, David R; Chadinha, Spencer A; Chester, Grace I; Chester, Josh; Clarkson, Ben R; Cochran, Kelly E; Doherty, Shannon E; Doyle, Catherine; Dwyer, Sarah; Edlin, Linnea M; Evans, Rebecca A; Fluharty, Taylor; Frederick, Janna; Galeota-Sprung, Jonah; Gammon, Betsy L; Grieshaber, Brandon; Gronniger, Jessica; Gutteridge, Katelyn; Henningsen, Joel; Isom, Bradley; Itell, Hannah L; Keffeler, Erica C; Lantz, Andrew J; Lim, Jonathan N; McGuire, Erin P; Moore, Alexander K; Morton, Jerrad; Nakano, Meredith; Pearson, Sara A; Perkins, Virginia; Parrish, Phoebe; Pierson, Claire E; Polpityaarachchige, Sachith; Quaney, Michael J; Slattery, Abagael; Smith, Kathryn E; Spell, Jackson; Spencer, Morgan; Taye, Telavive; Trueblood, Kamay; Vrana, Caroline J; Whitesides, E Tucker

2015-01-01

Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields - evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation.

Optimal timing of oral fosfomycin administration for pre-prostate biopsy prophylaxis.

PubMed

Rhodes, Nathaniel J; Gardiner, Bradley J; Neely, Michael N; Grayson, M Lindsay; Ellis, Andrew G; Lawrentschuk, Nathan; Frauman, Albert G; Maxwell, Kelly M; Zembower, Teresa R; Scheetz, Marc H

2015-07-01

As the optimal administration time for fosfomycin peri-procedural prophylaxis is unclear, we sought to determine optimal administration times for fosfomycin peri-procedural prophylaxis. Plasma, peripheral zone and transition zone fosfomycin concentrations were obtained from 26 subjects undergoing transurethral resection of the prostate (TURP), following a single oral dose of 3 g of fosfomycin. Population pharmacokinetic modelling was completed with the Nonparametric Adaptive Grid (NPAG) algorithm (Pmetrics package for R), with a four-compartment model. Plasma and tissue concentrations were simulated during the first 24 h post-dose, comparing these with EUCAST susceptibility breakpoints for Escherichia coli, a common uropathogen. Non-compartmental-determined pharmacokinetic values in our population were similar to those reported in the package insert. Predicted plasma concentrations rapidly increased after the first hour, giving more than 90% population coverage for organisms with an MIC ≤4 mg/L over the first 12 h post-dose. Organisms with higher MICs fared much worse, with organisms at the EUCAST breakpoint being covered for <10% of the population at any time. Transitional zone prostate concentrations exceeded 4 mg/L for 90% of the population between hours 1 and 9. Peripheral zone prostate concentrations were much lower and only exceeded 4 mg/L for 70% of the population between hours 1 and 4. Until more precise plasma and tissue data are available, we recommend that fosfomycin prophylaxis be given 1-4 h prior to prostate biopsy. We do not recommend fosfomycin prophylaxis for subjects with known organisms with MICs >4 mg/L. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Determination of the optimal sample size for a clinical trial accounting for the population size.

PubMed

Stallard, Nigel; Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

2017-07-01

The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal sampling strategies for detecting zoonotic disease epidemics.

PubMed

Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W

2014-06-01

The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.

SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boutilier, J; Chan, T; Lee, T

2014-06-15

Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the leftmore » femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time.« less

Wildlife Conservation Planning Using Stochastic Optimization and Importance Sampling

Treesearch

Robert G. Haight; Laurel E. Travis

1997-01-01

Formulations for determining conservation plans for sensitive wildlife species must account for economic costs of habitat protection and uncertainties about how wildlife populations will respond. This paper describes such a formulation and addresses the computational challenge of solving it. The problem is to determine the cost-efficient level of habitat protection...

Determination of Optimal Parameters for Dual-Layer Cathode of Polymer Electrolyte Fuel Cell Using Computational Intelligence-Aided Design

PubMed Central

Chen, Yi; Huang, Weina; Peng, Bei

2014-01-01

Because of the demands for sustainable and renewable energy, fuel cells have become increasingly popular, particularly the polymer electrolyte fuel cell (PEFC). Among the various components, the cathode plays a key role in the operation of a PEFC. In this study, a quantitative dual-layer cathode model was proposed for determining the optimal parameters that minimize the over-potential difference and improve the efficiency using a newly developed bat swarm algorithm with a variable population embedded in the computational intelligence-aided design. The simulation results were in agreement with previously reported results, suggesting that the proposed technique has potential applications for automating and optimizing the design of PEFCs. PMID:25490761

Vitamin D Status in South Asian Populations - Risks and Opportunities.

PubMed

Akhtar, Saeed

2016-08-17

Human body acquires a significant amount of vitamin D by cutaneous synthesis under the action of sunlight and less is supplied through nutritional sources. Diversified sociocultural and economic determinants have been identified that limit the dietary intake of vitamin D and enough distribution of sunlight to maintain optimal levels of 25-hydroxyvitamin D (25(OH)D). Consequently, the world has witnessed a high prevalence of hypovitaminosis D in resource-limited South Asian countries. The purpose of this review is to provide a South Asian perspective of vitamin D status, critically examining India, Pakistan, Bangladesh, and Sri Lanka, and to shed light on potential determinants (latitude and season, sunshine exposure habits, age, gender, and genetic factors) leading to hypovitaminosis D among a variety of population groups. Literature search was carried out using bibliographic databases "PubMed," "Google Scholar," and "ScienceDirect.com." Serum 25(OH)D level, 20-50 nmol/L, was mainly taken as vitamin D deficiency, and determinants of low serum 25(OH)D concentration of the population under study were also considered. The review concludes that vitamin D deficiency is highly prevalent among South Asian populations and global efforts are needed to overcome hypovitaminosis in the region. In addition, dietary diversification, supplementation and fortification of foods with vitamin D, adequate exposure to sunlight, and consumption of animal foods were suggested as viable approaches to maintain 25(OH)D levels for optimal health.

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

Optimal harvesting policy of predator-prey model with free fishing and reserve zones

NASA Astrophysics Data System (ADS)

Toaha, Syamsuddin; Rustam

2017-03-01

The present paper deals with an optimal harvesting of predator-prey model in an ecosystem that consists of two zones, namely the free fishing and prohibited zones. The dynamics of prey population in the ecosystem can migrate from the free fishing to the prohibited zone and vice versa. The predator and prey populations in the free fishing zone are then harvested with constant efforts. The existence of the interior equilibrium point is analyzed and its stability is determined using Routh-Hurwitz stability test. The stable interior equilibrium point is then related to the problem of maximum profit and the problem of present value of net revenue. We follow the Pontryagin's maximal principle to get the optimal harvesting policy of the present value of the net revenue. From the analysis, we found a critical point of the efforts that makes maximum profit. There also exists certain conditions of the efforts that makes the present value of net revenue becomes maximal. In addition, the interior equilibrium point is locally asymptotically stable which means that the optimal harvesting is reached and the unharvested prey, harvested prey, and harvested predator populations remain sustainable. Numerical examples are given to verify the analytical results.

Population Pharmacokinetics and Optimal Sampling Strategy for Model-Based Precision Dosing of Melphalan in Patients Undergoing Hematopoietic Stem Cell Transplantation.

PubMed

Mizuno, Kana; Dong, Min; Fukuda, Tsuyoshi; Chandra, Sharat; Mehta, Parinda A; McConnell, Scott; Anaissie, Elias J; Vinks, Alexander A

2018-05-01

High-dose melphalan is an important component of conditioning regimens for patients undergoing hematopoietic stem cell transplantation. The current dosing strategy based on body surface area results in a high incidence of oral mucositis and gastrointestinal and liver toxicity. Pharmacokinetically guided dosing will individualize exposure and help minimize overexposure-related toxicity. The purpose of this study was to develop a population pharmacokinetic model and optimal sampling strategy. A population pharmacokinetic model was developed with NONMEM using 98 observations collected from 15 adult patients given the standard dose of 140 or 200 mg/m 2 by intravenous infusion. The determinant-optimal sampling strategy was explored with PopED software. Individual area under the curve estimates were generated by Bayesian estimation using full and the proposed sparse sampling data. The predictive performance of the optimal sampling strategy was evaluated based on bias and precision estimates. The feasibility of the optimal sampling strategy was tested using pharmacokinetic data from five pediatric patients. A two-compartment model best described the data. The final model included body weight and creatinine clearance as predictors of clearance. The determinant-optimal sampling strategies (and windows) were identified at 0.08 (0.08-0.19), 0.61 (0.33-0.90), 2.0 (1.3-2.7), and 4.0 (3.6-4.0) h post-infusion. An excellent correlation was observed between area under the curve estimates obtained with the full and the proposed four-sample strategy (R 2  = 0.98; p < 0.01) with a mean bias of -2.2% and precision of 9.4%. A similar relationship was observed in children (R 2  = 0.99; p < 0.01). The developed pharmacokinetic model-based sparse sampling strategy promises to achieve the target area under the curve as part of precision dosing.

Quantifying the Role of Population Subdivision in Evolution on Rugged Fitness Landscapes

PubMed Central

Bitbol, Anne-Florence; Schwab, David J.

2014-01-01

Natural selection drives populations towards higher fitness, but crossing fitness valleys or plateaus may facilitate progress up a rugged fitness landscape involving epistasis. We investigate quantitatively the effect of subdividing an asexual population on the time it takes to cross a fitness valley or plateau. We focus on a generic and minimal model that includes only population subdivision into equivalent demes connected by global migration, and does not require significant size changes of the demes, environmental heterogeneity or specific geographic structure. We determine the optimal speedup of valley or plateau crossing that can be gained by subdivision, if the process is driven by the deme that crosses fastest. We show that isolated demes have to be in the sequential fixation regime for subdivision to significantly accelerate crossing. Using Markov chain theory, we obtain analytical expressions for the conditions under which optimal speedup is achieved: valley or plateau crossing by the subdivided population is then as fast as that of its fastest deme. We verify our analytical predictions through stochastic simulations. We demonstrate that subdivision can substantially accelerate the crossing of fitness valleys and plateaus in a wide range of parameters extending beyond the optimal window. We study the effect of varying the degree of subdivision of a population, and investigate the trade-off between the magnitude of the optimal speedup and the width of the parameter range over which it occurs. Our results, obtained for fitness valleys and plateaus, also hold for weakly beneficial intermediate mutations. Finally, we extend our work to the case of a population connected by migration to one or several smaller islands. Our results demonstrate that subdivision with migration alone can significantly accelerate the crossing of fitness valleys and plateaus, and shed light onto the quantitative conditions necessary for this to occur. PMID:25122220

Population pharmacokinetics of phenytoin after intravenous administration of fosphenytoin sodium in pediatric patients, adult patients, and healthy volunteers.

PubMed

Tanaka, Jun; Kasai, Hidefumi; Shimizu, Kenji; Shimasaki, Shigeki; Kumagai, Yuji

2013-03-01

We performed a population pharmacokinetic analysis of phenytoin after intravenous administration of fosphenytoin sodium in healthy, neurosurgical, and epileptic subjects, including pediatric patients, and determined the optimal dose and infusion rate for achieving the therapeutic range. We used pooled data obtained from two phase I studies and one phase III study performed in Japan. The population pharmacokinetic analysis was performed using NONMEM software. The optimal dose and infusion rate were determined using simulation results obtained using the final model. The therapeutic range for total plasma phenytoin concentration is 10-20 μg/mL. We used a linear two-compartment model with conversion of fosphenytoin to phenytoin. Pharmacokinetic parameters of phenytoin, such as total clearance and central and peripheral volume of distribution were influenced by body weight. The dose simulations are as follows. In adult patients, the optimal dose and infusion rate of phenytoin for achieving the therapeutic range was 22.5 mg/kg and 3 mg/kg/min respectively. In pediatric patients, the total plasma concentration of phenytoin was within the therapeutic range for a shorter duration than that in adult patients at 22.5 mg/kg (3 mg/kg/min). However, many pediatric patients showed phenytoin concentration within the toxic range after administration of a dose of 30 mg/kg. The pharmacokinetics of phenytoin after intravenous administration of fosphenytoin sodium could be described using a linear two-compartment model. The administration of fosphenytoin sodium 22.5 mg/kg at an infusion rate of 3 mg/kg/min was optimal for achieving the desired plasma phenytoin concentration.

Analysis of multidimensional difference-of-Gaussians filters in terms of directly observable parameters.

PubMed

Cope, Davis; Blakeslee, Barbara; McCourt, Mark E

2013-05-01

The difference-of-Gaussians (DOG) filter is a widely used model for the receptive field of neurons in the retina and lateral geniculate nucleus (LGN) and is a potential model in general for responses modulated by an excitatory center with an inhibitory surrounding region. A DOG filter is defined by three standard parameters: the center and surround sigmas (which define the variance of the radially symmetric Gaussians) and the balance (which defines the linear combination of the two Gaussians). These parameters are not directly observable and are typically determined by nonlinear parameter estimation methods applied to the frequency response function. DOG filters show both low-pass (optimal response at zero frequency) and bandpass (optimal response at a nonzero frequency) behavior. This paper reformulates the DOG filter in terms of a directly observable parameter, the zero-crossing radius, and two new (but not directly observable) parameters. In the two-dimensional parameter space, the exact region corresponding to bandpass behavior is determined. A detailed description of the frequency response characteristics of the DOG filter is obtained. It is also found that the directly observable optimal frequency and optimal gain (the ratio of the response at optimal frequency to the response at zero frequency) provide an alternate coordinate system for the bandpass region. Altogether, the DOG filter and its three standard implicit parameters can be determined by three directly observable values. The two-dimensional bandpass region is a potential tool for the analysis of populations of DOG filters (for example, populations of neurons in the retina or LGN), because the clustering of points in this parameter space may indicate an underlying organizational principle. This paper concentrates on circular Gaussians, but the results generalize to multidimensional radially symmetric Gaussians and are given as an appendix.

Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

PubMed

Pozzobon, Victor; Perre, Patrick

2018-01-21

This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.

NIH mouse study finds gut microorganisms may determine cancer treatment outcome

Cancer.gov

An intact gut commensal microbiota, which is a population of microorganisms living in the intestine, is required for optimal response to cancer therapy, according to a mouse study by scientists at the National Cancer Institute (NCI)

Optimal waist circumference cut-off values for predicting cardiovascular risk factors in a multi-ethnic Malaysian population.

PubMed

Cheong, Kee C; Ghazali, Sumarni M; Hock, Lim K; Yusoff, Ahmad F; Selvarajah, Sharmini; Haniff, Jamaiyah; Zainuddin, Ahmad Ali; Ying, Chan Y; Lin, Khor G; Rahman, Jamalludin A; Shahar, Suzana; Mustafa, Amal N

2014-01-01

Previous studies have proposed the lower waist circumference (WC) cutoffs be used for defining abdominal obesity in Asian populations. To determine the optimal cut-offs of waist circumference (WC) in predicting cardiovascular (CV) risk factors in the multi-ethnic Malaysian population. We analysed data from 32,703 respondents (14,980 men and 17,723 women) aged 18 years and above who participated in the Third National Health and Morbidity Survey in 2006. Gender-specific logistic regression analyses were used to examine associations between WC and three CV risk factors (diabetes mellitus, hypertension, and hypercholesterolemia). The Receiver Operating Characteristic (ROC) curves were used to determine the cut-off values of WC with optimum sensitivity and specificity for detecting these CV risk factors. The odds ratio for having diabetes mellitus, hypertension, and hypercholesterolemia, or at least one of these risks, increased significantly as the WC cut-off point increased. Optimal WC cut-off values for predicting the presence of diabetes mellitus, hypertension, hypercholesterolemia and at least one of the three CV risk factors varied from 81.4 to 85.5 cm for men and 79.8 to 80.7 cm for women. Our findings indicate that WC cut-offs of 81 cm for men and 80 cm for women are appropriate for defining abdominal obesity and for recommendation to undergo cardiovascular risk screening and weight management in the Malaysian adult population. © 2014 Asian Oceanian Association for the Study of Obesity . Published by Elsevier Ltd. All rights reserved.

Chinese version of the Optimism and Pessimism Scale: Psychometric properties in mainland China and development of a short form.

PubMed

Xia, Jie; Wu, Daxing; Zhang, Jibiao; Xu, Yuanchao; Xu, Yunxuan

2016-06-01

This study aimed to validate the Chinese version of the Optimism and Pessimism Scale in a sample of 730 adult Chinese individuals. Confirmatory factor analyses confirmed the bidimensionality of the scale with two factors, optimism and pessimism. The total scale and optimism and pessimism factors demonstrated satisfactory reliability and validity. Population-based normative data and mean values for gender, age, and education were determined. Furthermore, we developed a 20-item short form of the Chinese version of the Optimism and Pessimism Scale with structural validity comparable to the full form. In summary, the Chinese version of the Optimism and Pessimism Scale is an appropriate and practical tool for epidemiological research in mainland China. © The Author(s) 2014.

Study of a mixed dispersal population dynamics model

DOE PAGES

Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; ...

2016-08-27

In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to diemore » out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.« less

A Novel Space Partitioning Algorithm to Improve Current Practices in Facility Placement

PubMed Central

Jimenez, Tamara; Mikler, Armin R; Tiwari, Chetan

2012-01-01

In the presence of naturally occurring and man-made public health threats, the feasibility of regional bio-emergency contingency plans plays a crucial role in the mitigation of such emergencies. While the analysis of in-place response scenarios provides a measure of quality for a given plan, it involves human judgment to identify improvements in plans that are otherwise likely to fail. Since resource constraints and government mandates limit the availability of service provided in case of an emergency, computational techniques can determine optimal locations for providing emergency response assuming that the uniform distribution of demand across homogeneous resources will yield and optimal service outcome. This paper presents an algorithm that recursively partitions the geographic space into sub-regions while equally distributing the population across the partitions. For this method, we have proven the existence of an upper bound on the deviation from the optimal population size for sub-regions. PMID:23853502

Optimizing conservation strategies for Mexican freetailed bats: a population viability and ecosystem services approach

USGS Publications Warehouse

Wiederholt, Ruscena; Lopez-Hoffman, Laura; Svancara, Colleen; McCracken, Gary; Thogmartin, Wayne E.; Diffendorfer, James E.; Mattson, Brady; Bagstad, Kenneth J.; Cryan, Paul; Russell, Amy; Semmens, Darius J.; Rodrigo A. Medellín,

2015-01-01

Conservation planning can be challenging due to the need to balance biological concerns about population viability with social concerns about the benefits biodiversity provide to society, often while operating under a limited budget. Methods and tools that help prioritize conservation actions are critical for the management of at-risk species. Here, we use a multi-attribute utility function to assess the optimal maternity roosts to conserve for maintaining the population viability and the ecosystem services of a single species, the Mexican free-tailed bat (Tadarida brasiliensis mexicana). Mexican free-tailed bats provide ecosystem services such as insect pest-suppression in agricultural areas and recreational viewing opportunities, and may be threatened by climate change and development of wind energy. We evaluated each roost based on five attributes: the maternity roost’s contribution to population viability, the pest suppression ecosystem services to the surrounding area provided by the bats residing in the roost, the ecotourism value of the roost, the risks posed to each roost structure, and the risks posed to the population of bats residing in each roost. We compared several scenarios that prioritized these attributes differently, hypothesizing that the set of roosts with the highest rankings would vary according to the conservation scenario. Our results indicate that placing higher values on different roost attributes (e.g. population importance over ecosystem service value) altered the roost rankings. We determined that the values placed on various conservation objectives are an important determinant of habitat planning.

Optimization of the transductional efficiency of lentiviral vectors: effect of sera and polycations

PubMed Central

Denning, Warren; Das, Suvendu; Guo, Siqi; Xu, Jun; Kappes, John C.; Hel, Zdenek

2012-01-01

Lentiviral vectors are widely used as effective gene-delivery vehicles. Optimization of the conditions for efficient lentiviral transduction is of a high importance for a variety of research applications. Presence of positively-charged polycations reduces the electrostatic repulsion forces between a negatively-charged cell and an approaching enveloped lentiviral particle resulting in an increase in the transduction efficiency. Although a variety of polycations are commonly used to enhance the transduction with retroviruses, the relative effect of various types of polycations on the efficiency of transduction and on the potential bias in the determination of titer of lentiviral vectors is not fully understood. Here we present data suggesting that DEAE-dextran provides superior results in enhancing lentiviral transduction of most tested cell lines and primary cell cultures. Specific type and source of serum affects the efficiency of transduction of target cell populations. Non-specific binding of enhanced green fluorescent protein (EGFP)-containing membrane aggregates in the presence of DEAE-dextran does not significantly affect the determination of the titer of EGFP-expressing lentiviral vectors. In conclusion, various polycations and types of sera should be tested when optimizing lentiviral transduction of target cell populations. PMID:22407723

Optimization of the transductional efficiency of lentiviral vectors: effect of sera and polycations.

PubMed

Denning, Warren; Das, Suvendu; Guo, Siqi; Xu, Jun; Kappes, John C; Hel, Zdenek

2013-03-01

Lentiviral vectors are widely used as effective gene-delivery vehicles. Optimization of the conditions for efficient lentiviral transduction is of a high importance for a variety of research applications. Presence of positively charged polycations reduces the electrostatic repulsion forces between a negatively charged cell and an approaching enveloped lentiviral particle resulting in an increase in the transduction efficiency. Although a variety of polycations are commonly used to enhance the transduction with retroviruses, the relative effect of various types of polycations on the efficiency of transduction and on the potential bias in the determination of titer of lentiviral vectors is not fully understood. Here, we present data suggesting that DEAE-dextran provides superior results in enhancing lentiviral transduction of most tested cell lines and primary cell cultures. Specific type and source of serum affects the efficiency of transduction of target cell populations. Non-specific binding of enhanced green fluorescent protein (EGFP)-containing membrane aggregates in the presence of DEAE-dextran does not significantly affect the determination of the titer of EGFP-expressing lentiviral vectors. In conclusion, various polycations and types of sera should be tested when optimizing lentiviral transduction of target cell populations.

Serum levels of organochlorine pesticides in the general population of Thessaly, Greece, determined by HS-SPME GC-MS method.

PubMed

Koureas, Michalis; Karagkouni, Foteini; Rakitskii, Valerii; Hadjichristodoulou, Christos; Tsatsakis, Aristidis; Tsakalof, Andreas

2016-07-01

In this study, exposure levels of organochlorine pesticides (OCs) were determined in general population residing in Larissa, central Greece. Serum samples from 103 volunteers were analyzed by optimized headspace solid-phase microextraction gas chromatography-mass spectrometry, to detect and quantify OC levels. The most frequently detected analytes were p,p'-DDE (frequency 99%, median:1.25ng/ml) and Hexachlorobenzene (HCB) (frequency 69%, median: 0.13ng/ml). Statistical analysis revealed a significant relationship of p,p'-DDE and HCB levels with age. Copyright © 2016 Elsevier Inc. All rights reserved.

Optimal control in a model of malaria with differential susceptibility

NASA Astrophysics Data System (ADS)

Hincapié, Doracelly; Ospina, Juan

2014-06-01

A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.

Optimal control of population recovery--the role of economic restoration threshold.

PubMed

Lampert, Adam; Hastings, Alan

2014-01-01

A variety of ecological systems around the world have been damaged in recent years, either by natural factors such as invasive species, storms and global change or by direct human activities such as overfishing and water pollution. Restoration of these systems to provide ecosystem services entails significant economic benefits. Thus, choosing how and when to restore in an optimal fashion is important, but has not been well studied. Here we examine a general model where population growth can be induced or accelerated by investing in active restoration. We show that the most cost-effective method to restore an ecosystem dictates investment until the population approaches an 'economic restoration threshold', a density above which the ecosystem should be left to recover naturally. Therefore, determining this threshold is a key general approach for guiding efficient restoration management, and we demonstrate how to calculate this threshold for both deterministic and stochastic ecosystems. © 2013 John Wiley & Sons Ltd/CNRS.

HIV Treatment and Prevention: A Simple Model to Determine Optimal Investment.

PubMed

Juusola, Jessie L; Brandeau, Margaret L

2016-04-01

To create a simple model to help public health decision makers determine how to best invest limited resources in HIV treatment scale-up and prevention. A linear model was developed for determining the optimal mix of investment in HIV treatment and prevention, given a fixed budget. The model incorporates estimates of secondary health benefits accruing from HIV treatment and prevention and allows for diseconomies of scale in program costs and subadditive benefits from concurrent program implementation. Data sources were published literature. The target population was individuals infected with HIV or at risk of acquiring it. Illustrative examples of interventions include preexposure prophylaxis (PrEP), community-based education (CBE), and antiretroviral therapy (ART) for men who have sex with men (MSM) in the US. Outcome measures were incremental cost, quality-adjusted life-years gained, and HIV infections averted. Base case analysis indicated that it is optimal to invest in ART before PrEP and to invest in CBE before scaling up ART. Diseconomies of scale reduced the optimal investment level. Subadditivity of benefits did not affect the optimal allocation for relatively low implementation levels. The sensitivity analysis indicated that investment in ART before PrEP was optimal in all scenarios tested. Investment in ART before CBE became optimal when CBE reduced risky behavior by 4% or less. Limitations of the study are that dynamic effects are approximated with a static model. Our model provides a simple yet accurate means of determining optimal investment in HIV prevention and treatment. For MSM in the US, HIV control funds should be prioritized on inexpensive, effective programs like CBE, then on ART scale-up, with only minimal investment in PrEP. © The Author(s) 2015.

Optimal cut-off levels to define obesity: body mass index and waist circumference, and their relationship to cardiovascular disease, dyslipidaemia, hypertension and diabetes in Malaysia.

PubMed

Zaher, Zaki Morad Mohd; Zambari, Robayaah; Pheng, Chan Siew; Muruga, Vadivale; Ng, Bernard; Appannah, Geeta; Onn, Lim Teck

2009-01-01

Many studies in Asia have demonstrated that Asian populations may require lower cut-off levels for body mass index (BMI) and waist circumference to define obesity and abdominal obesity respectively, compared to western populations. Optimal cut-off levels for body mass index and waist circumference were determined to assess the relationship between the two anthropometric- and cardiovascular indices. Receiver operating characteristics analysis was used to determine the optimal cut-off levels. The study sample included 1833 subjects (mean age of 44+/-14 years) from 93 primary care clinics in Malaysia. Eight hundred and seventy two of the subjects were men and 960 were women. The optimal body mass index cut-off values predicting dyslipidaemia, hypertension, diabetes mellitus, or at least one cardiovascular risk factor varied from 23.5 to 25.5 kg/m2 in men and 24.9 to 27.4 kg/m2 in women. As for waist circumference, the optimal cut-off values varied from 83 to 92 cm in men and from 83 to 88 cm in women. The optimal cut-off values from our study showed that body mass index of 23.5 kg/m2 in men and 24.9 kg/m2 in women and waist circumference of 83 cm in men and women may be more suitable for defining the criteria for overweight or obesity among adults in Malaysia. Waist circumference may be a better indicator for the prediction of obesity-related cardiovascular risk factors in men and women compared to BMI. Further investigation using a bigger sample size in Asia needs to be done to confirm our findings.

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

Energetic constraints, size gradients, and size limits in benthic marine invertebrates.

PubMed

Sebens, Kenneth P

2002-08-01

Populations of marine benthic organisms occupy habitats with a range of physical and biological characteristics. In the intertidal zone, energetic costs increase with temperature and aerial exposure, and prey intake increases with immersion time, generating size gradients with small individuals often found at upper limits of distribution. Wave action can have similar effects, limiting feeding time or success, although certain species benefit from wave dislodgment of their prey; this also results in gradients of size and morphology. The difference between energy intake and metabolic (and/or behavioral) costs can be used to determine an energetic optimal size for individuals in such populations. Comparisons of the energetic optimal size to the maximum predicted size based on mechanical constraints, and the ensuing mortality schedule, provides a mechanism to study and explain organism size gradients in intertidal and subtidal habitats. For species where the energetic optimal size is well below the maximum size that could persist under a certain set of wave/flow conditions, it is probable that energetic constraints dominate. When the opposite is true, populations of small individuals can dominate habitats with strong dislodgment or damage probability. When the maximum size of individuals is far below either energetic optima or mechanical limits, other sources of mortality (e.g., predation) may favor energy allocation to early reproduction rather than to continued growth. Predictions based on optimal size models have been tested for a variety of intertidal and subtidal invertebrates including sea anemones, corals, and octocorals. This paper provides a review of the optimal size concept, and employs a combination of the optimal energetic size model and life history modeling approach to explore energy allocation to growth or reproduction as the optimal size is approached.

Social Determinants of Racial Disparities in CKD

PubMed Central

Norton, Jenna M.; Moxey-Mims, Marva M.; Eggers, Paul W.; Narva, Andrew S.; Star, Robert A.; Rodgers, Griffin P.

2016-01-01

Significant disparities in CKD rates and outcomes exist between black and white Americans. Health disparities are defined as health differences that adversely affect disadvantaged populations, on the basis of one or more health outcomes. CKD is the complex result of genetic and environmental factors, reflecting the balance of nature and nurture. Social determinants of health have an important role as environmental components, especially for black populations, who are disproportionately disadvantaged. Understanding the social determinants of health and appreciating the underlying differences associated with meaningful clinical outcomes may help nephrologists treat all their patients with CKD in an optimal manner. Altering the social determinants of health, although difficult, may embody important policy and research efforts, with the ultimate goal of improving outcomes for patients with kidney diseases, and minimizing the disparities between groups. PMID:27178804

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perras, Frédéric A.; Boteju, Kasuni C.; Slowing, Igor I.

In this work, we utilize direct 17O DNP for the characterization of non-protonated oxygens in heterogeneous catalysts. The optimal sample preparation and population transfer approach for 17O direct DNP experiments performed on silica surfaces is determined and applied to the characterization of Zr- and Y-based mesoporous silica-supported single-site catalysts.

Femoral Component Sizing in Oxford Unicompartmental Knee Replacement: Existing Guidelines Do Not Work for Indian Patients.

PubMed

Malhotra, Rajesh; Gaba, Sahil; Wahal, Naman; Kumar, Vijay; Srivastava, Deep N; Pandit, Hemant

2018-02-28

Oxford unicompartmental knee replacement (OUKR) has shown excellent long-term clinical outcomes as well as implant survival when used for correct indications with optimal surgical technique. Anteromedial osteoarthritis is highly prevalent in Indian patients, and OUKR is the ideal treatment option in such cases. Uncertainty prevails about the best method to determine femoral component size in OUKR. Preoperative templating has been shown to be inaccurate, while height- and gender-based guidelines based on European population might not apply to the Indian patients. Microplasty instrumentation introduced in 2012 introduced the sizing spoon, which has the dual function of femoral component sizing and determining the level of tibia cut. We aimed to check the accuracy of sizing spoon and also to determine whether the present guidelines are appropriate for use in the Indian patients. A total of 130 consecutive Oxford mobile bearing medial cemented UKR performed using the Microplasty instrumentation were included. The ideal femoral component size for each knee was recorded by looking for overhang and underhang in post-operative lateral knee radiograph. The accuracy of previous guidelines was determined by applying them to our study population. Previously published guidelines (which were based on Western population) proved to be accurate in only 37% of cases. Hence, based on the demographics of our study population, we formulated modified height- and gender-based guidelines, which would better suit the Indian population. Accuracy of modified guidelines was estimated to be 74%. The overall accuracy of sizing spoon (75%), when used as an intraoperative guide, was similar to that of modified guidelines. Existing guidelines for femoral component sizing do not work in Indian patients. Modified guidelines and use of intraoperative spoon should be used to choose the optimal implant size while performing OUKR in Indian patients. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Genetic Algorithm for Optimization: Preprocessing with n Dimensional Bisection and Error Estimation

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2006-01-01

A knowledge of the appropriate values of the parameters of a genetic algorithm (GA) such as the population size, the shrunk search space containing the solution, crossover and mutation probabilities is not available a priori for a general optimization problem. Recommended here is a polynomial-time preprocessing scheme that includes an n-dimensional bisection and that determines the foregoing parameters before deciding upon an appropriate GA for all problems of similar nature and type. Such a preprocessing is not only fast but also enables us to get the global optimal solution and its reasonably narrow error bounds with a high degree of confidence.

Optimal Vitamin D Status in a Middle-Aged and Elderly Population Residing in Shanghai, China.

PubMed

Aleteng, Qiqige; Zhao, Lin; Lin, Huandong; Xia, Mingfeng; Ma, Hui; Gao, Jian; Pan, Baishen; Gao, Xin

2017-12-19

BACKGROUND The aim of this study was to investigate the optimal vitamin D status in the middle-aged and elderly population residing in Shanghai, China. MATERIAL AND METHODS A total of 1,829 males and postmenopausal females older than 45 years of age in the Changfeng community of Shanghai were included in this study. The optimal vitamin D level was determined according to the suppression of parathyroid hormone (PTH) and the highest bone mineral density (BMD). Locally weighted scatter plot smoothing (LOWESS) was performed to study the correlations of 25(OH)D with PTH and BMD in the lumbar spine and total hip, adjusting for gender, age, weight, use of calcium and vitamin D supplements, eGFR, smoking status, and alcohol consumption. RESULTS The mean serum 25(OH)D concentration was 48.0±19.2 nmol/L for the whole study population. The circulating PTH was maximally suppressed by the serum 25(OH)D of 55 nmol/L in the total population (60 nmol/L for males and 50 nmol/L for females). The 25(OH)D concentrations corresponding to the highest BMD at lumbar spine (L1-L4) and total hip were 53 nmol/L and 75 nmol/L, respectively, for the whole population. These values were also higher in males than females. CONCLUSIONS The optimal 25(OH)D concentration of 55 nmol/L is sufficient to maintain the bone health and metabolic status in middle-aged and elderly individuals living in Shanghai. Males probably need higher vitamin D concentration than females. There are differences between vitamin D status based on lumbar spine BMD and total hip BMD.

Optimal management of non-Markovian biological populations

USGS Publications Warehouse

Williams, B.K.

2007-01-01

Wildlife populations typically are described by Markovian models, with population dynamics influenced at each point in time by current but not previous population levels. Considerable work has been done on identifying optimal management strategies under the Markovian assumption. In this paper we generalize this work to non-Markovian systems, for which population responses to management are influenced by lagged as well as current status and/or controls. We use the maximum principle of optimal control theory to derive conditions for the optimal management such a system, and illustrate the effects of lags on the structure of optimal habitat strategies for a predator-prey system.

Desynchronization of stochastically synchronized chemical oscillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snari, Razan; Tinsley, Mark R., E-mail: mark.tinsley@mail.wvu.edu, E-mail: kshowalt@wvu.edu; Faramarzi, Sadegh

Experimental and theoretical studies are presented on the design of perturbations that enhance desynchronization in populations of oscillators that are synchronized by periodic entrainment. A phase reduction approach is used to determine optimal perturbation timing based upon experimentally measured phase response curves. The effectiveness of the perturbation waveforms is tested experimentally in populations of periodically and stochastically synchronized chemical oscillators. The relevance of the approach to therapeutic methods for disrupting phase coherence in groups of stochastically synchronized neuronal oscillators is discussed.

Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model

PubMed Central

Nguyen, Chantal; Carlson, Jean M.

2016-01-01

Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling) of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs. PMID:27043931

Palmer amaranth seed mortality in response to burial depth and time

USDA-ARS?s Scientific Manuscript database

Glyphosate resistant Palmer amaranth infests millions of arable acres in the SE US. One proposed method of reducing population numbers is to bury surface seeds deeply, below their optimal emergence zone. The objective of this study was to determine how burial longevity and depth impact Palmer amaran...

Dissecting plant chromosomes by the use of ionizing radiation

USDA-ARS?s Scientific Manuscript database

Radiation treatment of genomes is used to generate chromosome breaks for numerous applications. This protocol describes the preparation of seeds and the determination of the optimal level of irradiation dosage for the creation of a radiation hybrid (RH) population. These RH lines can be used to gene...

A diffusion-based approach to stochastic individual growth and energy budget, with consequences to life-history optimization and population dynamics.

PubMed

Filin, I

2009-06-01

Using diffusion processes, I model stochastic individual growth, given exogenous hazards and starvation risk. By maximizing survival to final size, optimal life histories (e.g. switching size for habitat/dietary shift) are determined by two ratios: mean growth rate over growth variance (diffusion coefficient) and mortality rate over mean growth rate; all are size dependent. For example, switching size decreases with either ratio, if both are positive. I provide examples and compare with previous work on risk-sensitive foraging and the energy-predation trade-off. I then decompose individual size into reversibly and irreversibly growing components, e.g. reserves and structure. I provide a general expression for optimal structural growth, when reserves grow stochastically. I conclude that increased growth variance of reserves delays structural growth (raises threshold size for its commencement) but may eventually lead to larger structures. The effect depends on whether the structural trait is related to foraging or defence. Implications for population dynamics are discussed.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions

PubMed Central

2018-01-01

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence. PMID:29543711

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions.

PubMed

Alva, Maria L

2018-03-15

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence.

Energy: It is life

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arques, P.

1998-07-01

The relationships that seem to exist between energy and man are presented in this paper. Habitually, social coefficients are connected to the gross domestic product; some parameters with correlations are: birth rate, infant mortality rate, death rate, literacy, etc. Along with energy these define the optimal energy consumption per capita; the author presents the correlation between these parameters and energy consumed per capita. There exists a high correlation between energy consumption per capita and gross domestic product per capita. The set of parameters considered are correlated with similar values relative to these two parameters. Using data collected on a groupmore » of the different countries of the world, a table of 165 countries and 22 variables has been drawn up. From the [Country x variable] matrix, a correlation table is calculated and a factorial analysis is applied to this matrix. The first factorial plan comprises 57% of the information contained in this table. Results from this first factorial plan are presented. These parameters are analyzed: influence of a country's latitude on its inhabitants' consumption; relationship between consumed energy and gross domestic product; women's fertility rate; birth rate per 1000 population; sex ratio; life expectancy at birth; rate of literacy; death rate; population growth rate. Finally, it is difficult to define precise criteria for: an optimal distribution of population according to age, but with a power consumed of above 300 W per capita, the population becomes younger; the birth rate per 1000 population; the total fertility rate per woman; the population growth rate. The authors determine that optimal energy is approximately between 200 W and 677 W inclusive.« less

Integrating biology, field logistics, and simulations to optimize parameter estimation for imperiled species

USGS Publications Warehouse

Lanier, Wendy E.; Bailey, Larissa L.; Muths, Erin L.

2016-01-01

Conservation of imperiled species often requires knowledge of vital rates and population dynamics. However, these can be difficult to estimate for rare species and small populations. This problem is further exacerbated when individuals are not available for detection during some surveys due to limited access, delaying surveys and creating mismatches between the breeding behavior and survey timing. Here we use simulations to explore the impacts of this issue using four hypothetical boreal toad (Anaxyrus boreas boreas) populations, representing combinations of logistical access (accessible, inaccessible) and breeding behavior (synchronous, asynchronous). We examine the bias and precision of survival and breeding probability estimates generated by survey designs that differ in effort and timing for these populations. Our findings indicate that the logistical access of a site and mismatch between the breeding behavior and survey design can greatly limit the ability to yield accurate and precise estimates of survival and breeding probabilities. Simulations similar to what we have performed can help researchers determine an optimal survey design(s) for their system before initiating sampling efforts.

Performance breakdown in optimal stimulus decoding

NASA Astrophysics Data System (ADS)

Kostal, Lubomir; Lansky, Petr; Pilarski, Stevan

2015-06-01

Objective. One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. Approach. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. Main results. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. Significance. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.

Performance breakdown in optimal stimulus decoding.

PubMed

Lubomir Kostal; Lansky, Petr; Pilarski, Stevan

2015-06-01

One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.

Hitting the Optimal Vaccination Percentage and the Risks of Error: Why to Miss Right.

PubMed

Harvey, Michael J; Prosser, Lisa A; Messonnier, Mark L; Hutton, David W

2016-01-01

To determine the optimal level of vaccination coverage defined as the level that minimizes total costs and explore how economic results change with marginal changes to this level of coverage. A susceptible-infected-recovered-vaccinated model designed to represent theoretical infectious diseases was created to simulate disease spread. Parameter inputs were defined to include ranges that could represent a variety of possible vaccine-preventable conditions. Costs included vaccine costs and disease costs. Health benefits were quantified as monetized quality adjusted life years lost from disease. Primary outcomes were the number of infected people and the total costs of vaccination. Optimization methods were used to determine population vaccination coverage that achieved a minimum cost given disease and vaccine characteristics. Sensitivity analyses explored the effects of changes in reproductive rates, costs and vaccine efficacies on primary outcomes. Further analysis examined the additional cost incurred if the optimal coverage levels were not achieved. Results indicate that the relationship between vaccine and disease cost is the main driver of the optimal vaccination level. Under a wide range of assumptions, vaccination beyond the optimal level is less expensive compared to vaccination below the optimal level. This observation did not hold when the cost of the vaccine cost becomes approximately equal to the cost of disease. These results suggest that vaccination below the optimal level of coverage is more costly than vaccinating beyond the optimal level. This work helps provide information for assessing the impact of changes in vaccination coverage at a societal level.

Assessment of Medical Risks and Optimization of their Management using Integrated Medical Model

NASA Technical Reports Server (NTRS)

Fitts, Mary A.; Madurai, Siram; Butler, Doug; Kerstman, Eric; Risin, Diana

2008-01-01

The Integrated Medical Model (IMM) Project is a software-based technique that will identify and quantify the medical needs and health risks of exploration crew members during space flight and evaluate the effectiveness of potential mitigation strategies. The IMM Project employs an evidence-based approach that will quantify probability and consequences of defined in-flight medical risks, mitigation strategies, and tactics to optimize crew member health. Using stochastic techniques, the IMM will ultimately inform decision makers at both programmatic and institutional levels and will enable objective assessment of crew health and optimization of mission success using data from relevant cohort populations and from the astronaut population. The objectives of the project include: 1) identification and documentation of conditions that may occur during exploration missions (Baseline Medical Conditions List [BMCL), 2) assessment of the likelihood of conditions in the BMCL occurring during exploration missions (incidence rate), 3) determination of the risk associated with these conditions and quantify in terms of end states (Loss of Crew, Loss of Mission, Evacuation), 4) optimization of in-flight hardware mass, volume, power, bandwidth and cost for a given level of risk or uncertainty, and .. validation of the methodologies used.

Detecting glaucomatous change in visual fields: Analysis with an optimization framework.

PubMed

Yousefi, Siamak; Goldbaum, Michael H; Varnousfaderani, Ehsan S; Belghith, Akram; Jung, Tzyy-Ping; Medeiros, Felipe A; Zangwill, Linda M; Weinreb, Robert N; Liebmann, Jeffrey M; Girkin, Christopher A; Bowd, Christopher

2015-12-01

Detecting glaucomatous progression is an important aspect of glaucoma management. The assessment of longitudinal series of visual fields, measured using Standard Automated Perimetry (SAP), is considered the reference standard for this effort. We seek efficient techniques for determining progression from longitudinal visual fields by formulating the problem as an optimization framework, learned from a population of glaucoma data. The longitudinal data from each patient's eye were used in a convex optimization framework to find a vector that is representative of the progression direction of the sample population, as a whole. Post-hoc analysis of longitudinal visual fields across the derived vector led to optimal progression (change) detection. The proposed method was compared to recently described progression detection methods and to linear regression of instrument-defined global indices, and showed slightly higher sensitivities at the highest specificities than other methods (a clinically desirable result). The proposed approach is simpler, faster, and more efficient for detecting glaucomatous changes, compared to our previously proposed machine learning-based methods, although it provides somewhat less information. This approach has potential application in glaucoma clinics for patient monitoring and in research centers for classification of study participants. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of a Novel BRCA1 Pathogenic Mutation in Korean Patients Following Reclassification of BRCA1 and BRCA2 Variants According to the ACMG Standards and Guidelines Using Relevant Ethnic Controls.

PubMed

Park, Ji Soo; Nam, Eun Ji; Park, Hyung Seok; Han, Jung Woo; Lee, Jung-Yun; Kim, Jieun; Kim, Tae Il; Lee, Seung-Tae

2017-10-01

Comparison of variant frequencies in the general population has become an essential part of the American College of Medical Genetics and Genomics (ACMG) standards and guidelines for interpreting sequence variants. We determined the optimal number of relevant ethnic controls that should be used to accurately calculate the odds ratio (OR) of genetic variants. Using the ACMG guidelines, we reclassified BRCA1 and BRCA2 mutations and variants of unknown significance in 745 Korean patients susceptible to hereditary breast and ovarian cancer compared with 1,314 Korean population controls. We observed that the ORs were falsely inflated when we analyzed several variants using non-Korean population data. Our simulation indicated that the number of controls needed for the lower limit of a 95% confidence interval to exceed 1.0 varied according to the frequency of the variant in each patient group, with more than 820 controls needed for a variant existing in 1% of cases. Using a sufficient number of relevant population data, we could efficiently classify variants and identified the BRCA1 p.Leu1780Pro mutation as a possible pathogenic founder mutation in Korean patients. Our study suggests that BRCA1 p.Leu1780Pro is a novel pathogenic mutation found in Korean patients. We also determined the optimal number of relevant ethnic controls needed for accurate variant classification according to the ACMG guidelines.

Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE)

PubMed Central

Peñalvo, Jose L.; Khatibzadeh, Shahab; Singh, Gitanjali M.; Rao, Mayuree; Fahimi, Saman; Powles, John; Mozaffarian, Dariush

2017-01-01

Background Dietary habits are major contributors to coronary heart disease, stroke, and diabetes. However, comprehensive evaluation of etiologic effects of dietary factors on cardiometabolic outcomes, their quantitative effects, and corresponding optimal intakes are not well-established. Objective To systematically review the evidence for effects of dietary factors on cardiometabolic diseases, including comprehensively assess evidence for causality; estimate magnitudes of etiologic effects; evaluate heterogeneity and potential for bias in these etiologic effects; and determine optimal population intake levels. Methods We utilized Bradford-Hill criteria to assess probable or convincing evidence for causal effects of multiple diet-cardiometabolic disease relationships. Etiologic effects were quantified from published or de novo meta-analyses of prospective studies or randomized clinical trials, incorporating standardized units, dose-response estimates, and heterogeneity by age and other characteristics. Potential for bias was assessed in validity analyses. Optimal intakes were determined by levels associated with lowest disease risk. Results We identified 10 foods and 7 nutrients with evidence for causal cardiometabolic effects, including protective effects of fruits, vegetables, beans/legumes, nuts/seeds, whole grains, fish, yogurt, fiber, seafood omega-3s, polyunsaturated fats, and potassium; and harms of unprocessed red meats, processed meats, sugar-sweetened beverages, glycemic load, trans-fats, and sodium. Proportional etiologic effects declined with age, but did not generally vary by sex. Established optimal population intakes were generally consistent with observed national intakes and major dietary guidelines. In validity analyses, the identified effects of individual dietary components were similar to quantified effects of dietary patterns on cardiovascular risk factors and hard endpoints. Conclusions These novel findings provide a comprehensive summary of causal evidence, quantitative etiologic effects, heterogeneity, and optimal intakes of major dietary factors for cardiometabolic diseases, informing disease impact estimation and policy planning and priorities. PMID:28448503

Optimal Cut-Off Points of Fasting Plasma Glucose for Two-Step Strategy in Estimating Prevalence and Screening Undiagnosed Diabetes and Pre-Diabetes in Harbin, China

PubMed Central

Sun, Bo; Lan, Li; Cui, Wenxiu; Xu, Guohua; Sui, Conglan; Wang, Yibaina; Zhao, Yashuang; Wang, Jian; Li, Hongyuan

2015-01-01

To identify optimal cut-off points of fasting plasma glucose (FPG) for two-step strategy in screening abnormal glucose metabolism and estimating prevalence in general Chinese population. A population-based cross-sectional study was conducted on 7913 people aged 20 to 74 years in Harbin. Diabetes and pre-diabetes were determined by fasting and 2 hour post-load glucose from the oral glucose tolerance test in all participants. Screening potential of FPG, cost per case identified by two-step strategy, and optimal FPG cut-off points were described. The prevalence of diabetes was 12.7%, of which 65.2% was undiagnosed. Twelve percent or 9.0% of participants were diagnosed with pre-diabetes using 2003 ADA criteria or 1999 WHO criteria, respectively. The optimal FPG cut-off points for two-step strategy were 5.6 mmol/l for previously undiagnosed diabetes (area under the receiver-operating characteristic curve of FPG 0.93; sensitivity 82.0%; cost per case identified by two-step strategy ¥261), 5.3 mmol/l for both diabetes and pre-diabetes or pre-diabetes alone using 2003 ADA criteria (0.89 or 0.85; 72.4% or 62.9%; ¥110 or ¥258), 5.0 mmol/l for pre-diabetes using 1999 WHO criteria (0.78; 66.8%; ¥399), and 4.9 mmol/l for IGT alone (0.74; 62.2%; ¥502). Using the two-step strategy, the underestimates of prevalence reduced to nearly 38% for pre-diabetes or 18.7% for undiagnosed diabetes, respectively. Approximately a quarter of the general population in Harbin was in hyperglycemic condition. Using optimal FPG cut-off points for two-step strategy in Chinese population may be more effective and less costly for reducing the missed diagnosis of hyperglycemic condition. PMID:25785585

Population pharmacokinetics and dosing regimen design of milrinone in preterm infants

PubMed Central

Paradisis, Mary; Jiang, Xuemin; McLachlan, Andrew J; Evans, Nick; Kluckow, Martin; Osborn, David

2007-01-01

Aims To define the pharmacokinetics of milrinone in very preterm infants and determine an optimal dose regimen to prevent low systemic blood flow in the first 12 h after birth. Methods A prospective open‐labelled, dose‐escalation pharmacokinetic study was undertaken in two stages. In stage one, infants received milrinone at 0.25 μg/kg/min (n = 8) and 0.5 μg/kg/min (n = 11) infused from 3 to 24 h of age. Infants contributed 4–5 blood samples for concentration–time data which were analysed using a population modelling approach. A simulation study was used to explore the optimal dosing regimen to achieve target milrinone concentrations (180–300 ng/ml). This milrinone regimen was evaluated in stage two (n = 10). Results Infants (n = 29) born before 29 weeks gestation were enrolled. Milrinone pharmacokinetics were described using a one‐compartment model with first‐order elimination rate, with a population mean clearance (CV%) of 35 ml/h (24%) and volume of distribution of 512 ml (21%) and estimated half‐life of 10 h. The 0.25 and 0.5 μg/kg/min dosage regimens did not achieve optimal milrinone concentration‐time profiles to prevent early low systemic blood flow. Simulation studies predicted a loading infusion (0.75 μg/kg/min for 3 h) followed by maintenance infusion (0.2 μg/kg/min until 18 h of age) would provide an optimal milrinone concentration profile. This was confirmed in stage two of the study. Conclusion Population pharmacokinetic modelling in the preterm infant has established an optimal dose regimen for milrinone that increases the likelihood of achieving therapeutic aims and highlights the importance of pharmacokinetic studies in neonatal clinical pharmacology. PMID:16690639

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo; Craig, Tim

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and appliedmore » three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR weight prediction methodologies perform comparably to the LR model and can produce clinical quality treatment plans by simultaneously predicting multiple weights that capture trade-offs associated with sparing multiple OARs.« less

Wireless Sensor Networks - Node Localization for Various Industry Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Derr, Kurt; Manic, Milos

Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothingmore » (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications.« less

Wireless Sensor Networks - Node Localization for Various Industry Problems

DOE PAGES

Derr, Kurt; Manic, Milos

2015-06-01

Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothingmore » (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications.« less

Comparing population and incident data for optimal air ambulance base locations in Norway.

PubMed

Røislien, Jo; van den Berg, Pieter L; Lindner, Thomas; Zakariassen, Erik; Uleberg, Oddvar; Aardal, Karen; van Essen, J Theresia

2018-05-24

Helicopter emergency medical services are important in many health care systems. Norway has a nationwide physician manned air ambulance service servicing a country with large geographical variations in population density and incident frequencies. The aim of the study was to compare optimal air ambulance base locations using both population and incident data. We used municipality population and incident data for Norway from 2015. The 428 municipalities had a median (5-95 percentile) of 4675 (940-36,264) inhabitants and 10 (2-38) incidents. Optimal helicopter base locations were estimated using the Maximal Covering Location Problem (MCLP) optimization model, exploring the number and location of bases needed to cover various fractions of the population for time thresholds 30 and 45 min, in green field scenarios and conditioned on the existing base structure. The existing bases covered 96.90% of the population and 91.86% of the incidents for time threshold 45 min. Correlation between municipality population and incident frequencies was -0.0027, and optimal base locations varied markedly between the two data types, particularly when lowering the target time. The optimal solution using population density data put focus on the greater Oslo area, where one third of Norwegians live, while using incident data put focus on low population high incident areas, such as northern Norway and winter sport resorts. Using population density data as a proxy for incident frequency is not recommended, as the two data types lead to different optimal base locations. Lowering the target time increases the sensitivity to choice of data.

Classification of Individual Well-Being Scores for the Determination of Adverse Health and Productivity Outcomes in Employee Populations

PubMed Central

Sears, Lindsay E.; Coberley, Carter R.; Pope, James E.

2013-01-01

Abstract Adverse health and productivity outcomes have imposed a considerable economic burden on employers. To facilitate optimal worksite intervention designs tailored to differing employee risk levels, the authors established cutoff points for an Individual Well-Being Score (IWBS) based on a global measure of well-being. Cross-sectional associations between IWBS and adverse health and productivity outcomes, including high health care cost, emergency room visits, short-term disability days, absenteeism, presenteeism, low job performance ratings, and low intentions to stay with the employer, were studied in a sample of 11,702 employees from a large employer. Receiver operating characteristics curves were evaluated to detect a single optimal cutoff value of IWBS for predicting 2 or more adverse outcomes. More granular segmentation was achieved by computing relative risks of each adverse outcome from logistic regressions accounting for sociodemographic characteristics. Results showed strong and significant nonlinear associations between IWBS and health and productivity outcomes. An IWBS of 75 was found to be the optimal single cutoff point to discriminate 2 or more adverse outcomes. Logistic regression models found abrupt reductions of relative risk also clustered at IWBS cutoffs of 53, 66, and 88, in addition to 75, which segmented employees into high, high-medium, medium, low-medium, and low risk groups. To determine validity and generalizability, cutoff values were applied in a smaller employee population (N=1853) and confirmed significant differences between risk groups across health and productivity outcomes. The reported segmentation of IWBS into discrete cohorts based on risk of adverse health and productivity outcomes should facilitate well-being comparisons and worksite interventions. (Population Health Management 2013;16:90–98) PMID:23013034

Ethnic dependent differences in diagnostic accuracy of glycated hemoglobin (HbA1c) in Canadian adults.

PubMed

Booth, Ronald A; Jiang, Ying; Morrison, Howard; Orpana, Heather; Rogers Van Katwyk, Susan; Lemieux, Chantal

2018-02-01

Previous studies have shown varying sensitivity and specificity of hemoglobin A1c (HbA1c) to identify diabetes and prediabetes, compared to 2-h oral glucose tolerance testing (OGTT) and fasting plasma glucose (FPG), in different ethnic groups. Within the Canadian population, the ability of HbA1c to identify prediabetes and diabetes in First Nations, Métis and Inuit, East and South Asian ethnic groups has yet to be determined. We collected demographic, lifestyle information, biochemical results of glycemic status (FPG, OGTT, and HbA1c) from an ethnically diverse Canadian population sample, which included a purposeful sampling of First Nations, Métis, Inuit, South Asian and East Asian participants. Sensitivity and specificity using Canadian Diabetes Association (CDA) recommended cut-points varied between ethnic groups, with greater variability for identification of prediabetes than diabetes. Dysglycemia (prediabetes and diabetes) was identified with a sensitivity and specificity ranging from 47.1% to 87.5%, respectively in Caucasians to 24.1% and 88.8% in Inuit. Optimal HbA1c ethnic-specific cut-points for dysglycemia and diabetes were determined by receiver operating characteristic (ROC) curve analysis. Our sample showed broad differences in the ability of HbA1c to identify dysglycemia or diabetes in different ethnic groups. Optimal cut-points for dysglycemia or diabetes in all ethnic groups were substantially lower than CDA recommendations. Utilization of HbA1c as the sole biochemical diagnostic marker may produce varying degrees of false negative results depending on the ethnicity of screened individuals. Further research is necessary to identify and validate optimal ethnic specific cut-points used for diabetic screening in the Canadian population. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Comparison and optimization of in silico algorithms for predicting the pathogenicity of sodium channel variants in epilepsy.

PubMed

Holland, Katherine D; Bouley, Thomas M; Horn, Paul S

2017-07-01

Variants in neuronal voltage-gated sodium channel α-subunits genes SCN1A, SCN2A, and SCN8A are common in early onset epileptic encephalopathies and other autosomal dominant childhood epilepsy syndromes. However, in clinical practice, missense variants are often classified as variants of uncertain significance when missense variants are identified but heritability cannot be determined. Genetic testing reports often include results of computational tests to estimate pathogenicity and the frequency of that variant in population-based databases. The objective of this work was to enhance clinicians' understanding of results by (1) determining how effectively computational algorithms predict epileptogenicity of sodium channel (SCN) missense variants; (2) optimizing their predictive capabilities; and (3) determining if epilepsy-associated SCN variants are present in population-based databases. This will help clinicians better understand the results of indeterminate SCN test results in people with epilepsy. Pathogenic, likely pathogenic, and benign variants in SCNs were identified using databases of sodium channel variants. Benign variants were also identified from population-based databases. Eight algorithms commonly used to predict pathogenicity were compared. In addition, logistic regression was used to determine if a combination of algorithms could better predict pathogenicity. Based on American College of Medical Genetic Criteria, 440 variants were classified as pathogenic or likely pathogenic and 84 were classified as benign or likely benign. Twenty-eight variants previously associated with epilepsy were present in population-based gene databases. The output provided by most computational algorithms had a high sensitivity but low specificity with an accuracy of 0.52-0.77. Accuracy could be improved by adjusting the threshold for pathogenicity. Using this adjustment, the Mendelian Clinically Applicable Pathogenicity (M-CAP) algorithm had an accuracy of 0.90 and a combination of algorithms increased the accuracy to 0.92. Potentially pathogenic variants are present in population-based sources. Most computational algorithms overestimate pathogenicity; however, a weighted combination of several algorithms increased classification accuracy to >0.90. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Optimization of High-Throughput Sequencing Kinetics for determining enzymatic rate constants of thousands of RNA substrates

PubMed Central

Niland, Courtney N.; Jankowsky, Eckhard; Harris, Michael E.

2016-01-01

Quantification of the specificity of RNA binding proteins and RNA processing enzymes is essential to understanding their fundamental roles in biological processes. High Throughput Sequencing Kinetics (HTS-Kin) uses high throughput sequencing and internal competition kinetics to simultaneously monitor the processing rate constants of thousands of substrates by RNA processing enzymes. This technique has provided unprecedented insight into the substrate specificity of the tRNA processing endonuclease ribonuclease P. Here, we investigate the accuracy and robustness of measurements associated with each step of the HTS-Kin procedure. We examine the effect of substrate concentration on the observed rate constant, determine the optimal kinetic parameters, and provide guidelines for reducing error in amplification of the substrate population. Importantly, we find that high-throughput sequencing, and experimental reproducibility contribute their own sources of error, and these are the main sources of imprecision in the quantified results when otherwise optimized guidelines are followed. PMID:27296633

Direct 17O dynamic nuclear polarization of single-site heterogeneous catalysts

DOE PAGES

Perras, Frédéric A.; Boteju, Kasuni C.; Slowing, Igor I.; ...

2018-03-13

In this work, we utilize direct 17O DNP for the characterization of non-protonated oxygens in heterogeneous catalysts. The optimal sample preparation and population transfer approach for 17O direct DNP experiments performed on silica surfaces is determined and applied to the characterization of Zr- and Y-based mesoporous silica-supported single-site catalysts.

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

PubMed Central

Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami

2015-01-01

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach. PMID:26226448

Cross-cultural differences for adapting translated five-item version of International Index of Erectile Function: results of a Korean study.

PubMed

Ku, Ja Hyeon; Park, Dal Woo; Kim, Soo Woong; Paick, Jae-Seung

2005-06-01

To assess whether the translated Korean version of the International Index of Erectile Function (IIEF-5) developed by Rosen et al. (RIIEF-5) may be adapted for a Korean population to have cross-cultural equivalency to the original version. A total of 151 patients with erectile dysfunction (ED) and 156 controls were prospectively studied. All the patients and controls had had sexual activity or attempted sexual intercourse within the 4-week period before completing the questionnaire. The Classification and Regression Trees program was used to select an optimal set of five items from the IIEF-15 (KIIEF-5) to discriminate between men with and without ED. Then, the optimal cutoff score for the diagnosis of ED was determined using the receiver operating characteristic curve. The optimal cutoff score, sensitivity, and specificity were also calculated using the RIIEF-5. The KIIEF-5 consisted, in order of importance, of items 15, 5, 13, 4, and 2 from the IIEF-15. Item 7 in the original RIIEF-5 was replaced with item 13 in the new KIIEF-5. The optimal cutoff score proved to be 21, with a corresponding sensitivity and specificity of 0.97 and 0.91, respectively. For the original RIIEF-5, the optimal cutoff score was 21 and the corresponding sensitivity and specificity was 0.94 and 0.90, respectively. Although the RIIEF-5 may be adapted for a Korean population, the KIIEF-5 can aid in decreasing the incidence of an incorrect diagnosis of ED and decreasing the number of undiagnosed cases of ED in this population. In addition, our findings suggest that the equivalence of psychometric properties does not imply cross-cultural equivalence.

Order of events matter: comparing discrete models for optimal control of species augmentation.

PubMed

Bodine, Erin N; Gross, Louis J; Lenhart, Suzanne

2012-01-01

We investigate optimal timing of augmentation of an endangered/threatened species population in a target region by moving individuals from a reserve or captive population. This is formulated as a discrete-time optimal control problem in which augmentation occurs once per time period over a fixed number of time periods. The population model assumes the Allee effect growth functions in both target and reserve populations and the control objective is to maximize the target and reserve population sizes over the time horizon while accounting for costs of augmentation. Two possible orders of events are considered for different life histories of the species relative to augmentation time: move individuals either before or after population growth occurs. The control variable is the proportion of the reserve population to be moved to the target population. We develop solutions and illustrate numerical results which indicate circumstances for which optimal augmentation strategies depend upon the order of events.

Robust Nonlinear Neural Codes

NASA Astrophysics Data System (ADS)

Yang, Qianli; Pitkow, Xaq

2015-03-01

Most interesting natural sensory stimuli are encoded in the brain in a form that can only be decoded nonlinearly. But despite being a core function of the brain, nonlinear population codes are rarely studied and poorly understood. Interestingly, the few existing models of nonlinear codes are inconsistent with known architectural features of the brain. In particular, these codes have information content that scales with the size of the cortical population, even if that violates the data processing inequality by exceeding the amount of information entering the sensory system. Here we provide a valid theory of nonlinear population codes by generalizing recent work on information-limiting correlations in linear population codes. Although these generalized, nonlinear information-limiting correlations bound the performance of any decoder, they also make decoding more robust to suboptimal computation, allowing many suboptimal decoders to achieve nearly the same efficiency as an optimal decoder. Although these correlations are extremely difficult to measure directly, particularly for nonlinear codes, we provide a simple, practical test by which one can use choice-related activity in small populations of neurons to determine whether decoding is suboptimal or optimal and limited by correlated noise. We conclude by describing an example computation in the vestibular system where this theory applies. QY and XP was supported by a grant from the McNair foundation.

The effect of fermented cocoa pod (Theobroma cacao) husk supplemented with mineral on in vitro digestibility, rumen bacteria population and rumen liquid characteristics

NASA Astrophysics Data System (ADS)

Nurhaita; Definiati, N.; Santoso, U.; Akbar, S. A.; Henuk, Y. L.

2018-02-01

This study aimed to determine the effect of mineral supplementation, such as S, P and Zn on the nutrients digestibility of fermented cocoa pod husk, the population of rumen bacteria and rumen liquid characteristics in vitro. The study used a randomized block design with 5 treatments and 4 replicates. The treatments tested were: T0 = without minerals; T1 = 0.2% S mineral; T2 = 0.27% P mineral; T3 = S and P; and T4 = S, P and Zn at 50 ppm. Parameters measured were: (1) digestibility of dry matter and organic matter; (2) rumen bacterial and cellulolytic bacterial populations; (3) characteristics of rumen liquid in vitro. The results of the study showed that mineral supplementation significantly (P <0.05) improved dry matter and organic matter digestibility. Mineral supplementation had no effect on the total population of rumen bacteria and cellulolytic rumen bacterial populations. The characteristics of rumen liquid such pH, VFA and NH3 were in optimal condition. In conclusion supplementation of S, P and Zn simultaneously gave the best results to improve the digestibility of dry matter and organic matter and to maintain rumen liquid characteristics under optimal conditions for growth and microbial activity

An optimal stratified Simon two-stage design.

PubMed

Parashar, Deepak; Bowden, Jack; Starr, Colin; Wernisch, Lorenz; Mander, Adrian

2016-07-01

In Phase II oncology trials, therapies are increasingly being evaluated for their effectiveness in specific populations of interest. Such targeted trials require designs that allow for stratification based on the participants' molecular characterisation. A targeted design proposed by Jones and Holmgren (JH) Jones CL, Holmgren E: 'An adaptive Simon two-stage design for phase 2 studies of targeted therapies', Contemporary Clinical Trials 28 (2007) 654-661.determines whether a drug only has activity in a disease sub-population or in the wider disease population. Their adaptive design uses results from a single interim analysis to decide whether to enrich the study population with a subgroup or not; it is based on two parallel Simon two-stage designs. We study the JH design in detail and extend it by providing a few alternative ways to control the familywise error rate, in the weak sense as well as the strong sense. We also introduce a novel optimal design by minimising the expected sample size. Our extended design contributes to the much needed framework for conducting Phase II trials in stratified medicine. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd.

Optimal correction and design parameter search by modern methods of rigorous global optimization

NASA Astrophysics Data System (ADS)

Makino, K.; Berz, M.

2011-07-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle optics for the computation of aberrations allow the determination of particularly sharp underestimators for large regions. As a consequence, the subsequent progressive pruning of the allowed search space as part of the optimization progresses is carried out particularly effectively. The end result is the rigorous determination of the single or multiple optimal solutions of the parameter optimization, regardless of their location, their number, and the starting values of optimization. The methods are particularly powerful if executed in interplay with genetic optimizers generating their new populations within the currently active unpruned space. Their current best guess provides rigorous upper bounds of the minima, which can then beneficially be used for better pruning. Examples of the method and its performance will be presented, including the determination of all operating points of desired tunes or chromaticities, etc. in storage ring lattices.

Cut-off optimization for 13C-urea breath test in a community-based trial by mathematic, histology and serology approach.

PubMed

Li, Zhe-Xuan; Huang, Lei-Lei; Liu, Cong; Formichella, Luca; Zhang, Yang; Wang, Yu-Mei; Zhang, Lian; Ma, Jun-Ling; Liu, Wei-Dong; Ulm, Kurt; Wang, Jian-Xi; Zhang, Lei; Bajbouj, Monther; Li, Ming; Vieth, Michael; Quante, Michael; Zhou, Tong; Wang, Le-Hua; Suchanek, Stepan; Soutschek, Erwin; Schmid, Roland; Classen, Meinhard; You, Wei-Cheng; Gerhard, Markus; Pan, Kai-Feng

2017-05-18

The performance of diagnostic tests in intervention trials of Helicobacter pylori (H.pylori) eradication is crucial, since even minor inaccuracies can have major impact. To determine the cut-off point for 13 C-urea breath test ( 13 C-UBT) and to assess if it can be further optimized by serologic testing, mathematic modeling, histopathology and serologic validation were applied. A finite mixture model (FMM) was developed in 21,857 subjects, and an independent validation by modified Giemsa staining was conducted in 300 selected subjects. H.pylori status was determined using recomLine H.pylori assay in 2,113 subjects with a borderline 13 C-UBT results. The delta over baseline-value (DOB) of 3.8 was an optimal cut-off point by a FMM in modelling dataset, which was further validated as the most appropriate cut-off point by Giemsa staining (sensitivity = 94.53%, specificity = 92.93%). In the borderline population, 1,468 subjects were determined as H.pylori positive by recomLine (69.5%). A significant correlation between the number of positive H.pylori serum responses and DOB value was found (r s  = 0.217, P < 0.001). A mathematical approach such as FMM might be an alternative measure in optimizing the cut-off point for 13 C-UBT in community-based studies, and a second method to determine H.pylori status for subjects with borderline value of 13 C-UBT was necessary and recommended.

A non-destructive selection criterion for fibre content in jute : II. Regression approach.

PubMed

Arunachalam, V; Iyer, R D

1974-01-01

An experiment with ten populations of jute, comprising varieties and mutants of the two species Corchorus olitorius and C.capsularis was conducted at two different locations with the object of evolving an effective criterion for selecting superior single plants for fibre yield. At Delhi, variation existed only between varieties as a group and mutants as a group, while at Pusa variation also existed among the mutant populations of C. capsularis.A multiple regression approach was used to find the optimum combination of characters for prediction of fibre yield. A process of successive elimination of characters based on the coefficient of determination provided by individual regression equations was employed to arrive at the optimal set of characters for predicting fibre yield. It was found that plant height, basal and mid-diameters and basal and mid-dry fibre weights would provide such an optimal set.

Particle swarm optimizer for weighting factor selection in intensity-modulated radiation therapy optimization algorithms.

PubMed

Yang, Jie; Zhang, Pengcheng; Zhang, Liyuan; Shu, Huazhong; Li, Baosheng; Gui, Zhiguo

2017-01-01

In inverse treatment planning of intensity-modulated radiation therapy (IMRT), the objective function is typically the sum of the weighted sub-scores, where the weights indicate the importance of the sub-scores. To obtain a high-quality treatment plan, the planner manually adjusts the objective weights using a trial-and-error procedure until an acceptable plan is reached. In this work, a new particle swarm optimization (PSO) method which can adjust the weighting factors automatically was investigated to overcome the requirement of manual adjustment, thereby reducing the workload of the human planner and contributing to the development of a fully automated planning process. The proposed optimization method consists of three steps. (i) First, a swarm of weighting factors (i.e., particles) is initialized randomly in the search space, where each particle corresponds to a global objective function. (ii) Then, a plan optimization solver is employed to obtain the optimal solution for each particle, and the values of the evaluation functions used to determine the particle's location and the population global location for the PSO are calculated based on these results. (iii) Next, the weighting factors are updated based on the particle's location and the population global location. Step (ii) is performed alternately with step (iii) until the termination condition is reached. In this method, the evaluation function is a combination of several key points on the dose volume histograms. Furthermore, a perturbation strategy - the crossover and mutation operator hybrid approach - is employed to enhance the population diversity, and two arguments are applied to the evaluation function to improve the flexibility of the algorithm. In this study, the proposed method was used to develop IMRT treatment plans involving five unequally spaced 6MV photon beams for 10 prostate cancer cases. The proposed optimization algorithm yielded high-quality plans for all of the cases, without human planner intervention. A comparison of the results with the optimized solution obtained using a similar optimization model but with human planner intervention revealed that the proposed algorithm produced optimized plans superior to that developed using the manual plan. The proposed algorithm can generate admissible solutions within reasonable computational times and can be used to develop fully automated IMRT treatment planning methods, thus reducing human planners' workloads during iterative processes. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Maximizing the potential of cropping systems for nematode management.

PubMed

Noe, J P; Sasser, J N; Imbriani, J L

1991-07-01

Quantitative techniques were used to analyze and determine optimal potential profitability of 3-year rotations of cotton, Gossypium hirsutum cv. Coker 315, and soybean, Glycine max cv. Centennial, with increasing population densities of Hoplolaimus columbus. Data collected from naturally infested on-farm research plots were combined with economic information to construct a microcomputer spreadsheet analysis of the cropping system. Nonlinear mathematical functions were fitted to field data to represent damage functions and population dynamic curves. Maximum yield losses due to H. columbus were estimated to be 20% on cotton and 42% on soybean. Maximum at-harvest population densities were calculated to be 182/100 cm(3) soil for cotton and 149/100 cm(3) soil for soybean. Projected net incomes ranged from a $17.74/ha net loss for the soybean-cotton-soybean sequence to a net profit of $46.80/ha for the cotton-soybean-cotton sequence. The relative profitability of various rotations changed as nematode densities increased, indicating economic thresholds for recommending alternative crop sequences. The utility and power of quantitative optimization was demonstrated for comparisons of rotations under different economic assumptions and with other management alternatives.

Assessment of community satisfaction index of population and civil registration office in Malang municipal

NASA Astrophysics Data System (ADS)

Hakim, A. N.

2017-06-01

The demands and needs of the community will be the quality of public services in Malang increased, so that the Government of Malang as organizers and executors of public services must meet these demands. The Municipal Government in its efforts to improve public service performance, forming the regional One Stop Operator (PPTSP) with the goal will be to simplify and improve efficiency in administrative proceedings. But the existence of the one stop service is still not optimal because of the persistence of public complaints about the performance of the one stop service. This study will discuss the performance of services in service counter of Population and Civil Registration through community satisfaction index to measure the service level and the perception of satisfaction and interest to determine which variables are less optimal and need to be improved using IPA method. The results showed that the level of service at the service counter of Population and Civil Registration quite good. Meanwhile, according the results of IPA analysis, there are two important variables for the community on the performance / quality was lacking, namely the service procedure and time.

Balancing income and cost in red deer management.

PubMed

Skonhoft, Anders; Veiberg, Vebjørn; Gauteplass, Asle; Olaussen, Jon Olaf; Meisingset, Erling L; Mysterud, Atle

2013-01-30

This paper presents a bioeconomic analysis of a red deer population within a Norwegian institutional context. This population is managed by a well-defined manager, typically consisting of many landowners operating in a cooperative manner, with the goal of maximizing the present-value hunting related income while taking browsing and grazing damages into account. The red deer population is structured in five categories of animals (calves, female and male yearlings, adult females and adult males). It is shown that differences in the per-animal meat values and survival rates ('biological discounted' values) are instrumental in determining the optimal harvest composition. Fertility plays no direct role. It is argued that this is a general result working in stage-structured models with harvest values. In the numerical illustration it is shown that the optimal harvest pattern stays quite stable under various parameter changes. It is revealed which parameters and harvest restrictions that is most important. We also show that the current harvest pattern involves too much yearling harvest compared with the economically efficient level. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamics of hepatitis C under optimal therapy and sampling based analysis

NASA Astrophysics Data System (ADS)

Pachpute, Gaurav; Chakrabarty, Siddhartha P.

2013-08-01

We examine two models for hepatitis C viral (HCV) dynamics, one for monotherapy with interferon (IFN) and the other for combination therapy with IFN and ribavirin. Optimal therapy for both the models is determined using the steepest gradient method, by defining an objective functional which minimizes infected hepatocyte levels, virion population and side-effects of the drug(s). The optimal therapies for both the models show an initial period of high efficacy, followed by a gradual decline. The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored. We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the dynamics of each set under the optimal therapy already determined. Results show an increase in the percentage of responders (indicated by drop in viral load below detection levels) in case of combination therapy (72%) as compared to monotherapy (57%). Statistical tests performed to study correlations between sample parameters and time required for the viral load to fall below detection level, show a strong monotonic correlation with the death rate of infected hepatocytes, identifying it to be an important factor in deciding individual drug regimens.

Application of optimal control strategies to HIV-malaria co-infection dynamics

NASA Astrophysics Data System (ADS)

Fatmawati; Windarto; Hanif, Lathifah

2018-03-01

This paper presents a mathematical model of HIV and malaria co-infection transmission dynamics. Optimal control strategies such as malaria preventive, anti-malaria and antiretroviral (ARV) treatments are considered into the model to reduce the co-infection. First, we studied the existence and stability of equilibria of the presented model without control variables. The model has four equilibria, namely the disease-free equilibrium, the HIV endemic equilibrium, the malaria endemic equilibrium, and the co-infection equilibrium. We also obtain two basic reproduction ratios corresponding to the diseases. It was found that the disease-free equilibrium is locally asymptotically stable whenever their respective basic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. sic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. Then, the optimal control theory for the model was derived analytically by using Pontryagin Maximum Principle. Numerical simulations of the optimal control strategies are also performed to illustrate the results. From the numerical results, we conclude that the best strategy is to combine the malaria prevention and ARV treatments in order to reduce malaria and HIV co-infection populations.

Optimal allocation of testing resources for statistical simulations

NASA Astrophysics Data System (ADS)

Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

2015-07-01

Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

Determining Global Population Distribution: Methods, Applications and Data

PubMed Central

Balk, D.L.; Deichmann, U.; Yetman, G.; Pozzi, F.; Hay, S.I.; Nelson, A.

2011-01-01

Evaluating the total numbers of people at risk from infectious disease in the world requires not just tabular population data, but data that are spatially explicit and global in extent at a moderate resolution. This review describes the basic methods for constructing estimates of global population distribution with attention to recent advances in improving both spatial and temporal resolution. To evaluate the optimal resolution for the study of disease, the native resolution of the data inputs as well as that of the resulting outputs are discussed. Assumptions used to produce different population data sets are also described, with their implications for the study of infectious disease. Lastly, the application of these population data sets in studies to assess disease distribution and health impacts is reviewed. The data described in this review are distributed in the accompanying DVD. PMID:16647969

The heterogeneous HLA genetic composition of the Brazilian population and its relevance to the optimization of hematopoietic stem cell donor recruitment.

PubMed

Fabreti-Oliveira, R A; Nascimento, E; Fonseca, C G; Santos, M A

2014-08-01

The aim of this study was to investigate the human leukocyte antigen (HLA) molecular variation across the Brazilian population in order to determine possible regional differences, which would be highly relevant to optimizing donor recruitment strategies in hematopoietic stem cell transplantation (HSCT) and understanding the population genetic background of this heterogeneous country. HLA data of 551 HSCT donors from five Brazilian regions were characterized by high-resolution DNA alleles at the HLA-A, -B, -C, -DRB1 and -DQB1 loci and compared with other populations in Brazil and worldwide populations. Allele and haplotype frequencies were estimated. The analysis was performed to assess Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium (LD) among different loci in each recruitment center. Genetic variation was explored through genetic distance analyzed by using a new algorithm based on linear algebra, taking into account geographic regions of Brazil. The results indicated a heterogeneous genetic composition of the Brazilian population, such that HLA allele and haplotype frequencies exhibit different distributions among Brazilian regions, which has important implications for donor matching. In addition, a pronounced differentiation was observed by the absence of clustering of the regional populations in the reduced-dimension space. These data may be useful for increasing donor recruitment with more genetic representativeness in the Brazilian Volunteer Bone Marrow Donors Registry (REDOME). © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Interorganizational networks: fundamental to the Accreditation Canada program.

PubMed

Mitchell, Jonathan I; Nicklin, Wendy; MacDonald, Bernadette

2014-01-01

Within the Canadian healthcare system, the term population-accountable health network defines the use of collective resources to optimize the health of a population through integrated interventions. The leadership of these networks has also been identified as a critical factor, highlighting the need for creative management of resources in determining effective, balanced sets of interventions. In this article, using specific principles embedded in the Accreditation Canada program, the benefits of a network approach are highlighted, including knowledge sharing, improving the consistency of practice through standards, and a broader systems-and-population view of healthcare delivery across the continuum of care. The implications for Canadian health leaders to leverage the benefits of interorganizational networks are discussed.

Transvesical Intra-Abdominal Pressure Measurement in Newborn: What Is the Optimal Saline Volume Instillation?

PubMed

Defontaine, Anne; Tirel, Olivier; Costet, Nathalie; Beuchée, Alain; Ozanne, Bruno; Gaillot, Théophile; Arnaud, Alexis Pierre; Wodey, Eric

2016-02-01

To determine the optimal saline volume bladder instillation to measure intravesical pressure in critically ill newborns weighing less than 4.5 kg, and to establish a reference of intra-abdominal pressure value in this population. Prospective monocentric study. Neonatal ICU and PICU. Newborns, premature or not, weighing less than 4.5 kg who required a urethral catheter. Patients were classified into two groups according to whether they presented a risk factor for intra-abdominal hypertension. Nine intravesical pressure measures per patient were performed after different volume saline instillation. The first one was done without saline instillation and then by increments of 0.5 mL/kg to a maximum of 4 mL/kg. Linear models for repeated measurements of intravesical pressure with unstructured covariance were used to analyze the variation of intravesical pressure measures according to the conditions of measurement (volume instilled). Pairwise comparisons of intravesical pressure adjusted mean values between instillation volumes were done using Tukey tests, corrected for multiple testing to determine an optimal instillation volume. Forty-seven patients with completed measures (nine instillations volumes) were included in the analysis. Mean intravesical pressure values were not significantly different when measured after instillation of 0.5, 1, or 1.5 mL/kg, whereas measures after instillation of 2 mL/kg or more were significantly higher. The median intravesical pressure value in the group without intra-abdominal hypertension risk factor after instillation of 1 mL/kg was 5 mm Hg (2-6 mm Hg). The optimal saline volume bladder instillation to measure intra-abdominal pressure in newborns weighing less than 4.5 kg was 1 mL/kg. Reference intra-abdominal pressure in this population was found to be 5 mm Hg (2-6 mm Hg).

Controlled invasive mechanical ventilation strategies in obese patients undergoing surgery.

PubMed

Maia, Lígia de Albuquerque; Silva, Pedro Leme; Pelosi, Paolo; Rocco, Patricia Rieken Macedo

2017-06-01

The obesity prevalence is increasing in surgical population. As the number of obese surgical patients increases, so does the demand for mechanical ventilation. Nevertheless, ventilatory strategies in this population are challenging, since obesity results in pathophysiological changes in respiratory function. Areas covered: We reviewed the impact of obesity on respiratory system and the effects of controlled invasive mechanical ventilation strategies in obese patients undergoing surgery. To date, there is no consensus regarding the optimal invasive mechanical ventilation strategy for obese surgical patients, and no evidence that possible intraoperative beneficial effects on oxygenation and mechanics translate into better postoperative pulmonary function or improved outcomes. Expert commentary: Before determining the ideal intraoperative ventilation strategy, it is important to analyze the pathophysiology and comorbidities of each obese patient. Protective ventilation with low tidal volume, driving pressure, energy, and mechanical power should be employed during surgery; however, further studies are required to clarify the most effective ventilation strategies, such as the optimal positive end-expiratory pressure and whether recruitment maneuvers minimize lung injury. In this context, an ongoing trial of intraoperative ventilation in obese patients (PROBESE) should help determine the mechanical ventilation strategy that best improves clinical outcome in patients with body mass index≥35kg/m 2 .

Existence and characterization of optimal control in mathematics model of diabetics population

NASA Astrophysics Data System (ADS)

Permatasari, A. H.; Tjahjana, R. H.; Udjiani, T.

2018-03-01

Diabetes is a chronic disease with a huge burden affecting individuals and the whole society. In this paper, we constructed the optimal control mathematical model by applying a strategy to control the development of diabetic population. The constructed mathematical model considers the dynamics of disabled people due to diabetes. Moreover, an optimal control approach is proposed in order to reduce the burden of pre-diabetes. Implementation of control is done by preventing the pre-diabetes develop into diabetics with and without complications. The existence of optimal control and characterization of optimal control is discussed in this paper. Optimal control is characterized by applying the Pontryagin minimum principle. The results indicate that there is an optimal control in optimization problem in mathematics model of diabetic population. The effect of the optimal control variable (prevention) is strongly affected by the number of healthy people.

Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission.

PubMed

Stephenson, Brittany; Lanzas, Cristina; Lenhart, Suzanne; Day, Judy

2017-12-01

The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.

A New Method for Determining Structure Ensemble: Application to a RNA Binding Di-Domain Protein.

PubMed

Liu, Wei; Zhang, Jingfeng; Fan, Jing-Song; Tria, Giancarlo; Grüber, Gerhard; Yang, Daiwen

2016-05-10

Structure ensemble determination is the basis of understanding the structure-function relationship of a multidomain protein with weak domain-domain interactions. Paramagnetic relaxation enhancement has been proven a powerful tool in the study of structure ensembles, but there exist a number of challenges such as spin-label flexibility, domain dynamics, and overfitting. Here we propose a new (to our knowledge) method to describe structure ensembles using a minimal number of conformers. In this method, individual domains are considered rigid; the position of each spin-label conformer and the structure of each protein conformer are defined by three and six orthogonal parameters, respectively. First, the spin-label ensemble is determined by optimizing the positions and populations of spin-label conformers against intradomain paramagnetic relaxation enhancements with a genetic algorithm. Subsequently, the protein structure ensemble is optimized using a more efficient genetic algorithm-based approach and an overfitting indicator, both of which were established in this work. The method was validated using a reference ensemble with a set of conformers whose populations and structures are known. This method was also applied to study the structure ensemble of the tandem di-domain of a poly (U) binding protein. The determined ensemble was supported by small-angle x-ray scattering and nuclear magnetic resonance relaxation data. The ensemble obtained suggests an induced fit mechanism for recognition of target RNA by the protein. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Cost-Effectiveness of Screening Individuals With Cystic Fibrosis for Colorectal Cancer.

PubMed

Gini, Andrea; Zauber, Ann G; Cenin, Dayna R; Omidvari, Amir-Houshang; Hempstead, Sarah E; Fink, Aliza K; Lowenfels, Albert B; Lansdorp-Vogelaar, Iris

2017-12-27

Individuals with cystic fibrosis are at increased risk of colorectal cancer (CRC) compared to the general population, and risk is higher among those who received an organ transplant. We performed a cost-effectiveness analysis to determine optimal CRC screening strategies for patients with cystic fibrosis. We adjusted the existing Microsimulation Screening Analysis-Colon microsimulation model to reflect increased CRC risk and lower life expectancy in patients with cystic fibrosis. Modeling was performed separately for individuals who never received an organ transplant and patients who had received an organ transplant. We modeled 76 colonoscopy screening strategies that varied the age range and screening interval. The optimal screening strategy was determined based on a willingness to pay threshold of $100,000 per life-year gained. Sensitivity and supplementary analyses were performed, including fecal immunochemical test (FIT) as an alternative test, earlier ages of transplantation, and increased rates of colonoscopy complications, to assess whether optimal screening strategies would change. Colonoscopy every 5 years, starting at age 40 years, was the optimal colonoscopy strategy for patients with cystic fibrosis who never received an organ transplant; this strategy prevented 79% of deaths from CRC. Among patients with cystic fibrosis who had received an organ transplant, optimal colonoscopy screening should start at an age of 30 or 35 years, depending on the patient's age at time of transplantation. Annual FIT screening was predicted to be cost-effective for patients with cystic fibrosis. However, the level of accuracy of the FIT in population is not clear. Using a Microsimulation Screening Analysis-Colon microsimulation model, we found screening of patients with cystic fibrosis for CRC to be cost-effective. Due to the higher risk in these patients for CRC, screening should start at an earlier age with a shorter screening interval. The findings of this study (especially those on FIT screening) may be limited by restricted evidence available for patients with cystic fibrosis. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Cost Effectiveness of Screening Individuals With Cystic Fibrosis for Colorectal Cancer.

PubMed

Gini, Andrea; Zauber, Ann G; Cenin, Dayna R; Omidvari, Amir-Houshang; Hempstead, Sarah E; Fink, Aliza K; Lowenfels, Albert B; Lansdorp-Vogelaar, Iris

2018-02-01

Individuals with cystic fibrosis are at increased risk of colorectal cancer (CRC) compared with the general population, and risk is higher among those who received an organ transplant. We performed a cost-effectiveness analysis to determine optimal CRC screening strategies for patients with cystic fibrosis. We adjusted the existing Microsimulation Screening Analysis-Colon model to reflect increased CRC risk and lower life expectancy in patients with cystic fibrosis. Modeling was performed separately for individuals who never received an organ transplant and patients who had received an organ transplant. We modeled 76 colonoscopy screening strategies that varied the age range and screening interval. The optimal screening strategy was determined based on a willingness to pay threshold of $100,000 per life-year gained. Sensitivity and supplementary analyses were performed, including fecal immunochemical test (FIT) as an alternative test, earlier ages of transplantation, and increased rates of colonoscopy complications, to assess if optimal screening strategies would change. Colonoscopy every 5 years, starting at an age of 40 years, was the optimal colonoscopy strategy for patients with cystic fibrosis who never received an organ transplant; this strategy prevented 79% of deaths from CRC. Among patients with cystic fibrosis who had received an organ transplant, optimal colonoscopy screening should start at an age of 30 or 35 years, depending on the patient's age at time of transplantation. Annual FIT screening was predicted to be cost-effective for patients with cystic fibrosis. However, the level of accuracy of the FIT in this population is not clear. Using a Microsimulation Screening Analysis-Colon model, we found screening of patients with cystic fibrosis for CRC to be cost effective. Because of the higher risk of CRC in these patients, screening should start at an earlier age with a shorter screening interval. The findings of this study (especially those on FIT screening) may be limited by restricted evidence available for patients with cystic fibrosis. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

Optimal cutoff points for HOMA-IR and QUICKI in the diagnosis of metabolic syndrome and non-alcoholic fatty liver disease: A population based study.

PubMed

Motamed, Nima; Miresmail, Seyed Javad Haji; Rabiee, Behnam; Keyvani, Hossein; Farahani, Behzad; Maadi, Mansooreh; Zamani, Farhad

2016-03-01

The present study was carried out to determine the optimal cutoff points for homeostatic model assessment (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) in the diagnosis of metabolic syndrome (MetS) and non-alcoholic fatty liver disease (NAFLD). The baseline data of 5511 subjects aged ≥18years of a cohort study in northern Iran were utilized to analyze. Receiver operating characteristic (ROC) analysis was conducted to determine the discriminatory capability of HOMA-IR and QUICKI in the diagnosis of MetS and NAFLD. Youden index was utilized to determine the optimal cutoff points of HOMA-IR and QUICKI in the diagnosis of MetS and NAFLD. The optimal cutoff points for HOMA-IR in the diagnosis of MetS and NAFLD were 2.0 [sensitivity=64.4%, specificity=66.8%] and 1.79 [sensitivity=66.2%, specificity=62.2%] in men and were 2.5 [sensitivity=57.6%, specificity=67.9%] and 1.95 [sensitivity=65.1%, specificity=54.7%] in women respectively. Furthermore, the optimal cutoff points for QUICKI in the diagnosis of MetS and NAFLD were 0.343 [sensitivity=63.7%, specificity=67.8%] and 0.347 [sensitivity=62.9%, specificity=65.0%] in men and were 0.331 [sensitivity=55.7%, specificity=70.7%] and 0.333 [sensitivity=53.2%, specificity=67.7%] in women respectively. Not only the optimal cutoff points of HOMA-IR and QUICKI were different for MetS and NAFLD, but also different cutoff points were obtained for men and women for each of these two conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

Lipid-anthropometric index optimization for insulin sensitivity estimation

NASA Astrophysics Data System (ADS)

Velásquez, J.; Wong, S.; Encalada, L.; Herrera, H.; Severeyn, E.

2015-12-01

Insulin sensitivity (IS) is the ability of cells to react due to insulińs presence; when this ability is diminished, low insulin sensitivity or insulin resistance (IR) is considered. IR had been related to other metabolic disorders as metabolic syndrome (MS), obesity, dyslipidemia and diabetes. IS can be determined using direct or indirect methods. The indirect methods are less accurate and invasive than direct and they use glucose and insulin values from oral glucose tolerance test (OGTT). The accuracy is established by comparison using spearman rank correlation coefficient between direct and indirect method. This paper aims to propose a lipid-anthropometric index which offers acceptable correlation to insulin sensitivity index for different populations (DB1=MS subjects, DB2=sedentary without MS subjects and DB3=marathoners subjects) without to use OGTT glucose and insulin values. The proposed method is parametrically optimized through a random cross-validation, using the spearman rank correlation as comparator with CAUMO method. CAUMO is an indirect method designed from a simplification of the minimal model intravenous glucose tolerance test direct method (MINMOD-IGTT) and with acceptable correlation (0.89). The results show that the proposed optimized method got a better correlation with CAUMO in all populations compared to non-optimized. On the other hand, it was observed that the optimized method has better correlation with CAUMO in DB2 and DB3 groups than HOMA-IR method, which is the most widely used for diagnosing insulin resistance. The optimized propose method could detect incipient insulin resistance, when classify as insulin resistant subjects that present impaired postprandial insulin and glucose values.

Dosage optimization in positron emission tomography: state-of-the-art methods and future prospects

PubMed Central

Karakatsanis, Nicolas A; Fokou, Eleni; Tsoumpas, Charalampos

2015-01-01

Positron emission tomography (PET) is widely used nowadays for tumor staging and therapy response in the clinic. However, average PET radiation exposure has increased due to higher PET utilization. This study aims to review state-of-the-art PET tracer dosage optimization methods after accounting for the effects of human body attenuation and scan protocol parameters on the counting rate. In particular, the relationship between the noise equivalent count rate (NECR) and the dosage (NECR-dosage curve) for a range of clinical PET systems and body attenuation sizes will be systematically studied to prospectively estimate the minimum dosage required for sufficiently high NECR. The optimization criterion can be determined either as a function of the peak of the NECR-dosage curve or as a fixed NECR score when NECR uniformity across a patient population is important. In addition, the systematic NECR assessments within a controllable environment of realistic simulations and phantom experiments can lead to a NECR-dosage response model, capable of predicting the optimal dosage for every individual PET scan. Unlike conventional guidelines suggesting considerably large dosage levels for obese patients, NECR-based optimization recommends: i) moderate dosage to achieve 90% of peak NECR for obese patients, ii) considerable dosage reduction for slimmer patients such that uniform NECR is attained across the patient population, and iii) prolongation of scans for PET/MR protocols, where longer PET acquisitions are affordable due to lengthy MR sequences, with motion compensation becoming important then. Finally, the need for continuous adaptation of dosage optimization to emerging technologies will be discussed. PMID:26550543

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Analysis and optimization of population annealing

NASA Astrophysics Data System (ADS)

Amey, Christopher; Machta, Jonathan

2018-03-01

Population annealing is an easily parallelizable sequential Monte Carlo algorithm that is well suited for simulating the equilibrium properties of systems with rough free-energy landscapes. In this work we seek to understand and improve the performance of population annealing. We derive several useful relations between quantities that describe the performance of population annealing and use these relations to suggest methods to optimize the algorithm. These optimization methods were tested by performing large-scale simulations of the three-dimensional (3D) Edwards-Anderson (Ising) spin glass and measuring several observables. The optimization methods were found to substantially decrease the amount of computational work necessary as compared to previously used, unoptimized versions of population annealing. We also obtain more accurate values of several important observables for the 3D Edwards-Anderson model.

Optimal Therapy Scheduling Based on a Pair of Collaterally Sensitive Drugs.

PubMed

Yoon, Nara; Vander Velde, Robert; Marusyk, Andriy; Scott, Jacob G

2018-05-07

Despite major strides in the treatment of cancer, the development of drug resistance remains a major hurdle. One strategy which has been proposed to address this is the sequential application of drug therapies where resistance to one drug induces sensitivity to another drug, a concept called collateral sensitivity. The optimal timing of drug switching in these situations, however, remains unknown. To study this, we developed a dynamical model of sequential therapy on heterogeneous tumors comprised of resistant and sensitive cells. A pair of drugs (DrugA, DrugB) are utilized and are periodically switched during therapy. Assuming resistant cells to one drug are collaterally sensitive to the opposing drug, we classified cancer cells into two groups, [Formula: see text] and [Formula: see text], each of which is a subpopulation of cells resistant to the indicated drug and concurrently sensitive to the other, and we subsequently explored the resulting population dynamics. Specifically, based on a system of ordinary differential equations for [Formula: see text] and [Formula: see text], we determined that the optimal treatment strategy consists of two stages: an initial stage in which a chosen effective drug is utilized until a specific time point, T, and a second stage in which drugs are switched repeatedly, during which each drug is used for a relative duration (i.e., [Formula: see text]-long for DrugA and [Formula: see text]-long for DrugB with [Formula: see text] and [Formula: see text]). We prove that the optimal duration of the initial stage, in which the first drug is administered, T, is shorter than the period in which it remains effective in decreasing the total population, contrary to current clinical intuition. We further analyzed the relationship between population makeup, [Formula: see text], and the effect of each drug. We determine a critical ratio, which we term [Formula: see text], at which the two drugs are equally effective. As the first stage of the optimal strategy is applied, [Formula: see text] changes monotonically to [Formula: see text] and then, during the second stage, remains at [Formula: see text] thereafter. Beyond our analytic results, we explored an individual-based stochastic model and presented the distribution of extinction times for the classes of solutions found. Taken together, our results suggest opportunities to improve therapy scheduling in clinical oncology.

Semi-Supervised Learning of Lift Optimization of Multi-Element Three-Segment Variable Camber Airfoil

NASA Technical Reports Server (NTRS)

Kaul, Upender K.; Nguyen, Nhan T.

2017-01-01

This chapter describes a new intelligent platform for learning optimal designs of morphing wings based on Variable Camber Continuous Trailing Edge Flaps (VCCTEF) in conjunction with a leading edge flap called the Variable Camber Krueger (VCK). The new platform consists of a Computational Fluid Dynamics (CFD) methodology coupled with a semi-supervised learning methodology. The CFD component of the intelligent platform comprises of a full Navier-Stokes solution capability (NASA OVERFLOW solver with Spalart-Allmaras turbulence model) that computes flow over a tri-element inboard NASA Generic Transport Model (GTM) wing section. Various VCCTEF/VCK settings and configurations were considered to explore optimal design for high-lift flight during take-off and landing. To determine globally optimal design of such a system, an extremely large set of CFD simulations is needed. This is not feasible to achieve in practice. To alleviate this problem, a recourse was taken to a semi-supervised learning (SSL) methodology, which is based on manifold regularization techniques. A reasonable space of CFD solutions was populated and then the SSL methodology was used to fit this manifold in its entirety, including the gaps in the manifold where there were no CFD solutions available. The SSL methodology in conjunction with an elastodynamic solver (FiDDLE) was demonstrated in an earlier study involving structural health monitoring. These CFD-SSL methodologies define the new intelligent platform that forms the basis for our search for optimal design of wings. Although the present platform can be used in various other design and operational problems in engineering, this chapter focuses on the high-lift study of the VCK-VCCTEF system. Top few candidate design configurations were identified by solving the CFD problem in a small subset of the design space. The SSL component was trained on the design space, and was then used in a predictive mode to populate a selected set of test points outside of the given design space. The new design test space thus populated was evaluated by using the CFD component by determining the error between the SSL predictions and the true (CFD) solutions, which was found to be small. This demonstrates the proposed CFD-SSL methodologies for isolating the best design of the VCK-VCCTEF system, and it holds promise for quantitatively identifying best designs of flight systems, in general.

Application of a PCR-based approach to identify sex in Hawaiian honeycreepers (Drepanidinae)

USGS Publications Warehouse

Jarvi, S.I.; Banko, P.C.

2000-01-01

The application of molecular techniques to conservation genetics issues can provide important guidance criteria for management of endangered species. The results from this study establish that PCR-based approaches for sex determination developed in other bird species (Griffiths and Tiwari 1995; Griffiths et al. 1996, 1998; Ellegren 1996) can be applied with a high degree of confidence to at least four species of Hawaiian honeycreepers. This provides a rapid, reliable method with which population managers can optimize sex ratios within populations of endangered species that are subject to artificial manipulation through captive breeding programmes or geographic translocation.

Optimal control applied to a model for species augmentation.

PubMed

Bodine, Erin N; Gross, Louis J; Lenhart, Suzanne

2008-10-01

Species augmentation is a method of reducing species loss via augmenting declining or threatened populations with individuals from captive-bred or stable, wild populations. In this paper, we develop a differential equations model and optimal control formulation for a continuous time augmentation of a general declining population. We find a characterization for the optimal control and show numerical results for scenarios of different illustrative parameter sets. The numerical results provide considerably more detail about the exact dynamics of optimal augmentation than can be readily intuited. The work and results presented in this paper are a first step toward building a general theory of population augmentation, which accounts for the complexities inherent in many conservation biology applications.

Experts' Perspectives Toward a Population Health Approach for Children With Medical Complexity.

PubMed

Barnert, Elizabeth S; Coller, Ryan J; Nelson, Bergen B; Thompson, Lindsey R; Chan, Vincent; Padilla, Cesar; Klitzner, Thomas S; Szilagyi, Moira; Chung, Paul J

2017-08-01

Because children with medical complexity (CMC) display very different health trajectories, needs, and resource utilization than other children, it is unclear how well traditional conceptions of population health apply to CMC. We sought to identify key health outcome domains for CMC as a step toward determining core health metrics for this distinct population of children. We conducted and analyzed interviews with 23 diverse national experts on CMC to better understand population health for CMC. Interviewees included child and family advocates, health and social service providers, and research, health systems, and policy leaders. We performed thematic content analyses to identify emergent themes regarding population health for CMC. Overall, interviewees conveyed that defining and measuring population health for CMC is an achievable, worthwhile goal. Qualitative themes from interviews included: 1) CMC share unifying characteristics that could serve as the basis for population health outcomes; 2) optimal health for CMC is child specific and dynamic; 3) health of CMC is intertwined with health of families; 4) social determinants of health are especially important for CMC; and 5) measuring population health for CMC faces serious conceptual and logistical challenges. Experts have taken initial steps in defining the population health of CMC. Population health for CMC involves a dynamic concept of health that is attuned to individual, health-related goals for each child. We propose a framework that can guide the identification and development of population health metrics for CMC. Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Optimal exploitation strategies for an animal population in a Markovian environment: A theory and an example

USGS Publications Warehouse

Anderson, D.R.

1975-01-01

Optimal exploitation strategies were studied for an animal population in a Markovian (stochastic, serially correlated) environment. This is a general case and encompasses a number of important special cases as simplifications. Extensive empirical data on the Mallard (Anas platyrhynchos) were used as an example of general theory. The number of small ponds on the central breeding grounds was used as an index to the state of the environment. A general mathematical model was formulated to provide a synthesis of the existing literature, estimates of parameters developed from an analysis of data, and hypotheses regarding the specific effect of exploitation on total survival. The literature and analysis of data were inconclusive concerning the effect of exploitation on survival. Therefore, two hypotheses were explored: (1) exploitation mortality represents a largely additive form of mortality, and (2) exploitation mortality is compensatory with other forms of mortality, at least to some threshold level. Models incorporating these two hypotheses were formulated as stochastic dynamic programming models and optimal exploitation strategies were derived numerically on a digital computer. Optimal exploitation strategies were found to exist under the rather general conditions. Direct feedback control was an integral component in the optimal decision-making process. Optimal exploitation was found to be substantially different depending upon the hypothesis regarding the effect of exploitation on the population. If we assume that exploitation is largely an additive force of mortality in Mallards, then optimal exploitation decisions are a convex function of the size of the breeding population and a linear or slight concave function of the environmental conditions. Under the hypothesis of compensatory mortality forces, optimal exploitation decisions are approximately linearly related to the size of the Mallard breeding population. Dynamic programming is suggested as a very general formulation for realistic solutions to the general optimal exploitation problem. The concepts of state vectors and stage transformations are completely general. Populations can be modeled stochastically and the objective function can include extra-biological factors. The optimal level of exploitation in year t must be based on the observed size of the population and the state of the environment in year t unless the dynamics of the population, the state of the environment, and the result of the exploitation decisions are completely deterministic. Exploitation based on an average harvest, or harvest rate, or designed to maintain a constant breeding population size is inefficient.

A traditional and a less-invasive robust design: choices in optimizing effort allocation for seabird population studies

USGS Publications Warehouse

Converse, S.J.; Kendall, W.L.; Doherty, P.F.; Naughton, M.B.; Hines, J.E.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

For many animal populations, one or more life stages are not accessible to sampling, and therefore an unobservable state is created. For colonially-breeding populations, this unobservable state could represent the subset of adult breeders that have foregone breeding in a given year. This situation applies to many seabird populations, notably albatrosses, where skipped breeders are either absent from the colony, or are present but difficult to capture or correctly assign to breeding state. Kendall et al. have proposed design strategies for investigations of seabird demography where such temporary emigration occurs, suggesting the use of the robust design to permit the estimation of time-dependent parameters and to increase the precision of estimates from multi-state models. A traditional robust design, where animals are subject to capture multiple times in a sampling season, is feasible in many cases. However, due to concerns that multiple captures per season could cause undue disturbance to animals, Kendall et al. developed a less-invasive robust design (LIRD), where initial captures are followed by an assessment of the ratio of marked-to-unmarked birds in the population or sampled plot. This approach has recently been applied in the Northwestern Hawaiian Islands to populations of Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses. In this paper, we outline the LIRD and its application to seabird population studies. We then describe an approach to determining optimal allocation of sampling effort in which we consider a non-robust design option (nRD), and variations of both the traditional robust design (RD), and the LIRD. Variations we considered included the number of secondary sampling occasions for the RD and the amount of total effort allocated to the marked-to-unmarked ratio assessment for the LIRD. We used simulations, informed by early data from the Hawaiian study, to address optimal study design for our example cases. We found that the LIRD performed as well or nearly as well as certain variations of the RD in terms of root mean square error, especially when relatively little of the total effort was allocated to the assessment of the marked-to-unmarked ratio versus to initial captures. For the RD, we found no clear benefit of using 2, 4, or 6 secondary sampling occasions per year, though this result will depend on the relative effort costs of captures versus recaptures and on the length of the study. We also found that field-readable bands, which may be affixed to birds in addition to standard metal bands, will be beneficial in longer-term studies of albatrosses in the Northwestern Hawaiian Islands. Field-readable bands reduce the effort cost of recapturing individuals, and in the long-term this cost reduction can offset the additional effort expended in affixing the bands. Finally, our approach to determining optimal study design can be generally applied by researchers, with little seed data, to design their studies at the outset.

Determining when to change course in management actions.

PubMed

Ng, Chooi Fei; McCarthy, Michael A; Martin, Tara G; Possingham, Hugh P

2014-12-01

Time is of the essence in conservation biology. To secure the persistence of a species, we need to understand how to balance time spent among different management actions. A new and simple method to test the efficacy of a range of conservation actions is required. Thus, we devised a general theoretical framework to help determine whether to test a new action and when to cease a trial and revert to an existing action if the new action did not perform well. The framework involves constructing a general population model under the different management actions and specifying a management objective. By maximizing the management objective, we could generate an analytical solution that identifies the optimal timing of when to change management action. We applied the analytical solution to the case of the Christmas Island pipistrelle bat (Pipistrelle murrayi), a species for which captive breeding might have prevented its extinction. For this case, we used our model to determine whether to start a captive breeding program and when to stop a captive breeding program and revert to managing the species in the wild, given that the management goal is to maximize the chance of reaching a target wild population size. For the pipistrelle bat, captive breeding was to start immediately and it was desirable to place the species in captivity for the entire management period. The optimal time to revert to managing the species in the wild was driven by several key parameters, including the management goal, management time frame, and the growth rates of the population under different management actions. Knowing when to change management actions can help conservation managers' act in a timely fashion to avoid species extinction. © 2014 Society for Conservation Biology.

Contribution to the development of a food guide in Benin: linear programming for the optimization of local diets.

PubMed

Levesque, Sarah; Delisle, Hélène; Agueh, Victoire

2015-03-01

Food guides are important tools for nutrition education. While developing a food guide in Benin, the objective was to determine the daily number of servings per food group and the portion sizes of common foods to be recommended. Linear programming (LP) was used to determine, for each predefined food group, the optimal number and size of servings of commonly consumed foods. Two types of constraints were introduced into the LP models: (i) WHO/FAO Recommended Nutrient Intakes and dietary guidelines for the prevention of chronic diseases; and (ii) dietary patterns based on local food consumption data recently collected in southern Benin in 541 adults. Dietary intakes of the upper tertile of participants for diet quality based on prevention and micronutrient adequacy scores were used in the LP algorithms. Southern area of the Republic of Benin. Local key-players in nutrition (n 30) from the government, academic institutions, international organizations and civil society were partners in the development of the food guide directed at the population. The number of servings per food group and the portion size for eight age-sex groups were determined. For four limiting micronutrients (Fe, Ca, folate and Zn), local diets could be optimized to meet only 70 % of the Recommended Nutrient Intakes, not 100 %. It was possible to determine the daily number of servings and the portion sizes of common foods that can be recommended in Benin with the help of LP to optimize local diets, although Recommended Nutrient Intakes were not fully met for a few critical micronutrients.

Behavioral responses in structured populations pave the way to group optimality.

PubMed

Akçay, Erol; Van Cleve, Jeremy

2012-02-01

An unresolved controversy regarding social behaviors is exemplified when natural selection might lead to behaviors that maximize fitness at the social-group level but are costly at the individual level. Except for the special case of groups of clones, we do not have a general understanding of how and when group-optimal behaviors evolve, especially when the behaviors in question are flexible. To address this question, we develop a general model that integrates behavioral plasticity in social interactions with the action of natural selection in structured populations. We find that group-optimal behaviors can evolve, even without clonal groups, if individuals exhibit appropriate behavioral responses to each other's actions. The evolution of such behavioral responses, in turn, is predicated on the nature of the proximate behavioral mechanisms. We model a particular class of proximate mechanisms, prosocial preferences, and find that such preferences evolve to sustain maximum group benefit under certain levels of relatedness and certain ecological conditions. Thus, our model demonstrates the fundamental interplay between behavioral responses and relatedness in determining the course of social evolution. We also highlight the crucial role of proximate mechanisms such as prosocial preferences in the evolution of behavioral responses and in facilitating evolutionary transitions in individuality.

Optimizing cryopreservation of human spermatogonial stem cells: comparing the effectiveness of testicular tissue and single cell suspension cryopreservation

PubMed Central

Yango, Pamela; Altman, Eran; Smith, James F.; Klatsky, Peter C.; Tran, Nam D.

2015-01-01

Objective To determine whether optimal human spermatogonial stem cell (SSC) cryopreservation is best achieved with testicular tissue or single cell suspension cryopreservation. This study compares the effectiveness between these two approaches by using testicular SSEA-4+ cells, a known population containing SSCs. Design In vitro human testicular tissues. Setting Academic research unit. Patients Adult testicular tissues (n = 4) collected from subjects with normal spermatogenesis and normal fetal testicular tissues (n = 3). Intervention(s) Testicular tissue vs. single cell suspension cryopreservation. Main Outcome Measures Cell viability, total cell recovery per milligram of tissue, as well as, viable and SSEA-4+ cell recovery. Results Single cell suspension cryopreservation yielded higher recovery of SSEA-4+ cells enriched in adult SSCs whereas fetal SSEA-4+ cell recovery was similar between testicular tissue and single cell suspension cryopreservation. Conclusions Adult and fetal human SSEA-4+ populations exhibited differential sensitivity to cryopreservation based on whether they were cryopreserved in situ as testicular tissues or as single cells. Thus, optimal preservation of human SSCs depends on the patient age, type of samples cryopreserved, and end points of therapeutic applications. PMID:25241367

Optimal exploitation strategies for an animal population in a stochastic serially correlated environment

USGS Publications Warehouse

Anderson, D.R.

1974-01-01

Optimal exploitation strategies were studied for an animal population in a stochastic, serially correlated environment. This is a general case and encompasses a number of important cases as simplifications. Data on the mallard (Anas platyrhynchos) were used to explore the exploitation strategies and test several hypotheses because relatively much is known concerning the life history and general ecology of this species and extensive empirical data are available for analysis. The number of small ponds on the central breeding grounds was used as an index to the state of the environment. Desirable properties of an optimal exploitation strategy were defined. A mathematical model was formulated to provide a synthesis of the existing literature, estimates of parameters developed from an analysis of data, and hypotheses regarding the specific effect of exploitation on total survival. Both the literature and the analysis of data were inconclusive concerning the effect of exploitation on survival. Therefore, alternative hypotheses were formulated: (1) exploitation mortality represents a largely additive form of mortality, or (2 ) exploitation mortality is compensatory with other forms of mortality, at least to some threshold level. Models incorporating these two hypotheses were formulated as stochastic dynamic programming models and optimal exploitation strategies were derived numerically on a digital computer. Optimal exploitation strategies were found to exist under rather general conditions. Direct feedback control was an integral component in the optimal decision-making process. Optimal exploitation was found to be substantially different depending upon the hypothesis regarding the effect of exploitation on the population. Assuming that exploitation is largely an additive force of mortality, optimal exploitation decisions are a convex function of the size of the breeding population and a linear or slightly concave function of the environmental conditions. Optimal exploitation under this hypothesis tends to reduce the variance of the size of the population. Under the hypothesis of compensatory mortality forces, optimal exploitation decisions are approximately linearly related to the size of the breeding population. Environmental variables may be somewhat more important than the size of the breeding population to the production of young mallards. In contrast, the size of the breeding population appears to be more important in the exploitation process than is the state of the environment. The form of the exploitation strategy appears to be relatively insensitive to small changes in the production rate. In general, the relative importance of the size of the breeding population may decrease as fecundity increases. The optimal level of exploitation in year t must be based on the observed size of the population and the state of the environment in year t unless the dynamics of the population, the state of the environment, and the result of the exploitation decisions are completely deterministic. Exploitation based on an average harvest, harvest rate, or designed to maintain a constant breeding population size is inefficient.

Environmental osmolality influences sperm motility activation in an anuran amphibian.

PubMed

Byrne, P G; Dunne, C; Munn, A J; Silla, A J

2015-03-01

Evolutionary theory predicts that selection will favour sperm traits that maximize fertilization success in local fertilization environments. In externally fertilizing species, osmolality of the fertilization medium is known to play a critical role in activating sperm motility, but there remains limited evidence for adaptive responses to local osmotic environments. In this study, we used a split-sample experimental design and computer-assisted sperm analysis to (i) determine the optimal medium osmolality for sperm activation (% sperm motility and sperm velocity) in male common eastern froglets (Crinia signifera), (ii) test for among-population variation in percentage sperm motility and sperm velocity at various activation-medium osmolalities and (iii) test for among-population covariation between sperm performance and environmental osmolality. Frogs were obtained from nine populations that differed in environmental osmolality, and sperm samples of males from different populations were subjected to a range of activation-medium osmolalities. Percentage sperm motility was optimal between 10 and 50 mOsm kg(-1) , and sperm velocity was optimal between 10 and 100 mOsm kg(-1) , indicating that C. signifera has evolved sperm that can function across a broad range of osmolalities. As predicted, there was significant among-population variation in sperm performance. Furthermore, there was a significant interaction between activation-medium osmolality and environmental osmolality, indicating that frogs from populations with higher environmental osmolality produced sperm that performed better at higher osmolalities in vitro. This finding may reflect phenotypic plasticity in sperm functioning, or genetic divergence resulting from spatial variation in the strength of directional selection. Both of these explanations are consistent with evolutionary theory, providing some of the first empirical evidence that local osmotic environments can favour adaptive sperm motility responses in species that use an external mode of fertilization. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Determination of the optimal cutoff value for a serological assay: an example using the Johne's Absorbed EIA.

PubMed Central

Ridge, S E; Vizard, A L

1993-01-01

Traditionally, in order to improve diagnostic accuracy, existing tests have been replaced with newly developed diagnostic tests with superior sensitivity and specificity. However, it is possible to improve existing tests by altering the cutoff value chosen to distinguish infected individuals from uninfected individuals. This paper uses data obtained from an investigation of the operating characteristics of the Johne's Absorbed EIA to demonstrate a method of determining a preferred cutoff value from several potentially useful cutoff settings. A method of determining the financial gain from using the preferred rather than the current cutoff value and a decision analysis method to assist in determining the optimal cutoff value when critical population parameters are not known with certainty are demonstrated. The results of this study indicate that the currently recommended cutoff value for the Johne's Absorbed EIA is only close to optimal when the disease prevalence is very low and false-positive test results are deemed to be very costly. In other situations, there were considerable financial advantages to using cutoff values calculated to maximize the benefit of testing. It is probable that the current cutoff values for other diagnostic tests may not be the most appropriate for every testing situation. This paper offers methods for identifying the cutoff value that maximizes the benefit of medical and veterinary diagnostic tests. PMID:8501227

Synthesis, X-ray diffraction method, spectroscopic characterization (FT-IR, 1H and 13C NMR), antimicrobial activity, Hirshfeld surface analysis and DFT computations of novel sulfonamide derivatives

NASA Astrophysics Data System (ADS)

Demircioğlu, Zeynep; Özdemir, Fethi Ahmet; Dayan, Osman; Şerbetçi, Zafer; Özdemir, Namık

2018-06-01

Synthesized compounds of N-(2-aminophenyl)benzenesulfonamide 1 and (Z)-N-(2-((2-nitrobenzylidene)amino)phenyl)benzenesulfonamide 2 were characterized by antimicrobial activity, FT-IR, 1H and 13C NMR. Two new Schiff base ligands containing aromatic sulfonamide fragment of (Z)-N-(2-((3-nitrobenzylidene)amino)phenyl)benzenesulfonamide 3 and (Z)-N-(2-((4-nitrobenzylidene)amino)phenyl)benzenesulfonamide 4 were synthesized and investigated by spectroscopic techniques including 1H and 13C NMR, FT-IR, single crystal X-ray diffraction, Hirshfeld surface, theoretical method analyses and by antimicrobial activity. The molecular geometry obtained from the X-ray structure determination was optimized Density Functional Theory (DFT/B3LYP) method with the 6-311++G(d,p) basis set in ground state. From the optimized geometry of the molecules of 3 and 4, the geometric parameters, vibrational wavenumbers and chemical shifts were computed. The optimized geometry results, which were well represented the X-ray data, were shown that the chosen of DFT/B3LYP 6-311G++(d,p) was a successful choice. After a successful optimization, frontier molecular orbitals, chemical activity, non-linear optical properties (NLO), molecular electrostatic mep (MEP), Mulliken population method, natural population analysis (NPA) and natural bond orbital analysis (NBO), which cannot be obtained experimentally, were calculated and investigated.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

NASA Astrophysics Data System (ADS)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE PAGES

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; ...

2018-05-29

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

Optimal Harvesting in an Age-Structured Predator-Prey Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fister, K. Renee; Lenhart, Suzanne

2006-06-15

We investigate optimal harvesting control in a predator-prey model in which the prey population is represented by a first-order partial differential equation with age-structure and the predator population is represented by an ordinary differential equation in time. The controls are the proportions of the populations to be harvested, and the objective functional represents the profit from harvesting. The existence and uniqueness of the optimal control pair are established.

The technical report on sodium intake and cardiovascular disease in low- and middle-income countries by the joint working group of the World Heart Federation, the European Society of Hypertension and the European Public Health Association.

PubMed

Mancia, Giuseppe; Oparil, Suzanne; Whelton, Paul K; McKee, Martin; Dominiczak, Anna; Luft, Friedrich C; AlHabib, Khalid; Lanas, Fernando; Damasceno, Albertino; Prabhakaran, Dorairaj; La Torre, Giuseppe; Weber, Michael; O'Donnell, Martin; Smith, Sidney C; Narula, Jagat

2017-03-07

Ingestion of sodium is essential to health, but excess sodium intake is a risk factor for hypertension and cardiovascular disease. Defining an optimal range of sodium intake in populations has been challenging and controversial. Clinical trials evaluating the effect of sodium reduction on blood pressure have shown blood pressure lowering effects down to sodium intake of less than 1.5 g/day. Findings from these blood pressure trials form the basis for current guideline recommendations to reduce sodium intake to less than 2.3 g/day. However, these clinical trials employed interventions that are not feasible for population-wide implementation (i.e. feeding studies or intensive behavioural interventions), particularly in low and middle-income countries. Prospective cohort studies have identified the optimal range of sodium intake to reside in the moderate range (3-5 g/day), where the risk of cardiovascular disease and death is lowest. Therefore, there is consistent evidence from clinical trials and observational studies to support reducing sodium intake to less than 5 g/day in populations, but inconsistent evidence for further reductions below a moderate intake range (3-5 g/day). Unfortunately, there are no large randomized controlled trials comparing low sodium intake (< 3 g/day) to moderate sodium intake (3-5 g/day) in general populations to determine the net clinical effects of low sodium intake. Until such trials are completed, it is likely that controversy about optimal sodium intake range will continue. This working group calls for the completion of large definitive clinical trials to clarify the range of sodium intake for optimal cardiovascular health within the moderate to low intake range. We support interventions to reduce sodium intake in populations who consume high sodium intake (> 5 g/day), which should be embedded within an overall healthy dietary pattern. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For Permissions, please email: journals.permissions@oup.com.

All Might Have Won, But Not All Have the Prize: Optimal Treatment for Substance Abuse Among Adolescents with Conduct Problems

PubMed Central

Spas, Jayson; Ramsey, Susan; Paiva, Andrea L.; Stein, L.A.R.

2012-01-01

Considerable evidence from the literature on treatment outcomes indicates that substance abuse treatment among adolescents with conduct problems varies widely. Treatments commonly used among this population are cognitive-behavioral therapy (CBT), 12-step facilitation, multisystemic therapy (MST), psychoeducation (PE), and motivational interviewing (MI). This manuscript thoroughly and systematically reviews the available literature to determine which treatment is optimal for substance-abusing adolescents with conduct problems. Results suggest that although there are several evidence-based and empirically supported treatments, those that incorporate family-based intervention consistently provide the most positive treatment outcomes. In particular, this review further reveals that although many interventions have gained empirical support over the years, only one holds the prize as being the optimal treatment of choice for substance abuse treatment among adolescents with conduct problems. PMID:23170066

Statistical considerations in monitoring birds over large areas

USGS Publications Warehouse

Johnson, D.H.

2000-01-01

The proper design of a monitoring effort depends primarily on the objectives desired, constrained by the resources available to conduct the work. Typically, managers have numerous objectives, such as determining abundance of the species, detecting changes in population size, evaluating responses to management activities, and assessing habitat associations. A design that is optimal for one objective will likely not be optimal for others. Careful consideration of the importance of the competing objectives may lead to a design that adequately addresses the priority concerns, although it may not be optimal for any individual objective. Poor design or inadequate sample sizes may result in such weak conclusions that the effort is wasted. Statistical expertise can be used at several stages, such as estimating power of certain hypothesis tests, but is perhaps most useful in fundamental considerations of describing objectives and designing sampling plans.

Design optimization of an axial-field eddy-current magnetic coupling based on magneto-thermal analytical model

NASA Astrophysics Data System (ADS)

Fontchastagner, Julien; Lubin, Thierry; Mezani, Smaïl; Takorabet, Noureddine

2018-03-01

This paper presents a design optimization of an axial-flux eddy-current magnetic coupling. The design procedure is based on a torque formula derived from a 3D analytical model and a population algorithm method. The main objective of this paper is to determine the best design in terms of magnets volume in order to transmit a torque between two movers, while ensuring a low slip speed and a good efficiency. The torque formula is very accurate and computationally efficient, and is valid for any slip speed values. Nevertheless, in order to solve more realistic problems, and then, take into account the thermal effects on the torque value, a thermal model based on convection heat transfer coefficients is also established and used in the design optimization procedure. Results show the effectiveness of the proposed methodology.

Dosing strategies to optimize currently available anti-MRSA treatment options (Part 1: IV options).

PubMed

Hall, Ronald G; Thatcher, Michael; Wei, Wei; Varghese, Shibin; Varughese, Lincy; Ndiulor, Michelle; Payne, Kenna D

2017-05-01

Methicillin-resistant Staphylococcus aureus (MRSA) continues to be a predominant pathogen resulting in significant morbidity and mortality. Optimal dosing of anti-MRSA agents is needed to help prevent the development of antimicrobial resistance and to increase the likelihood of a favorable clinical outcome. Areas covered: This review summarizes the available data for antimicrobials routinely used for MRSA infections that are not administered orally or topically. We make recommendations and highlight the current gaps in the literature. A PubMed (1966 - Present) search was performed to identify relevant literature for this review. Expert commentary: Improvements in MIC determination and therapeutic drug monitoring are needed to fully implement individualized dosing that optimizes antimicrobial pharmacodynamics.Additional data will become available for these agents in regards to effectiveness for severe MRSA infections and pharmacokinetic data for special patient populations.

[On the relationship between population and means of subsistence].

PubMed

Li, J

1984-01-29

Population is the basis of all social activites and social production. Population growth and development must have a definite means of subsistence to meet its cultural and material needs. The larger the population of a country, the greater is its demand for consumer goods and, likewise, the yield of its means of subsistence should be greater. Population brings about the unification of production and consumption. Furthermore, the ratio of population to the means of subsistence must be maintained at an appropriate level. Population growth must be slower then the growth of the means of subsistence in order to ensure continuous economic expansion and population increase. However, there are some people, notably Malthus, who believe that the balance between population growth and the means of subsistence should be equal. It is crucial to note differences between Marxist and Malthusian points of view. The basic outlook on the nature of the relationship between population and the means of subsistence is different. For Malthusians, it is a matter of the number of people and the quantity of the means of subsistence. For Marxists, the relationship is a historically determined social relationship. For Malthusians, population development is the primary force behind social development, i.e., the imbalance between population and the means of subsistence stems from social ills. Marxists differ from this in believing that population cannot be divorced from material production. Malthusians believe that population surplus derives from a population increase that is greater than an increase in the means of subsistence. Marxists believe a population surplus is also an historically determined social relationship. The Malthusian outlook for the future of population and the means of subsistence is pessimistic, whereas the Marxian view embodies the optimism of revolution.

Population Genetic Analysis of Theileria annulata from Six Geographical Regions in China, Determined on the Basis of Micro- and Mini-satellite Markers

PubMed Central

Yin, Fangyuan; Liu, Zhijie; Liu, Junlong; Liu, Aihong; Salih, Diaeldin A.; Li, Youquan; Liu, Guangyuan; Luo, Jianxun; Guan, Guiquan; Yin, Hong

2018-01-01

Theileria annulata, a tick-borne apicomplexan protozoan, causes a lymphoproliferative disease of cattle with high prevalence in tropical and sub-tropical regions. Understanding the genetic diversity and structure of local populations will provide more fundamental knowledge for the population genetics and epidemics of protozoa. In this study, 78 samples of T. annulata collected from cattle/yaks representing 6 different geographic populations in China were genotyped using eight micro- and mini-satellite markers. High genetic variation within population, moderate genetic differentiation, and high level of diversity co-occurring with significant linkage disequilibrium were observed, which indicates there is gene flow between these populations in spite of the existence of reproductive and geographical barriers among populations. Furthermore, some degree of genetic differentiation was also found between samples from China and Oman. These findings provide a first glimpse of the genetic diversity of the T. annulata populations in China, and might contribute to the knowledge of distribution, dynamics, and epidemiology of T. annulata populations and optimize the management strategies for control. PMID:29515624

A new logistic dynamic particle swarm optimization algorithm based on random topology.

PubMed

Ni, Qingjian; Deng, Jianming

2013-01-01

Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

Disease and disaster: Optimal deployment of epidemic control facilities in a spatially heterogeneous population with changing behaviour.

PubMed

Gaythorpe, Katy; Adams, Ben

2016-05-21

Epidemics of water-borne infections often follow natural disasters and extreme weather events that disrupt water management processes. The impact of such epidemics may be reduced by deployment of transmission control facilities such as clinics or decontamination plants. Here we use a relatively simple mathematical model to examine how demographic and environmental heterogeneities, population behaviour, and behavioural change in response to the provision of facilities, combine to determine the optimal configurations of limited numbers of facilities to reduce epidemic size, and endemic prevalence. We show that, if the presence of control facilities does not affect behaviour, a good general rule for responsive deployment to minimise epidemic size is to place them in exactly the locations where they will directly benefit the most people. However, if infected people change their behaviour to seek out treatment then the deployment of facilities offering treatment can lead to complex effects that are difficult to foresee. So careful mathematical analysis is the only way to get a handle on the optimal deployment. Behavioural changes in response to control facilities can also lead to critical facility numbers at which there is a radical change in the optimal configuration. So sequential improvement of a control strategy by adding facilities to an existing optimal configuration does not always produce another optimal configuration. We also show that the pre-emptive deployment of control facilities has conflicting effects. The configurations that minimise endemic prevalence are very different to those that minimise epidemic size. So cost-benefit analysis of strategies to manage endemic prevalence must factor in the frequency of extreme weather events and natural disasters. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimal Resting-Growth Strategies of Microbial Populations in Fluctuating Environments

PubMed Central

Geisel, Nico; Vilar, Jose M. G.; Rubi, J. Miguel

2011-01-01

Bacteria spend most of their lifetime in non-growing states which allow them to survive extended periods of stress and starvation. When environments improve, they must quickly resume growth to maximize their share of limited nutrients. Cells with higher stress resistance often survive longer stress durations at the cost of needing more time to resume growth, a strong disadvantage in competitive environments. Here we analyze the basis of optimal strategies that microorganisms can use to cope with this tradeoff. We explicitly show that the prototypical inverse relation between stress resistance and growth rate can explain much of the different types of behavior observed in stressed microbial populations. Using analytical mathematical methods, we determine the environmental parameters that decide whether cells should remain vegetative upon stress exposure, downregulate their metabolism to an intermediate optimum level, or become dormant. We find that cell-cell variability, or intercellular noise, is consistently beneficial in the presence of extreme environmental fluctuations, and that it provides an efficient population-level mechanism for adaption in a deteriorating environment. Our results reveal key novel aspects of responsive phenotype switching and its role as an adaptive strategy in changing environments. PMID:21525975

[Development of products for the elderly population: vitamin enriched pudding].

PubMed

Vera, M S; de Penna, E W; Bunger, A; Soto, D; Cariaga, L; Fuenzalida, R; Cornejo, E; Lopez, L

1995-03-01

An instant dessert powder, pudding type was developed to be consumed at lunch or dinner time. The dessert was designed to be prepared in skim milk and meets the nutritional needs of elderly people. The dessert contains modified starch, carragenine, vegetal fat, sacharose. Each serving has been enriched with 30% of the daily vitamin requirement advised for adults over 51 years old. The optimized process was carried out according to the Karlsruhe test. Each serving consists of 22g powder prepared in proportion of 18% in skim milk. The optimized dessert powder was controlled by means of physical, chemical and microbiological analyses. The sensory quality was determined in the ready to eat product and the acceptability level was measured in a group of people selected according to the characteristics of the target population. The dessert powder contains 1.1% protein, 5.2% fats, 89.76% carbohidrates, and provides 409 Kcal/100g. Both the sensory and microbiological quality were good and the level of acceptance reached 98%.

Feedback quantum control of molecular electronic population transfer

NASA Astrophysics Data System (ADS)

Bardeen, Christopher J.; Yakovlev, Vladislav V.; Wilson, Kent R.; Carpenter, Scott D.; Weber, Peter M.; Warren, Warren S.

1997-11-01

Feedback quantum control, where the sample `teaches' a computer-controlled arbitrary lightform generator to find the optimal light field, is experimentally demonstrated for a molecular system. Femtosecond pulses tailored by a computer-controlled acousto-optic pulse shaper excite fluorescence from laser dye molecules in solution. Fluorescence and laser power are monitored, and the computer uses the experimental data and a genetic algorithm to optimize population transfer from ground to first excited state. Both efficiency (the ratio of excited state population to laser energy) and effectiveness (total excited state population) are optimized. Potential use as an `automated theory tester' is discussed.

Classification of individual well-being scores for the determination of adverse health and productivity outcomes in employee populations.

PubMed

Shi, Yuyan; Sears, Lindsay E; Coberley, Carter R; Pope, James E

2013-04-01

Adverse health and productivity outcomes have imposed a considerable economic burden on employers. To facilitate optimal worksite intervention designs tailored to differing employee risk levels, the authors established cutoff points for an Individual Well-Being Score (IWBS) based on a global measure of well-being. Cross-sectional associations between IWBS and adverse health and productivity outcomes, including high health care cost, emergency room visits, short-term disability days, absenteeism, presenteeism, low job performance ratings, and low intentions to stay with the employer, were studied in a sample of 11,702 employees from a large employer. Receiver operating characteristics curves were evaluated to detect a single optimal cutoff value of IWBS for predicting 2 or more adverse outcomes. More granular segmentation was achieved by computing relative risks of each adverse outcome from logistic regressions accounting for sociodemographic characteristics. Results showed strong and significant nonlinear associations between IWBS and health and productivity outcomes. An IWBS of 75 was found to be the optimal single cutoff point to discriminate 2 or more adverse outcomes. Logistic regression models found abrupt reductions of relative risk also clustered at IWBS cutoffs of 53, 66, and 88, in addition to 75, which segmented employees into high, high-medium, medium, low-medium, and low risk groups. To determine validity and generalizability, cutoff values were applied in a smaller employee population (N=1853) and confirmed significant differences between risk groups across health and productivity outcomes. The reported segmentation of IWBS into discrete cohorts based on risk of adverse health and productivity outcomes should facilitate well-being comparisons and worksite interventions.

Defining an integrative approach for health promotion and disease prevention: A population health equity framework

PubMed Central

Trinh-Shevrin, Chau; Nadkarni, Smiti; Park, Rebecca; Islam, Nadia; Kwon, Simona C.

2015-01-01

Background Eliminating health disparities in racial ethnic minority and underserved populations requires a paradigm shift from disease-focused biomedical approaches to a health equity framework that aims to achieve optimal health for all by targeting social and structural determinants of health. Methods We describe the concepts and parallel approaches that underpin an integrative population health equity framework. Using a case study approach we present the experience of the NYU Center for the Study of Asian American Health (CSAAH) in applying the framework to guide its work. Results This framework is central to CSAAH’s efforts moving towards a population health equity vision for Asian Americans. Discussion Advancing the health of underserved populations requires community engagement and an understanding of the multilevel contextual factors that influence health. Applying an integrative framework has allowed us to advance health equity for Asian American communities and may serve as a useful framework for other underserved populations. PMID:25981095

Gauging the likelihood of stable cavitation from ultrasound contrast agents

NASA Astrophysics Data System (ADS)

Bader, Kenneth B.; Holland, Christy K.

2013-01-01

The mechanical index (MI) was formulated to gauge the likelihood of adverse bioeffects from inertial cavitation. However, the MI formulation did not consider bubble activity from stable cavitation. This type of bubble activity can be readily nucleated from ultrasound contrast agents (UCAs) and has the potential to promote beneficial bioeffects. Here, the presence of stable cavitation is determined numerically by tracking the onset of subharmonic oscillations within a population of bubbles for frequencies up to 7 MHz and peak rarefactional pressures up to 3 MPa. In addition, the acoustic pressure rupture threshold of an UCA population was determined using the Marmottant model. The threshold for subharmonic emissions of optimally sized bubbles was found to be lower than the inertial cavitation threshold for all frequencies studied. The rupture thresholds of optimally sized UCAs were found to be lower than the threshold for subharmonic emissions for either single cycle or steady state acoustic excitations. Because the thresholds of both subharmonic emissions and UCA rupture are linearly dependent on frequency, an index of the form ICAV = Pr/f (where Pr is the peak rarefactional pressure in MPa and f is the frequency in MHz) was derived to gauge the likelihood of subharmonic emissions due to stable cavitation activity nucleated from UCAs.

Gauging the likelihood of stable cavitation from ultrasound contrast agents.

PubMed

Bader, Kenneth B; Holland, Christy K

2013-01-07

The mechanical index (MI) was formulated to gauge the likelihood of adverse bioeffects from inertial cavitation. However, the MI formulation did not consider bubble activity from stable cavitation. This type of bubble activity can be readily nucleated from ultrasound contrast agents (UCAs) and has the potential to promote beneficial bioeffects. Here, the presence of stable cavitation is determined numerically by tracking the onset of subharmonic oscillations within a population of bubbles for frequencies up to 7 MHz and peak rarefactional pressures up to 3 MPa. In addition, the acoustic pressure rupture threshold of an UCA population was determined using the Marmottant model. The threshold for subharmonic emissions of optimally sized bubbles was found to be lower than the inertial cavitation threshold for all frequencies studied. The rupture thresholds of optimally sized UCAs were found to be lower than the threshold for subharmonic emissions for either single cycle or steady state acoustic excitations. Because the thresholds of both subharmonic emissions and UCA rupture are linearly dependent on frequency, an index of the form I(CAV) = P(r)/f (where P(r) is the peak rarefactional pressure in MPa and f is the frequency in MHz) was derived to gauge the likelihood of subharmonic emissions due to stable cavitation activity nucleated from UCAs.

Gauging the likelihood of stable cavitation from ultrasound contrast agents

PubMed Central

Bader, Kenneth B; Holland, Christy K

2015-01-01

The mechanical index (MI) was formulated to gauge the likelihood of adverse bioeffects from inertial cavitation. However, the MI formulation did not consider bubble activity from stable cavitation. This type of bubble activity can be readily nucleated from ultrasound contrast agents (UCAs) and has the potential to promote beneficial bioeffects. Here, the presence of stable cavitation is determined numerically by tracking the onset of subharmonic oscillations within a population of bubbles for frequencies up to 7 MHz and peak rarefactional pressures up to 3 MPa. In addition, the acoustic pressure rupture threshold of an UCA population was determined using the Marmottant model. The threshold for subharmonic emissions of optimally sized bubbles was found to be lower than the inertial cavitation threshold for all frequencies studied. The rupture thresholds of optimally sized UCAs were found to be lower than the threshold for subharmonic emissions for either single cycle or steady state acoustic excitations. Because the thresholds of both subharmonic emissions and UCA rupture are linearly dependent on frequency, an index of the form ICAV = Pr/f (where Pr is the peak rarefactional pressure in MPa and f is the frequency in MHz) was derived to gauge the likelihood of subharmonic emissions due to stable cavitation activity nucleated from UCAs. PMID:23221109

Optimization of the MINERVA Exoplanet Search Strategy via Simulations

NASA Astrophysics Data System (ADS)

Nava, Chantell; Johnson, Samson; McCrady, Nate; Minerva

2015-01-01

Detection of low-mass exoplanets requires high spectroscopic precision and high observational cadence. MINERVA is a dedicated observatory capable of sub meter-per-second radial velocity precision. As a dedicated observatory, MINERVA can observe with every-clear-night cadence that is essential for low-mass exoplanet detection. However, this cadence complicates the determination of an optimal observing strategy. We simulate MINERVA observations to optimize our observing strategy and maximize exoplanet detections. A dispatch scheduling algorithm provides observations of MINERVA targets every day over a three-year observing campaign. An exoplanet population with a distribution informed by Kepler statistics is assigned to the targets, and radial velocity curves induced by the planets are constructed. We apply a correlated noise model that realistically simulates stellar astrophysical noise sources. The simulated radial velocity data is fed to the MINERVA planet detection code and the expected exoplanet yield is calculated. The full simulation provides a tool to test different strategies for scheduling observations of our targets and optimizing the MINERVA exoplanet search strategy.

An optimal control strategies using vaccination and fogging in dengue fever transmission model

NASA Astrophysics Data System (ADS)

Fitria, Irma; Winarni, Pancahayani, Sigit; Subchan

2017-08-01

This paper discussed regarding a model and an optimal control problem of dengue fever transmission. We classified the model as human and vector (mosquito) population classes. For the human population, there are three subclasses, such as susceptible, infected, and resistant classes. Then, for the vector population, we divided it into wiggler, susceptible, and infected vector classes. Thus, the model consists of six dynamic equations. To minimize the number of dengue fever cases, we designed two optimal control variables in the model, the giving of fogging and vaccination. The objective function of this optimal control problem is to minimize the number of infected human population, the number of vector, and the cost of the controlling efforts. By giving the fogging optimally, the number of vector can be minimized. In this case, we considered the giving of vaccination as a control variable because it is one of the efforts that are being developed to reduce the spreading of dengue fever. We used Pontryagin Minimum Principle to solve the optimal control problem. Furthermore, the numerical simulation results are given to show the effect of the optimal control strategies in order to minimize the epidemic of dengue fever.

Population resizing on fitness improvement genetic algorithm to optimize promotion visit route based on android and google maps API

NASA Astrophysics Data System (ADS)

Listyorini, Tri; Muzid, Syafiul

2017-06-01

The promotion team of Muria Kudus University (UMK) has done annual promotion visit to several senior high schools in Indonesia. The visits were done to numbers of schools in Kudus, Jepara, Demak, Rembang and Purwodadi. To simplify the visit, each visit round is limited to 15 (fifteen) schools. However, the team frequently faces some obstacles during the visit, particularly in determining the route that they should take toward the targeted school. It is due to the long distance or the difficult route to reach the targeted school that leads to elongated travel duration and inefficient fuel cost. To solve these problems, the development of a certain application using heuristic genetic algorithm method based on the dynamic of population size or Population Resizing on Fitness lmprovement Genetic Algorithm (PRoFIGA), was done. This android-based application was developed to make the visit easier and to determine a shorter route for the team, hence, the visiting period will be effective and efficient. The result of this research was an android-based application to determine the shortest route by combining heuristic method and Google Maps Application Programming lnterface (API) that display the route options for the team.

Spatial optimization of prairie dog colonies for black-footed ferret recovery

Treesearch

Michael Bevers; John G. Hof; Daniel W. Uresk; Gregory L. Schenbeck

1997-01-01

A discrete-time reaction-diffusion model for black-footed ferret release, population growth, and dispersal is combined with ferret carrying capacity constraints based on prairie dog population management decisions to form a spatial optimization model. Spatial arrangement of active prairie dog colonies within a ferret reintroduction area is optimized over time for...

Genome-wide analysis of ivermectin response by Onchocerca volvulus reveals that genetic drift and soft selective sweeps contribute to loss of drug sensitivity

PubMed Central

Nana-Djeunga, Hugues C.; Kengne-Ouafo, Jonas A.; Pion, Sébastien D. S.; Bopda, Jean; Kamgno, Joseph; Wanji, Samuel; Che, Hua; Kuesel, Annette C.; Walker, Martin; Basáñez, Maria-Gloria; Boakye, Daniel A.; Osei-Atweneboana, Mike Y.; Boussinesq, Michel; Prichard, Roger K.; Grant, Warwick N.

2017-01-01

Background Treatment of onchocerciasis using mass ivermectin administration has reduced morbidity and transmission throughout Africa and Central/South America. Mass drug administration is likely to exert selection pressure on parasites, and phenotypic and genetic changes in several Onchocerca volvulus populations from Cameroon and Ghana—exposed to more than a decade of regular ivermectin treatment—have raised concern that sub-optimal responses to ivermectin's anti-fecundity effect are becoming more frequent and may spread. Methodology/Principal findings Pooled next generation sequencing (Pool-seq) was used to characterise genetic diversity within and between 108 adult female worms differing in ivermectin treatment history and response. Genome-wide analyses revealed genetic variation that significantly differentiated good responder (GR) and sub-optimal responder (SOR) parasites. These variants were not randomly distributed but clustered in ~31 quantitative trait loci (QTLs), with little overlap in putative QTL position and gene content between the two countries. Published candidate ivermectin SOR genes were largely absent in these regions; QTLs differentiating GR and SOR worms were enriched for genes in molecular pathways associated with neurotransmission, development, and stress responses. Finally, single worm genotyping demonstrated that geographic isolation and genetic change over time (in the presence of drug exposure) had a significantly greater role in shaping genetic diversity than the evolution of SOR. Conclusions/Significance This study is one of the first genome-wide association analyses in a parasitic nematode, and provides insight into the genomics of ivermectin response and population structure of O. volvulus. We argue that ivermectin response is a polygenically-determined quantitative trait (QT) whereby identical or related molecular pathways but not necessarily individual genes are likely to determine the extent of ivermectin response in different parasite populations. Furthermore, we propose that genetic drift rather than genetic selection of SOR is the underlying driver of population differentiation, which has significant implications for the emergence and potential spread of SOR within and between these parasite populations. PMID:28746337

CoAIMs: A Cost-Effective Panel of Ancestry Informative Markers for Determining Continental Origins

PubMed Central

Londin, Eric R.; Keller, Margaret A.; Maista, Cathleen; Smith, Gretchen; Mamounas, Laura A.; Zhang, Ran; Madore, Steven J.; Gwinn, Katrina; Corriveau, Roderick A.

2010-01-01

Background Genetic ancestry is known to impact outcomes of genotype-phenotype studies that are designed to identify risk for common diseases in human populations. Failure to control for population stratification due to genetic ancestry can significantly confound results of disease association studies. Moreover, ancestry is a critical factor in assessing lifetime risk of disease, and can play an important role in optimizing treatment. As modern medicine moves towards using personal genetic information for clinical applications, it is important to determine genetic ancestry in an accurate, cost-effective and efficient manner. Self-identified race is a common method used to track and control for population stratification; however, social constructs of race are not necessarily informative for genetic applications. The use of ancestry informative markers (AIMs) is a more accurate method for determining genetic ancestry for the purposes of population stratification. Methodology/Principal Findings Here we introduce a novel panel of 36 microsatellite (MSAT) AIMs that determines continental admixture proportions. This panel, which we have named Continental Ancestry Informative Markers or CoAIMs, consists of MSAT AIMs that were chosen based upon their measure of genetic variance (Fst), allele frequencies and their suitability for efficient genotyping. Genotype analysis using CoAIMs along with a Bayesian clustering method (STRUCTURE) is able to discern continental origins including Europe/Middle East (Caucasians), East Asia, Africa, Native America, and Oceania. In addition to determining continental ancestry for individuals without significant admixture, we applied CoAIMs to ascertain admixture proportions of individuals of self declared race. Conclusion/Significance CoAIMs can be used to efficiently and effectively determine continental admixture proportions in a sample set. The CoAIMs panel is a valuable resource for genetic researchers performing case-control genetic association studies, as it can control for the confounding effects of population stratification. The MSAT-based approach used here has potential for broad applicability as a cost effective tool toward determining admixture proportions. PMID:20976178

Accounting for connectivity and spatial correlation in the optimal placement of wildlife habitat

Treesearch

John Hof; Curtis H. Flather

1996-01-01

This paper investigates optimization approaches to simultaneously modelling habitat fragmentation and spatial correlation between patch populations. The problem is formulated with habitat connectivity affecting population means and variances, with spatial correlations accounted for in covariance calculations. Population with a pre-specifled confidence level is then...

A comparative genetic analysis of the Irish greyhound population using multilocus DNA fingerprinting, canine single locus minisatellites and canine microsatellites.

PubMed

Sutton, M D; Holmes, N G; Brennan, F B; Binns, M M; Kelly, E P; Duke, E J

1998-06-01

Pairwise analysis of HinfI/33.6 DNA fingerprints from a total of one hundred and fifty-three Irish greyhounds of known pedigree were used to determine band-share estimates of unrelated, first-degree and second-degree relationships. Forty-eight unrelated Irish greyhounds were used to determine allele frequencies for three single-locus minisatellites, and following a preliminary screen, eight of the most polymorphic tetra-nucleotide microsatellites from a panel of 15. The results indicated that both band-share estimates by DNA fingerprinting and microsatellite allele frequencies are highly effective in resolving parentage in this greyhound population, while single-locus minisatellites showed limited polymorphism and could not be used alone for routine parentage testing in this breed. The present study also demonstrated that, to obtain optimal resolution of parentage, sample sets of known pedigree status are required to determine the band-share distribution and/or microsatellite allele frequencies.

Optimizing the health impacts of civil legal aid interventions: the public health framework of medical-legal partnerships.

PubMed

Lawton, Ellen; Tyler, Elizabeth Tobin

2013-07-01

Research documents the significance of the social determinants of health - the social and environmental conditions in which people live, work and play. A critical foundation of these social and environmental conditions are laws and regulations, which construct the environments in which individuals and populations live, influencing how and when people face disease. Increasingly, healthcare providers, public health professionals and lawyers concerned with social determinants are joining forces to form Medical-Legal Partnerships (MLPs) which offer a preventive approach to address the complex social, legal and systemic problems that affect the health of vulnerable populations. Now in more than 500 health and legal institutions across the country, including Rhode Island, MLP is a healthcare delivery model that integrates legal assistance as a vital component of healthcare. This article explores the many benefits of the MLP model for improving patient health, transforming medical and legal practice and institutions and generating policy changes that specifically address health disparities and social determinants.

Optimization of neural network architecture for classification of radar jamming FM signals

NASA Astrophysics Data System (ADS)

Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

2017-05-01

The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Scaling laws between population and facility densities.

PubMed

Um, Jaegon; Son, Seung-Woo; Lee, Sung-Ik; Jeong, Hawoong; Kim, Beom Jun

2009-08-25

When a new facility like a grocery store, a school, or a fire station is planned, its location should ideally be determined by the necessities of people who live nearby. Empirically, it has been found that there exists a positive correlation between facility and population densities. In the present work, we investigate the ideal relation between the population and the facility densities within the framework of an economic mechanism governing microdynamics. In previous studies based on the global optimization of facility positions in minimizing the overall travel distance between people and facilities, it was shown that the density of facility D and that of population rho should follow a simple power law D approximately rho(2/3). In our empirical analysis, on the other hand, the power-law exponent alpha in D approximately rho(alpha) is not a fixed value but spreads in a broad range depending on facility types. To explain this discrepancy in alpha, we propose a model based on economic mechanisms that mimic the competitive balance between the profit of the facilities and the social opportunity cost for populations. Through our simple, microscopically driven model, we show that commercial facilities driven by the profit of the facilities have alpha = 1, whereas public facilities driven by the social opportunity cost have alpha = 2/3. We simulate this model to find the optimal positions of facilities on a real U.S. map and show that the results are consistent with the empirical data.

Seeding the initial population with feasible solutions in metaheuristic optimization of steel trusses

NASA Astrophysics Data System (ADS)

Kazemzadeh Azad, Saeid

2018-01-01

In spite of considerable research work on the development of efficient algorithms for discrete sizing optimization of steel truss structures, only a few studies have addressed non-algorithmic issues affecting the general performance of algorithms. For instance, an important question is whether starting the design optimization from a feasible solution is fruitful or not. This study is an attempt to investigate the effect of seeding the initial population with feasible solutions on the general performance of metaheuristic techniques. To this end, the sensitivity of recently proposed metaheuristic algorithms to the feasibility of initial candidate designs is evaluated through practical discrete sizing of real-size steel truss structures. The numerical experiments indicate that seeding the initial population with feasible solutions can improve the computational efficiency of metaheuristic structural optimization algorithms, especially in the early stages of the optimization. This paves the way for efficient metaheuristic optimization of large-scale structural systems.

Theory of Arachnid Prey Localization

NASA Astrophysics Data System (ADS)

Stürzl, W.; Kempter, R.; van Hemmen, J. L.

2000-06-01

Sand scorpions and many other arachnids locate their prey through highly sensitive slit sensilla at the tips (tarsi) of their eight legs. This sensor array responds to vibrations with stimulus-locked action potentials encoding the target direction. We present a neuronal model to account for stimulus angle determination using a population of second-order neurons, each receiving excitatory input from one tarsus and inhibition from a triad opposite to it. The input opens a time window whose width determines a neuron's firing probability. Stochastic optimization is realized through tuning the balance between excitation and inhibition. The agreement with experiments on the sand scorpion is excellent.

Design and multi-physics optimization of rotary MRF brakes

NASA Astrophysics Data System (ADS)

Topcu, Okan; Taşcıoğlu, Yiğit; Konukseven, Erhan İlhan

2018-03-01

Particle swarm optimization (PSO) is a popular method to solve the optimization problems. However, calculations for each particle will be excessive when the number of particles and complexity of the problem increases. As a result, the execution speed will be too slow to achieve the optimized solution. Thus, this paper proposes an automated design and optimization method for rotary MRF brakes and similar multi-physics problems. A modified PSO algorithm is developed for solving multi-physics engineering optimization problems. The difference between the proposed method and the conventional PSO is to split up the original single population into several subpopulations according to the division of labor. The distribution of tasks and the transfer of information to the next party have been inspired by behaviors of a hunting party. Simulation results show that the proposed modified PSO algorithm can overcome the problem of heavy computational burden of multi-physics problems while improving the accuracy. Wire type, MR fluid type, magnetic core material, and ideal current inputs have been determined by the optimization process. To the best of the authors' knowledge, this multi-physics approach is novel for optimizing rotary MRF brakes and the developed PSO algorithm is capable of solving other multi-physics engineering optimization problems. The proposed method has showed both better performance compared to the conventional PSO and also has provided small, lightweight, high impedance rotary MRF brake designs.

Otoacoustic emissions in the general adult population of Nord-Trøndelag, Norway: III. Relationships with pure-tone hearing thresholds.

PubMed

Engdahl, Bo; Tambs, Kristian; Borchgrevink, Hans M; Hoffman, Howard J

2005-01-01

This study aims to describe the association between otoacoustic emissions (OAEs) and pure-tone hearing thresholds (PTTs) in an unscreened adult population (N =6415), to determine the efficiency by which TEOAEs and DPOAEs can identify ears with elevated PTTs, and to investigate whether a combination of DPOAE and TEOAE responses improves this performance. Associations were examined by linear regression analysis and ANOVA. Test performance was assessed by receiver operator characteristic (ROC) curves. The relation between OAEs and PTTs appeared curvilinear with a moderate degree of non-linearity. Combining DPOAEs and TEOAEs improved performance. Test performance depended on the cut-off thresholds defining elevated PTTs with optimal values between 25 and 45 dB HL, depending on frequency and type of OAE measure. The unique constitution of the present large sample, which reflects the general adult population, makes these results applicable to population-based studies and screening programs.

Kinship-based politics and the optimal size of kin groups

PubMed Central

Hammel, E. A.

2005-01-01

Kin form important political groups, which change in size and relative inequality with demographic shifts. Increases in the rate of population growth increase the size of kin groups but decrease their inequality and vice versa. The optimal size of kin groups may be evaluated from the marginal political product (MPP) of their members. Culture and institutions affect levels and shapes of MPP. Different optimal group sizes, from different perspectives, can be suggested for any MPP schedule. The relative dominance of competing groups is determined by their MPP schedules. Groups driven to extremes of sustainability may react in Malthusian fashion, including fission and fusion, or in Boserupian fashion, altering social technology to accommodate changes in size. The spectrum of alternatives for actors and groups, shaped by existing institutions and natural and cultural selection, is very broad. Nevertheless, selection may result in survival of particular kinds of political structures. PMID:16091466

Kinship-based politics and the optimal size of kin groups.

PubMed

Hammel, E A

2005-08-16

Kin form important political groups, which change in size and relative inequality with demographic shifts. Increases in the rate of population growth increase the size of kin groups but decrease their inequality and vice versa. The optimal size of kin groups may be evaluated from the marginal political product (MPP) of their members. Culture and institutions affect levels and shapes of MPP. Different optimal group sizes, from different perspectives, can be suggested for any MPP schedule. The relative dominance of competing groups is determined by their MPP schedules. Groups driven to extremes of sustainability may react in Malthusian fashion, including fission and fusion, or in Boserupian fashion, altering social technology to accommodate changes in size. The spectrum of alternatives for actors and groups, shaped by existing institutions and natural and cultural selection, is very broad. Nevertheless, selection may result in survival of particular kinds of political structures.

Determining Mutation Rates in Bacterial Populations

PubMed Central

Rosche, William A.; Foster, Patricia L.

2010-01-01

When properly determined, spontaneous mutation rates are a more accurate and biologically meaningful reflection of the underlying mutagenic mechanism than are mutation frequencies. Because bacteria grow exponentially and mutations arise stochastically, methods to estimate mutation rates depend on theoretical models that describe the distribution of mutant numbers among parallel cultures, as in the original Luria-Delbrück fluctuation analysis. An accurate determination of mutation rate depends on understanding the strengths and limitations of these methods, and how to design fluctuation assays to optimize a given method. In this paper we describe a number of methods to estimate mutation rates, give brief accounts of their derivations, and discuss how they behave under various experimental conditions. PMID:10610800

Man in Balance with the Environment: Pollution and the Optimal Population Size

ERIC Educational Resources Information Center

Ultsch, Gordon R.

1973-01-01

Discusses the relationship between population size and pollution, and suggests that the optimal population level toward which we should strive would be that level at which man is in balance with the biosphere in terms of pollution production and degradation, coupled with a harmless steady-state background pollution level. (JR)

Optimizing habitat location for black-tailed prairie dogs in southwestern South Dakota

Treesearch

John Hof; Michael Bevers; Daniel W. Uresk; Gregory L. Schenbeck

2002-01-01

A spatial optimization model was formulated and used to maximize black-tailed prairie dog populations in the Badlands National Park and the Buffalo Gap National Grassland in South Dakota. The choice variables involved the strategic placement of limited additional protected habitat. Population dynamics were captured in formulations that reflected exponential population...

Effect of extreme sea surface temperature events on the demography of an age-structured albatross population.

PubMed

Pardo, Deborah; Jenouvrier, Stéphanie; Weimerskirch, Henri; Barbraud, Christophe

2017-06-19

Climate changes include concurrent changes in environmental mean, variance and extremes, and it is challenging to understand their respective impact on wild populations, especially when contrasted age-dependent responses to climate occur. We assessed how changes in mean and standard deviation of sea surface temperature (SST), frequency and magnitude of warm SST extreme climatic events (ECE) influenced the stochastic population growth rate log( λ s ) and age structure of a black-browed albatross population. For changes in SST around historical levels observed since 1982, changes in standard deviation had a larger (threefold) and negative impact on log( λ s ) compared to changes in mean. By contrast, the mean had a positive impact on log( λ s ). The historical SST mean was lower than the optimal SST value for which log( λ s ) was maximized. Thus, a larger environmental mean increased the occurrence of SST close to this optimum that buffered the negative effect of ECE. This 'climate safety margin' (i.e. difference between optimal and historical climatic conditions) and the specific shape of the population growth rate response to climate for a species determine how ECE affect the population. For a wider range in SST, both the mean and standard deviation had negative impact on log( λ s ), with changes in the mean having a greater effect than the standard deviation. Furthermore, around SST historical levels increases in either mean or standard deviation of the SST distribution led to a younger population, with potentially important conservation implications for black-browed albatrosses.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Cost-effectiveness of interventions to prevent alcohol-related disease and injury in Australia.

PubMed

Cobiac, Linda; Vos, Theo; Doran, Christopher; Wallace, Angela

2009-10-01

To evaluate cost-effectiveness of eight interventions for reducing alcohol-attributable harm and determine the optimal intervention mix. Interventions include volumetric taxation, advertising bans, an increase in minimum legal drinking age, licensing controls on operating hours, brief intervention (with and without general practitioner telemarketing and support), drink driving campaigns, random breath testing and residential treatment for alcohol dependence (with and without naltrexone). Cost-effectiveness is modelled over the life-time of the Australian population in 2003, with all costs and health outcomes evaluated from an Australian health sector perspective. Each intervention is compared with current practice, and the most cost-effective options are then combined to determine the optimal intervention mix. Cost-effectiveness is measured in 2003 Australian dollars per disability adjusted life year averted. Although current alcohol intervention in Australia (random breath testing) is cost-effective, if the current spending of $71 million could be invested in a more cost-effective combination of interventions, more than 10 times the amount of health gain could be achieved. Taken as a package of interventions, all seven preventive interventions would be a cost-effective investment that could lead to substantial improvement in population health; only residential treatment is not cost-effective. Based on current evidence, interventions to reduce harm from alcohol are highly recommended. The potential reduction in costs of treating alcohol-related diseases and injuries mean that substantial improvements in population health can be achieved at a relatively low cost to the health sector. © 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

Continuous Adaptive Population Reduction (CAPR) for Differential Evolution Optimization.

PubMed

Wong, Ieong; Liu, Wenjia; Ho, Chih-Ming; Ding, Xianting

2017-06-01

Differential evolution (DE) has been applied extensively in drug combination optimization studies in the past decade. It allows for identification of desired drug combinations with minimal experimental effort. This article proposes an adaptive population-sizing method for the DE algorithm. Our new method presents improvements in terms of efficiency and convergence over the original DE algorithm and constant stepwise population reduction-based DE algorithm, which would lead to a reduced number of cells and animals required to identify an optimal drug combination. The method continuously adjusts the reduction of the population size in accordance with the stage of the optimization process. Our adaptive scheme limits the population reduction to occur only at the exploitation stage. We believe that continuously adjusting for a more effective population size during the evolutionary process is the major reason for the significant improvement in the convergence speed of the DE algorithm. The performance of the method is evaluated through a set of unimodal and multimodal benchmark functions. In combining with self-adaptive schemes for mutation and crossover constants, this adaptive population reduction method can help shed light on the future direction of a completely parameter tune-free self-adaptive DE algorithm.

An Investigation of the Pareto Distribution as a Model for High Grazing Angle Clutter

DTIC Science & Technology

2011-03-01

radar detection schemes under controlled conditions. Complicated clutter models result in mathematical difficulties in the determination of optimal and...a population [7]. It has been used in the modelling of actuarial data; an example is in excess of loss quotations in insurance [8]. Its usefulness as...UNCLASSIFIED modified Bessel functions, making it difficult to employ in radar detection schemes. The Pareto Distribution is amenable to mathematical

Understrength Air Force Officer Career Fields. A Force Management Approach

DTIC Science & Technology

2005-01-01

LtCol John Crown (DPSA). In addition, we had very helpful interviews with Mr. Vaughan Blackstone (DPAPP) and Mr. Dennis Miller (DPPAO). Also at...econometric impact analysis that was used to determine an optimal bonus amount or target population prior to bonus implementation.15 The success of...problems in managing personnel assignments. First, there is a high " tax " for special-duty jobs that requires them to place personnel officers into

Fetal programming of infant neuromotor development: the generation R study.

PubMed

van Batenburg-Eddes, Tamara; de Groot, Laila; Steegers, Eric A P; Hofman, Albert; Jaddoe, Vincent W V; Verhulst, Frank C; Tiemeier, Henning

2010-02-01

The objective of the study was to examine whether infant neuromotor development is determined by fetal size and body symmetry in the general population. This study was embedded within the Generation R Study, a population-based cohort in Rotterdam. In 2965 fetuses, growth parameters were measured in mid-pregnancy and late pregnancy. After birth, at age 9 to 15 wks, neuromotor development was assessed with an adapted version of Touwen's Neurodevelopmental Examination. Less optimal neuromotor development was defined as a score in the highest tertile. We found that higher fetal weight was beneficial to infant neurodevelopment. A fetus with a 1-SD score higher weight in mid-pregnancy had an 11% lower risk of less optimal neuromotor development (OR: 0.89; 95% CI: 0.82-0.97). Similarly, a fetus with a 1-SD score larger abdominal-to-head circumference (AC/HC) ratio had a 13% lower risk of less optimal neuromotor development (OR: 0.87; 95% CI: 0.79-0.96). These associations were also present in late pregnancy. Our findings show that fetal size and body symmetry in pregnancy are associated with infant neuromotor development. These results suggest that differences in infant neuromotor development, a marker of behavioral and cognitive problems, are at least partly caused by processes occurring early in fetal life.

Managing older patients with head and neck cancer: The non-surgical curative approach.

PubMed

Iqbal, Muhammad Shahid; Dua, Divyanshu; Kelly, Charles; Bossi, Paolo

2018-06-09

Managing older patients with head and neck cancers poses a challenge due to the often reduced levels of physiological reserve, the frequent comorbidities and treatment related toxicity. These factors have implications on speech, breathing and swallowing functions. Treatment management plans in these patients may result in de-intensification strategies and as a result of this, use of non-standard treatments is increasing. There have been published reports that indicate the addition of concurrent systemic therapy to radiation in selected older patients is feasible, and produces outcomes comparable with younger patients. However, some other studies including meta-analyses suggest a lack of real survival benefit with the addition of chemotherapy. So, the key point appears to be the optimal patient selection. Appropriate geriatric and frailty assessments are required to help determine the optimal treatment for older patients with head and neck cancer. Treatment for this population still needs to be well defined and optimized in both modality and intensity. Qualitative studies are also required to address short and long-term post-treatment quality-of-life and survivorship issues in this specific patient population. This review summarizes the evidence available regarding the non-surgical management of older patients with head and neck cancers. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Effects of number of training generations on genomic prediction for various traits in a layer chicken population.

PubMed

Weng, Ziqing; Wolc, Anna; Shen, Xia; Fernando, Rohan L; Dekkers, Jack C M; Arango, Jesus; Settar, Petek; Fulton, Janet E; O'Sullivan, Neil P; Garrick, Dorian J

2016-03-19

Genomic estimated breeding values (GEBV) based on single nucleotide polymorphism (SNP) genotypes are widely used in animal improvement programs. It is typically assumed that the larger the number of animals is in the training set, the higher is the prediction accuracy of GEBV. The aim of this study was to quantify genomic prediction accuracy depending on the number of ancestral generations included in the training set, and to determine the optimal number of training generations for different traits in an elite layer breeding line. Phenotypic records for 16 traits on 17,793 birds were used. All parents and some selection candidates from nine non-overlapping generations were genotyped for 23,098 segregating SNPs. An animal model with pedigree relationships (PBLUP) and the BayesB genomic prediction model were applied to predict EBV or GEBV at each validation generation (progeny of the most recent training generation) based on varying numbers of immediately preceding ancestral generations. Prediction accuracy of EBV or GEBV was assessed as the correlation between EBV and phenotypes adjusted for fixed effects, divided by the square root of trait heritability. The optimal number of training generations that resulted in the greatest prediction accuracy of GEBV was determined for each trait. The relationship between optimal number of training generations and heritability was investigated. On average, accuracies were higher with the BayesB model than with PBLUP. Prediction accuracies of GEBV increased as the number of closely-related ancestral generations included in the training set increased, but reached an asymptote or slightly decreased when distant ancestral generations were used in the training set. The optimal number of training generations was 4 or more for high heritability traits but less than that for low heritability traits. For less heritable traits, limiting the training datasets to individuals closely related to the validation population resulted in the best predictions. The effect of adding distant ancestral generations in the training set on prediction accuracy differed between traits and the optimal number of necessary training generations is associated with the heritability of traits.

Seasonal movement and spatial distribution of the sheep ked (Diptera: Hippoboscidae) on Wyoming lambs.

PubMed

Legg, D E; Kumar, R; Watson, D W; Lloyd, J E

1991-10-01

When populations of adult sheep ked, Melophagus ovinus (L.), infesting unshorn lambs were monitored at the University of Wyoming Paradise Farm during 1986, we determined the body regions on which keds would be found at various times of the year and their seasonal population trends for optimal sampling. Results suggested that ked populations were consistently greater on the ribs than on any other area of the lamb. No significant differences were detected for ked populations between sides of a lamb. Distinct and similar ked population trends over time occurred only in the rib, thigh, shoulder, hind leg, belly, and hind flank areas of the lambs, suggesting that a significant seasonal migration did not occur. Analyses for seasonal population fluctuations indicated that ked populations increased in the winter and spring, decreased in summer and then increased again in the fall. Thus, sampling for keds in the rib area at shearing, which begins in March in Wyoming and runs through mid-April, would be an opportune time to detect keds. At other times of the year, the rib area should be inspected for presence of sheep ked.

Impact of stakeholders influence, geographic level and risk perception on strategic decisions in simulated foot and mouth disease epizootics in France.

PubMed

Marsot, Maud; Rautureau, Séverine; Dufour, Barbara; Durand, Benoit

2014-01-01

Comparison of control strategies against animal infectious diseases allows determining optimal strategies according to their epidemiological and/or economic impacts. However, in real life, the choice of a control strategy does not always obey a pure economic or epidemiological rationality. The objective of this study was to analyze the choice of a foot and mouth disease (FMD) control strategy as a decision-making process in which the decision-maker is influenced by several stakeholders (government, agro-food industries, public opinion). For each of these, an indicator of epizootic impact was quantified to compare seven control strategies. We then determined how, in France, the optimal control strategy varied according to the relative weights of stakeholders and to the perception of risk by the decision-maker (risk-neutral/risk-averse). When the scope of decision was national, whatever their perception of risk and the stakeholders' weights, decision-makers chose a strategy based on vaccination. This consensus concealed marked differences between regions, which were connected with the regional breeding characteristics. Vaccination-based strategies were predominant in regions with dense cattle and swine populations, and in regions with a dense population of small ruminants, combined with a medium density of cattle and swine. These differences between regions suggested that control strategies could be usefully adapted to local breeding conditions. We then analyzed the feasibility of adaptive decision-making processes depending on the date and place where the epizootic starts, or on the evolution of the epizootic over time. The initial conditions always explained at least half of the variance of impacts, the remaining variance being attributed to the variability of epizootics evolution. However, the first weeks of this evolution explained a large part of the impacts variability. Although the predictive value of the initial conditions for determining the optimal strategy was weak, adaptive strategies changing dynamically according to the evolution of the epizootic appeared feasible.

Macronutrient Optimization and Seasonal Diet Mixing in a Large Omnivore, the Grizzly Bear: A Geometric Analysis

PubMed Central

Coogan, Sean C. P.; Raubenheimer, David; Stenhouse, Gordon B.; Nielsen, Scott E.

2014-01-01

Nutrient balance is a strong determinant of animal fitness and demography. It is therefore important to understand how the compositions of available foods relate to required balance of nutrients and habitat suitability for animals in the wild. These relationships are, however, complex, particularly for omnivores that often need to compose balanced diets by combining their intake from diverse nutritionally complementary foods. Here we apply geometric models to understand how the nutritional compositions of foods available to an omnivorous member of the order Carnivora, the grizzly bear (Ursus arctos L.), relate to optimal macronutrient intake, and assess the seasonal nutritional constraints on the study population in west-central Alberta, Canada. The models examined the proportion of macronutrients that bears could consume by mixing their diet from food available in each season, and assessed the extent to which bears could consume the ratio of protein to non-protein energy previously demonstrated using captive bears to optimize mass gain. We found that non-selective feeding on ungulate carcasses provided a non-optimal macronutrient balance with surplus protein relative to fat and carbohydrate, reflecting adaptation to an omnivorous lifestyle, and that optimization through feeding selectively on different tissues of ungulate carcasses is unlikely. Bears were, however, able to dilute protein intake to an optimal ratio by mixing their otherwise high-protein diet with carbohydrate-rich fruit. Some individual food items were close to optimally balanced in protein to non-protein energy (e.g. Hedysarum alpinum roots), which may help explain their dietary prevalence. Ants may be consumed particularly as a source of lipids. Overall, our analysis showed that most food available to bears in the study area were high in protein relative to lipid or carbohydrate, suggesting the lack of non-protein energy limits the fitness (e.g. body size and reproduction) and population density of grizzly bears in this ecosystem. PMID:24841821

Macronutrient optimization and seasonal diet mixing in a large omnivore, the grizzly bear: a geometric analysis.

PubMed

Coogan, Sean C P; Raubenheimer, David; Stenhouse, Gordon B; Nielsen, Scott E

2014-01-01

Nutrient balance is a strong determinant of animal fitness and demography. It is therefore important to understand how the compositions of available foods relate to required balance of nutrients and habitat suitability for animals in the wild. These relationships are, however, complex, particularly for omnivores that often need to compose balanced diets by combining their intake from diverse nutritionally complementary foods. Here we apply geometric models to understand how the nutritional compositions of foods available to an omnivorous member of the order Carnivora, the grizzly bear (Ursus arctos L.), relate to optimal macronutrient intake, and assess the seasonal nutritional constraints on the study population in west-central Alberta, Canada. The models examined the proportion of macronutrients that bears could consume by mixing their diet from food available in each season, and assessed the extent to which bears could consume the ratio of protein to non-protein energy previously demonstrated using captive bears to optimize mass gain. We found that non-selective feeding on ungulate carcasses provided a non-optimal macronutrient balance with surplus protein relative to fat and carbohydrate, reflecting adaptation to an omnivorous lifestyle, and that optimization through feeding selectively on different tissues of ungulate carcasses is unlikely. Bears were, however, able to dilute protein intake to an optimal ratio by mixing their otherwise high-protein diet with carbohydrate-rich fruit. Some individual food items were close to optimally balanced in protein to non-protein energy (e.g. Hedysarum alpinum roots), which may help explain their dietary prevalence. Ants may be consumed particularly as a source of lipids. Overall, our analysis showed that most food available to bears in the study area were high in protein relative to lipid or carbohydrate, suggesting the lack of non-protein energy limits the fitness (e.g. body size and reproduction) and population density of grizzly bears in this ecosystem.

Optimal control of population and coherence in three-level Λ systems

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Malinovskaya, Svetlana A.; Malinovsky, Vladimir S.

2011-08-01

Optimal control theory (OCT) implementations for an efficient population transfer and creation of maximum coherence in a three-level system are considered. We demonstrate that the half-stimulated Raman adiabatic passage scheme for creation of the maximum Raman coherence is the optimal solution according to the OCT. We also present a comparative study of several implementations of OCT applied to the complete population transfer and creation of the maximum coherence. Performance of the conjugate gradient method, the Zhu-Rabitz method and the Krotov method has been analysed.

An Ecohydrological Approach to the Resiliency and Stability of Ecosystems

NASA Astrophysics Data System (ADS)

Peña Alzate, S.; Canon Barriga, J. E.

2013-12-01

We introduce a simplified ecohydrological model to quantitatively assess the resiliency and stability of ecosystems. The proposed model couples a hydrological soil moisture balance with a set of spatiotemporal dynamics of systems and agent-based algorithms to represent the interactions among several plant populations in a gridded area under different water, soil and temperature constraints. The model also allows disturbances, representing mostly the effects of deforestation practices. The simulated ecosystem, composed by a set of plant populations, includes allometric rules (i.e., power laws for generational and reproductive times, linear approximations for water and temperature gains, losses and optimal values and a set of intra and interspecific interaction rules based on high, optimal and low competition responses among the populations). Disturbances are determined by a clearance of populations in a defined area within the model's domain. The effects of climate variability can be also incorporated through precipitation and temperature time series that exhibit trends and heteroskedasticity. Resiliency and stability are calculated with modified indices that are used in hydrology, in this case to determine the ability of the ecosystem to recover from a disturbance. The model represents different types of plant phenotypes showing exponential growth in the first steps of the simulations. The indices, evaluated on each population and over the structure of the entire ecosystem, show how different populations respond differently to disturbances, following behaviors similar to those expected in nature, like high reproduction rates on gregarious plants with short generation times, and low densities in plants with high generations times. The selection of plant populations was mainly focused on the concept of biodiversity with emphasis on tropical regions. The model can represent the spatial and temporal succession of the ecosystem after being disturbed. The model also shows the differences between a disturbed and undisturbed ecosystem in a temporal scale, and how the differences in the phenotypical characteristics of plant populations can be advantageous or disadvantageous when they are disturbed. This ecohydrological model is intended to be used as an aid for making decisions about restoration and conservation practices, and also to help understanding resilience and stability of ecosystems, especially in tropical forests under climate change scenarios. Acknowledgements: authors thank the financial support of COLCIENCIAS (program Jovenes Investigadores e innovadores 2012), GAIA group and Universidad de Antioquia through its Sustainability Program 2011-2012.

Optimizing reserve expansion for disjunct populations of San Joaquin kit fox

Treesearch

Robert G. Haight; Brian Cypher; Patrick A. Kelly; Scott Phillips; Katherine Ralls; Hugh P. Possingham

2004-01-01

Expanding habitat protection is a common strategy for species conservation. We present a model to optimize the expansion of reserves for disjunct populations of an endangered species. The objective is to maximize the expected number of surviving populations subject to budget and habitat constraints. The model accounts for benefits of reserve expansion in terms of...

Adaptive cockroach swarm algorithm

NASA Astrophysics Data System (ADS)

Obagbuwa, Ibidun C.; Abidoye, Ademola P.

2017-07-01

An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

PubMed

Dühring, Sybille; Ewald, Jan; Germerodt, Sebastian; Kaleta, Christoph; Dandekar, Thomas; Schuster, Stefan

2017-07-01

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage- Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage- C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells. © 2017 The Author(s).

An eHealth Intervention to Promote Physical Activity and Social Network of Single, Chronically Impaired Older Adults: Adaptation of an Existing Intervention Using Intervention Mapping

PubMed Central

Peels, Denise A; Berendsen, Brenda AJ; Bolman, Catherine AW; Lechner, Lilian

2017-01-01

Background Especially for single older adults with chronic diseases, physical inactivity and a poor social network are regarded as serious threats to their health and independence. The Active Plus intervention is an automated computer-tailored eHealth intervention that has been proven effective to promote physical activity (PA) in the general population of adults older than 50 years. Objective The aim of this study was to report on the methods and results of the systematic adaptation of Active Plus to the wishes and needs of the subgroup of single people older than 65 years who have one or more chronic diseases, as this specific target population may encounter specific challenges regarding PA and social network. Methods The Intervention Mapping (IM) protocol was used to systematically adapt the existing intervention to optimally suit this specific target population. A literature study was performed, and quantitative as well as qualitative data were derived from health care professionals (by questionnaires, n=10) and the target population (by focus group interviews, n=14), which were then systematically integrated into the adapted intervention. Results As the health problems and the targeted behavior are largely the same in the original and adapted intervention, the outcome of the needs assessment was that the performance objectives remained the same. As found in the literature study and in data derived from health professionals and focus groups, the relative importance and operationalization of the relevant psychosocial determinants related to these objectives are different from the original intervention, resulting in a refinement of the change objectives to optimally fit the specific target population. This refinement also resulted in changes in the practical applications, program components, intervention materials, and the evaluation and implementation strategy for the subgroup of single, chronically impaired older adults. Conclusions This study demonstrates that the adaptation of an existing intervention is an intensive process in which adopting the IM protocol is an invaluable tool. The study provides a broad insight in adapting interventions aimed at single older adults with a chronic disease. It is concluded that even when the new target population is a sizable segment of the original target population, the adapted intervention still needs considerable changes to optimally fit the needs and situational differences of the narrower target population. PMID:29170146

The association of sleep duration and depressive symptoms in rural communities of southeastern Missouri, Tennessee, and Arkansas

PubMed Central

JJ, Chang; J, Salas; K, Habicht; GW, Pien; KA, Stamatakis; RC, Brownson

2012-01-01

Purpose To determine the association between sleep duration and depressive symptoms in a rural setting. Methods We conducted a cross-sectional study using data from Wave 3 of the Walk the Ozarks to Wellness Project including 12 rural communities in Missouri, Arkansas, and Tennessee (N = 1,204). Sleep duration was defined based on average weeknight and weekend hours per day: short (< 7), optimal (7-8), and long (> 8). The primary outcome was self-reported elevated depressive symptoms. Multivariable logistic regression was used to estimate adjusted prevalence odds ratios (aPOR) and 95% confidence intervals (95% CI). Findings Elevated depressive symptoms were common in this rural population (17%). Depressive symptoms were more prevalent among subjects with short (26.1%) and long (24%) sleep duration compared to those with optimal (11.8%) sleep duration. After adjusting for age, gender, race, education, employment status, income, and BMI, short sleep duration was associated with increased odds of elevated depressive symptoms (aPOR=2.12, 95% CI: 1.49, 3.01), compared to optimal sleep duration. Conversely, the association between long sleep duration and depressive symptoms was not statistically significant after covariate adjustment. Similar findings were observed when we excluded individuals with insomnia symptoms for analysis. Conclusions This study suggests that short sleep duration (<7 hours per night) and depressive symptoms are common among rural populations. Short sleep duration is positively associated with elevated depressive symptoms. The economic and healthcare burden of depression may be more overwhelming among rural populations, necessitating the need to target modifiable behaviors such as sleep habits to improve mental health. PMID:22757951

MARKOV: A methodology for the solution of infinite time horizon MARKOV decision processes

USGS Publications Warehouse

Williams, B.K.

1988-01-01

Algorithms are described for determining optimal policies for finite state, finite action, infinite discrete time horizon Markov decision processes. Both value-improvement and policy-improvement techniques are used in the algorithms. Computing procedures are also described. The algorithms are appropriate for processes that are either finite or infinite, deterministic or stochastic, discounted or undiscounted, in any meaningful combination of these features. Computing procedures are described in terms of initial data processing, bound improvements, process reduction, and testing and solution. Application of the methodology is illustrated with an example involving natural resource management. Management implications of certain hypothesized relationships between mallard survival and harvest rates are addressed by applying the optimality procedures to mallard population models.

Optimal dietary patterns designed from local foods to achieve maternal nutritional goals.

PubMed

Raymond, Jofrey; Kassim, Neema; Rose, Jerman W; Agaba, Morris

2018-04-04

Achieving nutritional requirements for pregnant and lactating mothers in rural households while maintaining the intake of local and culture-specific foods can be a difficult task. Deploying a linear goal programming approach can effectively generate optimal dietary patterns that incorporate local and culturally acceptable diets. The primary objective of this study was to determine whether a realistic and affordable diet that achieves nutritional goals for rural pregnant and lactating women can be formulated from locally available foods in Tanzania. A cross sectional study was conducted to assess dietary intakes of 150 pregnant and lactating women using a weighed dietary record (WDR), 24 h dietary recalls and a 7-days food record. A market survey was also carried out to estimate the cost per 100 g of edible portion of foods that are frequently consumed in the study population. Dietary survey and market data were then used to define linear programming (LP) model parameters for diet optimisation. All LP analyses were done using linear program solver to generate optimal dietary patterns. Our findings showed that optimal dietary patterns designed from locally available foods would improve dietary adequacy for 15 and 19 selected nutrients in pregnant and lactating women, respectively, but inadequacies remained for iron, zinc, folate, pantothenic acid, and vitamin E, indicating that these are problem nutrients (nutrients that did not achieve 100% of their RNIs in optimised diets) in the study population. These findings suggest that optimal use of local foods can improve dietary adequacy for rural pregnant and lactating women aged 19-50 years. However, additional cost-effective interventions are needed to ensure adequate intakes for the identified problem nutrients.

The importance of functional form in optimal control solutions of problems in population dynamics

USGS Publications Warehouse

Runge, M.C.; Johnson, F.A.

2002-01-01

Optimal control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system dynamics, models that are all reasonable in light of available data, but that differ substantially in their implications for optimal control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the optimal harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the optimal harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher optimal harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the optimal steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying optimal control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the optimal harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood profile may end up producing alternatives that do not differ as importantly as if different functional forms had been used. We recommend that biological knowledge be used to bracket a range of possible functional forms, and robustness of conclusions be checked over this range.

A fuzzy multi-objective linear programming approach for integrated sheep farming and wildlife in land management decisions: a case study in the Patagonian rangelands

NASA Astrophysics Data System (ADS)

Metternicht, Graciela; Blanco, Paula; del Valle, Hector; Laterra, Pedro; Hardtke, Leonardo; Bouza, Pablo

2015-04-01

Wildlife is part of the Patagonian rangelands sheep farming environment, with the potential of providing extra revenue to livestock owners. As sheep farming became less profitable, farmers and ranchers could focus on sustainable wildlife harvesting. It has been argued that sustainable wildlife harvesting is ecologically one of the most rational forms of land use because of its potential to provide multiple products of high value, while reducing pressure on ecosystems. The guanaco (Lama guanicoe) is the most conspicuous wild ungulate of Patagonia. Guanaco ?bre, meat, pelts and hides are economically valuable and have the potential to be used within the present Patagonian context of production systems. Guanaco populations in South America, including Patagonia, have experienced a sustained decline. Causes for this decline are related to habitat alteration, competition for forage with sheep, and lack of reasonable management plans to develop livelihoods for ranchers. In this study we propose an approach to explicitly determinate optimal stocking rates based on trade-offs between guanaco density and livestock grazing intensity on rangelands. The focus of our research is on finding optimal sheep stocking rates at paddock level, to ensure the highest production outputs while: a) meeting requirements of sustainable conservation of guanacos over their minimum viable population; b) maximizing soil carbon sequestration, and c) minimizing soil erosion. In this way, determination of optimal stocking rate in rangelands becomes a multi-objective optimization problem that can be addressed using a Fuzzy Multi-Objective Linear Programming (MOLP) approach. Basically, this approach converts multi-objective problems into single-objective optimizations, by introducing a set of objective weights. Objectives are represented using fuzzy set theory and fuzzy memberships, enabling each objective function to adopt a value between 0 and 1. Each objective function indicates the satisfaction of the decision maker towards the respective objective. Fuzzy logic is closer to intuitive thinking used by decision makers, making it a user-friendly approach for them to select alternatives. The proposed approach was applied in a study area of approximately 40,000 hectares in semiarid Patagonian rangelands where extensive, continuous sheep grazing for wool production is the main land use. Multi- and hyper-spectral data were combined with ancillary data within a GIS environment, and used to derive maps of forage production, guanacos density, soil organic carbon and soil erosion. Different scenarios, with different objectives weights were evaluated. Results showed that under scenario 1, where livestock production is predicted to have the highest values, guanaco numbers decrease substantially as well as soil carbon sequestration, and soil erosion exhibit the highest values. On the other hand, when guanaco population is prioritized, livestock production has the lowest value. A compromise alternative resulted from a scenario where variables are assigned same weight; under this condition, high livestock production is predicted, while conservation of guanaco population is sustainable, carbon sequestration is maximized and soil erosion minimized.

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

PubMed Central

Barish, Syndi; Ochs, Michael F.; Sontag, Eduardo D.; Gevertz, Jana L.

2017-01-01

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists. PMID:28716945

Coordination Between the Sexes Constrains the Optimization of Reproductive Timing in Honey Bee Colonies.

PubMed

Lemanski, Natalie J; Fefferman, Nina H

2017-06-01

Honeybees are an excellent model system for examining how trade-offs shape reproductive timing in organisms with seasonal environments. Honeybee colonies reproduce two ways: producing swarms comprising a queen and thousands of workers or producing males (drones). There is an energetic trade-off between producing workers, which contribute to colony growth, and drones, which contribute only to reproduction. The timing of drone production therefore determines both the drones' likelihood of mating and when colonies reach sufficient size to swarm. Using a linear programming model, we ask when a colony should produce drones and swarms to maximize reproductive success. We find the optimal behavior for each colony is to produce all drones prior to swarming, an impossible solution on a population scale because queens and drones would never co-occur. Reproductive timing is therefore not solely determined by energetic trade-offs but by the game theoretic problem of coordinating the production of reproductives among colonies.

Screening of Actinomycetes from mangrove ecosystem for L-asparaginase activity and optimization by response surface methodology.

PubMed

Usha, Rajamanickam; Mala, Krishnaswami Kanjana; Venil, Chidambaram Kulandaisamy; Palaniswamy, Muthusamy

2011-01-01

Marine actinomycetes were isolated from sediment samples collected from Pitchavaram mangrove ecosystem situated along the southeast coast of India. Maximum actinomycete population was noted in rhizosphere region. About 38% of the isolates produced L-asparaginase. One potential strain KUA106 produced higher level of enzyme using tryptone glucose yeast extract medium. Based on the studied phenotypic characteristics, strain KUA106 was identified as Streptomyces parvulus KUA106. The optimization method that combines the Plackett-Burman design, a factorial design and the response surface method, which were used to optimize the medium for the production of L-asparaginase by Streptomycetes parvulus. Four medium factors were screened from eleven medium factors by Plackett-Burman design experiments and subsequent optimization process to find out the optimum values of the selected parameters using central composite design was performed. Asparagine, tryptone, d) extrose and NaCl components were found to be the best medium for the L-asparaginase production. The combined optimization method described here is the effective method for screening medium factors as well as determining their optimum level for the production of L-asparaginase by Streptomycetes parvulus KUAP106.

Genetic algorithm-based multi-objective optimal absorber system for three-dimensional seismic structures

NASA Astrophysics Data System (ADS)

Ren, Wenjie; Li, Hongnan; Song, Gangbing; Huo, Linsheng

2009-03-01

The problem of optimizing an absorber system for three-dimensional seismic structures is addressed. The objective is to determine the number and position of absorbers to minimize the coupling effects of translation-torsion of structures at minimum cost. A procedure for a multi-objective optimization problem is developed by integrating a dominance-based selection operator and a dominance-based penalty function method. Based on the two-branch tournament genetic algorithm, the selection operator is constructed by evaluating individuals according to their dominance in one run. The technique guarantees the better performing individual winning its competition, provides a slight selection pressure toward individuals and maintains diversity in the population. Moreover, due to the evaluation for individuals in each generation being finished in one run, less computational effort is taken. Penalty function methods are generally used to transform a constrained optimization problem into an unconstrained one. The dominance-based penalty function contains necessary information on non-dominated character and infeasible position of an individual, essential for success in seeking a Pareto optimal set. The proposed approach is used to obtain a set of non-dominated designs for a six-storey three-dimensional building with shape memory alloy dampers subjected to earthquake.

Uncertainty, learning, and the optimal management of wildlife

USGS Publications Warehouse

Williams, B.K.

2001-01-01

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Analysis of patterns of patient compliance after an abnormal Pap smear result: the influence of demographic characteristics on patient compliance.

PubMed

Rojas, Christine; Zhou, Ming K; Khamis, Harry J; Amesse, Lawrence

2013-07-01

This study aimed to determine population characteristics that correlate to suboptimal follow-up after an abnormal cervical cytology result. Nonpregnant women, ages 21 to 65 years, with newly diagnosed abnormal cervical cytology result between January 2009 and January 2012 at an urban clinic were eligible for inclusion in this retrospective chart review. Cervical cytology data and demographic characteristics such as age, ethnicity, employment, marital and smoking status, health insurance and number of pregnancies were abstracted from electronic medical record. A log-linear model was used to determine which factors influenced patient compliance. Of the total of 206 women, 78 (37.9%) had optimal follow-up and 128 (62.1%) had suboptimal follow-up. The 3 variables that were statistically significant in influencing patient follow-up after adjusted analyses included severity of cytology result (p = .0013), ethnicity (p = .02), and employment status (p = .0159). The risk ratio for optimal follow-up for those with severe cytology result was 1.81; for the non-whites, 1.77; and for the employed, 1.53. Ethnicity, severity of cervical cytology result, and employment status play an important role in patient follow-up after an abnormal cervical cytology result. Detecting trends in our patient population that influence adherence to follow-up will help health care providers formulate strategies that target this problem.

Drivers of telemedicine use: comparative evidence from samples of Spanish, Colombian and Bolivian physicians.

PubMed

Saigí-Rubió, Francesc; Torrent-Sellens, Joan; Jiménez-Zarco, Ana

2014-10-08

The aim of the study presented in this article is to analyse the determinants of telemedicine use. To that end, the study makes two basic contributions. First, it considers six working hypotheses in the context of technology acceptance models (TAMs). Second, it uses data obtained for three samples of physicians from three different countries (Spain, Colombia and Bolivia). Obtaining and comparing evidence on an international scale allows determinants of telemedicine use to be evaluated across different contexts. In Bolivia, the survey was conducted in hospitals and health care centres of the urban and rural districts of the municipality of Sucre, in a population comprising a total of 350 physicians. In Spain, the survey population consisted of medical professionals of all profiles affiliated with health care within the Canary Islands Health Service, comprising a total of 356 physicians. Finally, in Colombia, it was conducted in the Society of Surgery Service at San José Hospital of Bogotá, in a population comprising a total of 184 physicians. Using an extended TAM and survey data from 510 physicians (113 in Spain, 118 in Colombia and 279 in Bolivia), binary logistic regression analysis was performed. In the three samples, it was found that the physician's level of information and communication technology (ICT) use in his/her personal life was the variable that had the highest explanatory power regarding telemedicine use. In the Spanish sample, the physicians' perceived ease-of-use of ICTs in clinical practice and propensity to innovate were the two other variables that determined telemedicine use, whereas in the Colombian and Bolivian samples, it was the level of optimism about ICTs. The results facilitated a more complete model that includes personal, usability, and innovatory aspects in the explanation of Telemedicine use in Spain, whereas the results for the Latin American samples indicated a more primary model in the explanation of Telemedicine use, which was completed by an optimism factor that did not emerge in the Spanish sample.

Optimal city size and population density for the 21st century.

PubMed

Speare A; White, M J

1990-10-01

The thesis that large scale urban areas result in greater efficiency, reduced costs, and a better quality of life is reexamined. The environmental and social costs are measured for different scales of settlement. The desirability and perceived problems of a particular place are examined in relation to size of place. The consequences of population decline are considered. New York city is described as providing both opportunities in employment, shopping, and cultural activities as well as a high cost of living, crime, and pollution. The historical development of large cities in the US is described. Immigration has contributed to a greater concentration of population than would have otherwise have occurred. The spatial proximity of goods and services argument (agglomeration economies) has changed with advancements in technology such as roads, trucking, and electronic communication. There is no optimal city size. The overall effect of agglomeration can be assessed by determining whether the markets for goods and labor are adequate to maximize well-being and balance the negative and positive aspects of urbanization. The environmental costs of cities increase with size when air quality, water quality, sewage treatment, and hazardous waste disposal is considered. Smaller scale and lower density cities have the advantages of a lower concentration of pollutants. Also, mobilization for program support is easier with homogenous population. Lower population growth in large cities would contribute to a higher quality of life, since large metropolitan areas have a concentration of immigrants, younger age distributions, and minority groups with higher than average birth rates. The negative consequences of decline can be avoided if reduction of population in large cities takes place gradually. For example, poorer quality housing can be removed for open space. Cities should, however, still attract all classes of people with opportunities equally available.

Application of optimal design methodologies in clinical pharmacology experiments.

PubMed

Ogungbenro, Kayode; Dokoumetzidis, Aristides; Aarons, Leon

2009-01-01

Pharmacokinetics and pharmacodynamics data are often analysed by mixed-effects modelling techniques (also known as population analysis), which has become a standard tool in the pharmaceutical industries for drug development. The last 10 years has witnessed considerable interest in the application of experimental design theories to population pharmacokinetic and pharmacodynamic experiments. Design of population pharmacokinetic experiments involves selection and a careful balance of a number of design factors. Optimal design theory uses prior information about the model and parameter estimates to optimize a function of the Fisher information matrix to obtain the best combination of the design factors. This paper provides a review of the different approaches that have been described in the literature for optimal design of population pharmacokinetic and pharmacodynamic experiments. It describes options that are available and highlights some of the issues that could be of concern as regards practical application. It also discusses areas of application of optimal design theories in clinical pharmacology experiments. It is expected that as the awareness about the benefits of this approach increases, more people will embrace it and ultimately will lead to more efficient population pharmacokinetic and pharmacodynamic experiments and can also help to reduce both cost and time during drug development. Copyright (c) 2008 John Wiley & Sons, Ltd.

Micronutrients in parenteral nutrition: boron, silicon, and fluoride.

PubMed

Nielsen, Forrest H

2009-11-01

Boron may be beneficial for bone growth and maintenance, central nervous system function, and the inflammatory response, and silicon may be beneficial for bone maintenance and wound healing. Fluoride is not an essential element but amounts provided by contamination may be beneficial for bone strength. Fluoride toxicity may be a concern in parenteral nutrition. Further studies are warranted to determine whether there are optimal amounts of boron and silicon that should be delivered to typical and special population patients receiving parenteral nutrition. In addition, further studies are needed to determine whether providing the dietary guideline of adequate intake amounts of fluoride parenterally would prevent or treat parenteral nutrition osteopenia.

Pediatric tuberculous meningitis: model-based approach to determining optimal doses of the anti-tuberculosis drugs rifampin and levofloxacin for children

PubMed Central

Savic, Radojka M.; Ruslami, Rovina; Hibma, Jennifer E.; Hesseling, Anneke; Ramachandran, Geetha; Ganiem, A. Rizal; Swaminathan, Soumya; McIlleron, Helen; Gupta, Amita; Thakur, Kiran; van Crevel, Reinout; Aarnoutse, Rob; Dooley, Kelly E.

2016-01-01

Pediatric TB meningitis (TBM) is a highly-morbid, oft-fatal disease. Standard treatment includes isoniazid, rifampin, pyrazinamide, and ethambutol. Current rifampin dosing achieves low cerebrospinal fluid (CSF) concentrations, and CSF penetration of ethambutol is poor. In adult trials, higher-dose rifampin and/or a fluoroquinolone reduced mortality and disability. To estimate optimal dosing of rifampin and levofloxacin for children, we compiled plasma and CSF pharmacokinetic and outcomes data from adult TBM trials plus plasma pharmacokinetic data from children. A population pharmacokinetic/pharmacodynamic model using adult data defined rifampin target exposures (plasma AUC0–24=92 mg*h/L). Levofloxacin targets and rifampin pediatric drug disposition information were literature-derived. To attain target rifampin exposures, children require daily doses of at least 30 mg/kg orally or 15 mg/kg intravenously. From our pediatric population PK model, oral levofloxacin doses needed to attain exposure targets were 19–33 mg/kg. Our results provide data-driven guidance to maximize pediatric TBM treatment while we await definitive trial results. PMID:26260983

Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.

PubMed

Tilahun, Getachew Teshome; Makinde, Oluwole Daniel; Malonza, David

2017-01-01

We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifurcation and the sensitivity analysis is performed. The optimal control problem is designed by applying Pontryagin maximum principle with three control strategies, namely, the prevention strategy through sanitation, proper hygiene, and vaccination; the treatment strategy through application of appropriate medicine; and the screening of the carriers. The cost functional accounts for the cost involved in prevention, screening, and treatment together with the total number of the infected persons averted. Numerical results for the typhoid outbreak dynamics and its optimal control revealed that a combination of prevention and treatment is the best cost-effective strategy to eradicate the disease.

Early life environment and social determinants of cardiac health in children with congenital heart disease.

PubMed

Wong, Peter; Denburg, Avram; Dave, Malini; Levin, Leo; Morinis, Julia Orkin; Suleman, Shazeen; Wong, Jonathan; Ford-Jones, Elizabeth; Moore, Aideen M

2018-04-01

Congenital heart disease is a significant cause of infant mortality. Epidemiology and social context play a crucial role in conditioning disease burden and modulating outcomes, while diagnosis and treatment remain resource intensive. This review will address the role of social demographics, environmental exposure, epigenetics and nutrition in the aetiology of congenital heart disease. We then discuss the determinant effect of social factors on the provision and outcomes of care for congenital heart disease and implications for practice. It is our hope that enhanced knowledge of the intersection of social determinants of health and congenital heart disease will facilitate effective preventative strategies at the individual and population levels to optimize heart health outcomes across the life course.

Mutation Bias Favors Protein Folding Stability in the Evolution of Small Populations

PubMed Central

Porto, Markus; Bastolla, Ugo

2010-01-01

Mutation bias in prokaryotes varies from extreme adenine and thymine (AT) in obligatory endosymbiotic or parasitic bacteria to extreme guanine and cytosine (GC), for instance in actinobacteria. GC mutation bias deeply influences the folding stability of proteins, making proteins on the average less hydrophobic and therefore less stable with respect to unfolding but also less susceptible to misfolding and aggregation. We study a model where proteins evolve subject to selection for folding stability under given mutation bias, population size, and neutrality. We find a non-neutral regime where, for any given population size, there is an optimal mutation bias that maximizes fitness. Interestingly, this optimal GC usage is small for small populations, large for intermediate populations and around 50% for large populations. This result is robust with respect to the definition of the fitness function and to the protein structures studied. Our model suggests that small populations evolving with small GC usage eventually accumulate a significant selective advantage over populations evolving without this bias. This provides a possible explanation to the observation that most species adopting obligatory intracellular lifestyles with a consequent reduction of effective population size shifted their mutation spectrum towards AT. The model also predicts that large GC usage is optimal for intermediate population size. To test these predictions we estimated the effective population sizes of bacterial species using the optimal codon usage coefficients computed by dos Reis et al. and the synonymous to non-synonymous substitution ratio computed by Daubin and Moran. We found that the population sizes estimated in these ways are significantly smaller for species with small and large GC usage compared to species with no bias, which supports our prediction. PMID:20463869

Comparison of Genetic Algorithm and Hill Climbing for Shortest Path Optimization Mapping

NASA Astrophysics Data System (ADS)

Fronita, Mona; Gernowo, Rahmat; Gunawan, Vincencius

2018-02-01

Traveling Salesman Problem (TSP) is an optimization to find the shortest path to reach several destinations in one trip without passing through the same city and back again to the early departure city, the process is applied to the delivery systems. This comparison is done using two methods, namely optimization genetic algorithm and hill climbing. Hill Climbing works by directly selecting a new path that is exchanged with the neighbour's to get the track distance smaller than the previous track, without testing. Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations. To simplify the process of determining the shortest path supported by the development of software that uses the google map API. Tests carried out as much as 20 times with the number of city 8, 16, 24 and 32 to see which method is optimal in terms of distance and time computation. Based on experiments conducted with a number of cities 3, 4, 5 and 6 producing the same value and optimal distance for the genetic algorithm and hill climbing, the value of this distance begins to differ with the number of city 7. The overall results shows that these tests, hill climbing are more optimal to number of small cities and the number of cities over 30 optimized using genetic algorithms.

Hybrid intelligent optimization methods for engineering problems

NASA Astrophysics Data System (ADS)

Pehlivanoglu, Yasin Volkan

The purpose of optimization is to obtain the best solution under certain conditions. There are numerous optimization methods because different problems need different solution methodologies; therefore, it is difficult to construct patterns. Also mathematical modeling of a natural phenomenon is almost based on differentials. Differential equations are constructed with relative increments among the factors related to yield. Therefore, the gradients of these increments are essential to search the yield space. However, the landscape of yield is not a simple one and mostly multi-modal. Another issue is differentiability. Engineering design problems are usually nonlinear and they sometimes exhibit discontinuous derivatives for the objective and constraint functions. Due to these difficulties, non-gradient-based algorithms have become more popular in recent decades. Genetic algorithms (GA) and particle swarm optimization (PSO) algorithms are popular, non-gradient based algorithms. Both are population-based search algorithms and have multiple points for initiation. A significant difference from a gradient-based method is the nature of the search methodologies. For example, randomness is essential for the search in GA or PSO. Hence, they are also called stochastic optimization methods. These algorithms are simple, robust, and have high fidelity. However, they suffer from similar defects, such as, premature convergence, less accuracy, or large computational time. The premature convergence is sometimes inevitable due to the lack of diversity. As the generations of particles or individuals in the population evolve, they may lose their diversity and become similar to each other. To overcome this issue, we studied the diversity concept in GA and PSO algorithms. Diversity is essential for a healthy search, and mutations are the basic operators to provide the necessary variety within a population. After having a close scrutiny of the diversity concept based on qualification and quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.

Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.

PubMed

Green, Adam W; Bailey, Larissa L

2015-01-01

Adaptive management provides a useful framework for managing natural resources in the face of uncertainty. An important component of adaptive management is identifying clear, measurable conservation objectives that reflect the desired outcomes of stakeholders. A common objective is to have a sustainable population, or metapopulation, but it can be difficult to quantify a threshold above which such a population is likely to persist. We performed a Bayesian metapopulation viability analysis (BMPVA) using a dynamic occupancy model to quantify the characteristics of two wood frog (Lithobates sylvatica) metapopulations resulting in sustainable populations, and we demonstrate how the results could be used to define meaningful objectives that serve as the basis of adaptive management. We explored scenarios involving metapopulations with different numbers of patches (pools) using estimates of breeding occurrence and successful metamorphosis from two study areas to estimate the probability of quasi-extinction and calculate the proportion of vernal pools producing metamorphs. Our results suggest that ≥50 pools are required to ensure long-term persistence with approximately 16% of pools producing metamorphs in stable metapopulations. We demonstrate one way to incorporate the BMPVA results into a utility function that balances the trade-offs between ecological and financial objectives, which can be used in an adaptive management framework to make optimal, transparent decisions. Our approach provides a framework for using a standard method (i.e., PVA) and available information to inform a formal decision process to determine optimal and timely management policies.

Relationship Between Crop Losses and Initial Population Densities of Meloidogyne arenaria in Winter-Grown Oriental Melon in Korea

PubMed Central

Kim, D.G.; Ferris, H.

2002-01-01

To determine the economic threshold level, oriental melon (Cucumis melo L. cv. Geumssaragi-euncheon) grafted on Shintozoa (Cucurbita maxima × Cu. moschata) was planted in plots (2 × 3 m) under a plastic film in February with a range of initial population densities (Pi) of Meloidogyne arenaria. The relationships of early, late, and total yield to Pi measured in September and January were adequately described by both linear regression and the Seinhorst damage model. Initial nematode densities in September in excess of 14 second-stage juveniles (J2)/100 cm³ soil caused losses in total yields that exceeded the economic threshold and indicate the need for fosthiazate nematicide treatment at current costs. Differences in yield-loss relationships to Pi between early- and late-season harvests enhance the resolution of the management decision and suggest approaches for optimizing returns. Determination of population levels for advisory purposes can be based on assay samples taken several months before planting, which allows time for implementation of management procedures. We introduce (i) an amendment of the economic threshold definition to reflect efficacy of the nematode management procedure under consideration, and (ii) the concept of profit limit as the nematode population at which net returns from the system will become negative. PMID:19265907

Evidence-based medicine is affordable: the cost-effectiveness of current compared with optimal treatment in rheumatoid and osteoarthritis.

PubMed

Andrews, Gavin; Simonella, Leonardo; Lapsley, Helen; Sanderson, Kristy; March, Lyn

2006-04-01

To determine the cost-effectiveness of averting the burden of disease. We used secondary population data and metaanalyses of various government-funded services and interventions to investigate the costs and benefits of various levels of treatment for rheumatoid arthritis (RA) and osteoarthritis (OA) in adults using a burden of disease framework. Population burden was calculated for both diseases in the absence of any treatment as years lived with disability (YLD), ignoring the years of life lost. We then estimated the proportion of burden averted with current interventions, the proportion that could be averted with optimally implemented current evidence-based guidelines, and the direct treatment cost-effectiveness ratio in dollars per YLD averted for both treatment levels. The majority of people with arthritis sought medical treatment. Current treatment for RA averted 26% of the burden, with a cost-effectiveness ratio of dollar 19,000 per YLD averted. Optimal, evidence-based treatment would avert 48% of the burden, with a cost-effectiveness ratio of dollar 12,000 per YLD averted. Current treatment of OA in Australia averted 27% of the burden, with a cost-effectiveness ratio of dollar 25,000 per YLD averted. Optimal, evidence-based treatment would avert 39% of the burden, with an unchanged cost-effectiveness ratio of dollar 25,000 per YLD averted. While the precise dollar costs in each country will differ, the relativities at this level of coverage should remain the same. There is no evidence that closing the gap between evidence and practice would result in a drop in efficiency.

An optimizing start-up strategy for a bio-methanator.

PubMed

Sbarciog, Mihaela; Loccufier, Mia; Vande Wouwer, Alain

2012-05-01

This paper presents an optimizing start-up strategy for a bio-methanator. The goal of the control strategy is to maximize the outflow rate of methane in anaerobic digestion processes, which can be described by a two-population model. The methodology relies on a thorough analysis of the system dynamics and involves the solution of two optimization problems: steady-state optimization for determining the optimal operating point and transient optimization. The latter is a classical optimal control problem, which can be solved using the maximum principle of Pontryagin. The proposed control law is of the bang-bang type. The process is driven from an initial state to a small neighborhood of the optimal steady state by switching the manipulated variable (dilution rate) from the minimum to the maximum value at a certain time instant. Then the dilution rate is set to the optimal value and the system settles down in the optimal steady state. This control law ensures the convergence of the system to the optimal steady state and substantially increases its stability region. The region of attraction of the steady state corresponding to maximum production of methane is considerably enlarged. In some cases, which are related to the possibility of selecting the minimum dilution rate below a certain level, the stability region of the optimal steady state equals the interior of the state space. Aside its efficiency, which is evaluated not only in terms of biogas production but also from the perspective of treatment of the organic load, the strategy is also characterized by simplicity, being thus appropriate for implementation in real-life systems. Another important advantage is its generality: this technique may be applied to any anaerobic digestion process, for which the acidogenesis and methanogenesis are, respectively, characterized by Monod and Haldane kinetics.

Allochthonous bioaugmentation in ex situ treatment of crude oil-polluted sediments in the presence of an effective degrading indigenous microbiome.

PubMed

Fodelianakis, S; Antoniou, E; Mapelli, F; Magagnini, M; Nikolopoulou, M; Marasco, R; Barbato, M; Tsiola, A; Tsikopoulou, I; Giaccaglia, L; Mahjoubi, M; Jaouani, A; Amer, R; Hussein, E; Al-Horani, F A; Benzha, F; Blaghen, M; Malkawi, H I; Abdel-Fattah, Y; Cherif, A; Daffonchio, D; Kalogerakis, N

2015-04-28

Oil-polluted sediment bioremediation depends on both physicochemical and biological parameters, but the effect of the latter cannot be evaluated without the optimization of the former. We aimed in optimizing the physicochemical parameters related to biodegradation by applying an ex-situ landfarming set-up combined with biostimulation to oil-polluted sediment, in order to determine the added effect of bioaugmentation by four allochthonous oil-degrading bacterial consortia in relation to the degradation efficiency of the indigenous community. We monitored hydrocarbon degradation, sediment ecotoxicity and hydrolytic activity, bacterial population sizes and bacterial community dynamics, characterizing the dominant taxa through time and at each treatment. We observed no significant differences in total degradation, but increased ecotoxicity between the different treatments receiving both biostimulation and bioaugmentation and the biostimulated-only control. Moreover, the added allochthonous bacteria quickly perished and were rarely detected, their addition inducing minimal shifts in community structure although it altered the distribution of the residual hydrocarbons in two treatments. Therefore, we concluded that biodegradation was mostly performed by the autochthonous populations while bioaugmentation, in contrast to biostimulation, did not enhance the remediation process. Our results indicate that when environmental conditions are optimized, the indigenous microbiome at a polluted site will likely outperform any allochthonous consortium. Copyright © 2015 Elsevier B.V. All rights reserved.

How to Minimize the Attack Rate during Multiple Influenza Outbreaks in a Heterogeneous Population

PubMed Central

Fung, Isaac Chun-Hai; Antia, Rustom; Handel, Andreas

2012-01-01

Background If repeated interventions against multiple outbreaks are not feasible, there is an optimal level of control during the first outbreak. Any control measures above that optimal level will lead to an outcome that may be as sub-optimal as that achieved by an intervention that is too weak. We studied this scenario in more detail. Method An age-stratified ordinary-differential-equation model was constructed to study infectious disease outbreaks and control in a population made up of two groups, adults and children. The model was parameterized using influenza as an example. This model was used to simulate two consecutive outbreaks of the same infectious disease, with an intervention applied only during the first outbreak, and to study how cumulative attack rates were influenced by population composition, strength of inter-group transmission, and different ways of triggering and implementing the interventions. We assumed that recovered individuals are fully immune and the intervention does not confer immunity. Results/Conclusion The optimal intervention depended on coupling between the two population sub-groups, the length, strength and timing of the intervention, and the population composition. Population heterogeneity affected intervention strategies only for very low cross-transmission between groups. At more realistic values, coupling between the groups led to synchronization of outbreaks and therefore intervention strategies that were optimal in reducing the attack rates for each subgroup and the population overall coincided. For a sustained intervention of low efficacy, early intervention was found to be best, while at high efficacies, a delayed start was better. For short interventions, a delayed start was always advantageous, independent of the intervention efficacy. For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak’s beginning as the trigger. PMID:22701558

Finding optimal vaccination strategies for pandemic influenza using genetic algorithms.

PubMed

Patel, Rajan; Longini, Ira M; Halloran, M Elizabeth

2005-05-21

In the event of pandemic influenza, only limited supplies of vaccine may be available. We use stochastic epidemic simulations, genetic algorithms (GA), and random mutation hill climbing (RMHC) to find optimal vaccine distributions to minimize the number of illnesses or deaths in the population, given limited quantities of vaccine. Due to the non-linearity, complexity and stochasticity of the epidemic process, it is not possible to solve for optimal vaccine distributions mathematically. However, we use GA and RMHC to find near optimal vaccine distributions. We model an influenza pandemic that has age-specific illness attack rates similar to the Asian pandemic in 1957-1958 caused by influenza A(H2N2), as well as a distribution similar to the Hong Kong pandemic in 1968-1969 caused by influenza A(H3N2). We find the optimal vaccine distributions given that the number of doses is limited over the range of 10-90% of the population. While GA and RMHC work well in finding optimal vaccine distributions, GA is significantly more efficient than RMHC. We show that the optimal vaccine distribution found by GA and RMHC is up to 84% more effective than random mass vaccination in the mid range of vaccine availability. GA is generalizable to the optimization of stochastic model parameters for other infectious diseases and population structures.

Geosynchronous earth orbit/low earth orbit space object inspection and debris disposal: A preliminary analysis using a carrier satellite with deployable small satellites

NASA Astrophysics Data System (ADS)

Crockett, Derick

Detailed observations of geosynchronous satellites from earth are very limited. To better inspect these high altitude satellites, the use of small, refuelable satellites is proposed. The small satellites are stationed on a carrier platform in an orbit near the population of geosynchronous satellites. A carrier platform equipped with deployable, refuelable SmallSats is a viable option to inspect geosynchronous satellites. The propellant requirement to transfer to a targeted geosynchronous satellite, perform a proximity inspection mission, and transfer back to the carrier platform in a nearby orbit is determined. Convex optimization and traditional optimization techniques are explored, determining minimum propellant trajectories. Propellant is measured by the total required change in velocity, delta-v. The trajectories were modeled in a relative reference frame using the Clohessy-Wiltshire equations. Mass estimations for the carrier platform and the SmallSat were determined by using the rocket equation. The mass estimates were compared to the mass of a single, non-refuelable satellite performing the same geosynchronous satellite inspection missions. From the minimum delta-v trajectories and the mass analysis, it is determined that using refuelable SmallSats and a carrier platform in a nearby orbit can be more efficient than using a single non-refuelable satellite to perform multiple geosynchronous satellite inspections.

Adopting epidemic model to optimize medication and surgical intervention of excess weight

NASA Astrophysics Data System (ADS)

Sun, Ruoyan

2017-01-01

We combined an epidemic model with an objective function to minimize the weighted sum of people with excess weight and the cost of a medication and surgical intervention in the population. The epidemic model is consisted of ordinary differential equations to describe three subpopulation groups based on weight. We introduced an intervention using medication and surgery to deal with excess weight. An objective function is constructed taking into consideration the cost of the intervention as well as the weight distribution of the population. Using empirical data, we show that fixed participation rate reduces the size of obese population but increases the size for overweight. An optimal participation rate exists and decreases with respect to time. Both theoretical analysis and empirical example confirm the existence of an optimal participation rate, u*. Under u*, the weighted sum of overweight (S) and obese (O) population as well as the cost of the program is minimized. This article highlights the existence of an optimal participation rate that minimizes the number of people with excess weight and the cost of the intervention. The time-varying optimal participation rate could contribute to designing future public health interventions of excess weight.

Outbreak and Extinction Dynamics in a Stochastic Ebola Model

NASA Astrophysics Data System (ADS)

Nieddu, Garrett; Bianco, Simone; Billings, Lora; Forgoston, Eric; Kaufman, James

A zoonotic disease is a disease that can be passed between animals and humans. In many cases zoonotic diseases can persist in the animal population even if there are no infections in the human population. In this case we call the infected animal population the reservoir for the disease. Ebola virus disease (EVD) and SARS are both notable examples of such diseases. There is little work devoted to understanding stochastic disease extinction and reintroduction in the presence of a reservoir. Here we build a stochastic model for EVD and explicitly consider the presence of an animal reservoir. Using a master equation approach and a WKB ansatz, we determine the associated Hamiltonian of the system. Hamilton's equations are then used to numerically compute the 12-dimensional optimal path to extinction, which is then used to estimate mean extinction times. We also numerically investigate the behavior of the model for dynamic population size. Our results provide an improved understanding of outbreak and extinction dynamics in diseases like EVD.

[Equity of Health Resources Allocation in Minority Regions of Sichuan Province].

PubMed

Chen, Nan; Tang, Wen; Liang, Zhi; Zou, Bo; Li, Xiao-song

2016-03-01

To determine equity of health resources allocation in minority regions of Sichuan province from 2009 to 2013. Health resources distribution equity among populations and across geographic catchments were measured using coefficients of Inter-Individual differences and Individual-Mean differences. Health resources, especially human resources, in minority regions increased slowly over the years. Poorer allocation equity was found in nursing resources compared with doctors and hospital beds. Better distribution equity was found among populations than across geographic catchments. High levels of equity in resource distributions among populations and across geographic catchments were found in Aba. In Liangshan, more equitable distributions were found in doctors and hospital beds compared with nurses. The rest of minority regions had poor absolute allocation equity in doctors and hospital beds among populations. Appropriate allocation of health resources can promote health development. Health resources allocation in minority regions of Sichuan province is unreasonable. The government and relevant departments should take actions to optimize health resources allocations.

Balance of Interactions Determines Optimal Survival in Multi-Species Communities.

PubMed

Choudhary, Anshul; Sinha, Sudeshna

2015-01-01

We consider a multi-species community modelled as a complex network of populations, where the links are given by a random asymmetric connectivity matrix J, with fraction 1 - C of zero entries, where C reflects the over-all connectivity of the system. The non-zero elements of J are drawn from a Gaussian distribution with mean μ and standard deviation σ. The signs of the elements Jij reflect the nature of density-dependent interactions, such as predatory-prey, mutualism or competition, and their magnitudes reflect the strength of the interaction. In this study we try to uncover the broad features of the inter-species interactions that determine the global robustness of this network, as indicated by the average number of active nodes (i.e. non-extinct species) in the network, and the total population, reflecting the biomass yield. We find that the network transitions from a completely extinct system to one where all nodes are active, as the mean interaction strength goes from negative to positive, with the transition getting sharper for increasing C and decreasing σ. We also find that the total population, displays distinct non-monotonic scaling behaviour with respect to the product μC, implying that survival is dependent not merely on the number of links, but rather on the combination of the sparseness of the connectivity matrix and the net interaction strength. Interestingly, in an intermediate window of positive μC, the total population is maximal, indicating that too little or too much positive interactions is detrimental to survival. Rather, the total population levels are optimal when the network has intermediate net positive connection strengths. At the local level we observe marked qualitative changes in dynamical patterns, ranging from anti-phase clusters of period 2 cycles and chaotic bands, to fixed points, under the variation of mean μ of the interaction strengths. We also study the correlation between synchronization and survival, and find that synchronization does not necessarily lead to extinction. Lastly, we propose an effective low dimensional map to capture the behavior of the entire network, and this provides a broad understanding of the interplay of the local dynamical patterns and the global robustness trends in the network.

Mining in low coal. Volume 1. Biomechanics and work physiology. Open file report 15 Jun 78-15 Sep 81

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ayoub, M.M.; Bethea, N.J.; Bobo, M.

1981-11-01

The objectives of this research were (1) to evaluate the job demands associated with low coal mining, (2) to survey the anthropometry, strength, and aerobic capacity of low coal miners to determine if they differ from the U.S. population, and (3) to recommend, on the basis of available information, optimal job and work station design for low coal mining. The male and female anthropometry, except for weight and circumferential dimensions, was quite similar to the comparison populations. Back strength for male and female miners was significantly lower than the industrial worker population. This can be one of the contributing factorsmore » of low back problems in mining. Shoveling, timbering, and helpers tasks were physiologically demanding activities. However, because of the frequent stoppage of work, adequate rest was usually available. If work stoppage is corrected, then better work and rest schedules are essential.« less

The impact of translocations on neutral and functional genetic diversity within and among populations of the Seychelles warbler.

PubMed

Wright, David J; Spurgin, Lewis G; Collar, Nigel J; Komdeur, Jan; Burke, Terry; Richardson, David S

2014-05-01

Translocations are an increasingly common tool in conservation. The maintenance of genetic diversity through translocation is critical for both the short- and long-term persistence of populations and species. However, the relative spatio-temporal impacts of translocations on neutral and functional genetic diversity, and how this affects genetic structure among the conserved populations overall, have received little investigation. We compared the impact of translocating different numbers of founders on both microsatellite and major histocompatibility complex (MHC) class I diversity over a 23-year period in the Seychelles warbler (Acrocephalus sechellensis). We found low and stable microsatellite and MHC diversity in the source population and evidence for only a limited loss of either type of diversity in the four new populations. However, we found evidence of significant, but low to moderate, genetic differentiation between populations, with those populations established with fewer founders clustering separately. Stochastic genetic capture (as opposed to subsequent drift) was the main determinant of translocated population diversity. Furthermore, a strong correlation between microsatellite and MHC differentiation suggested that neutral processes outweighed selection in shaping MHC diversity in the new populations. These data provide important insights into how to optimize the use of translocation as a conservation tool. © 2014 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

The impact of translocations on neutral and functional genetic diversity within and among populations of the Seychelles warbler

PubMed Central

Wright, David J; Spurgin, Lewis G; Collar, Nigel J; Komdeur, Jan; Burke, Terry; Richardson, David S

2014-01-01

Translocations are an increasingly common tool in conservation. The maintenance of genetic diversity through translocation is critical for both the short- and long-term persistence of populations and species. However, the relative spatio-temporal impacts of translocations on neutral and functional genetic diversity, and how this affects genetic structure among the conserved populations overall, have received little investigation. We compared the impact of translocating different numbers of founders on both microsatellite and major histocompatibility complex (MHC) class I diversity over a 23-year period in the Seychelles warbler (Acrocephalus sechellensis). We found low and stable microsatellite and MHC diversity in the source population and evidence for only a limited loss of either type of diversity in the four new populations. However, we found evidence of significant, but low to moderate, genetic differentiation between populations, with those populations established with fewer founders clustering separately. Stochastic genetic capture (as opposed to subsequent drift) was the main determinant of translocated population diversity. Furthermore, a strong correlation between microsatellite and MHC differentiation suggested that neutral processes outweighed selection in shaping MHC diversity in the new populations. These data provide important insights into how to optimize the use of translocation as a conservation tool. PMID:24689851

Optimizing Surveillance Performance of Alpha-Fetoprotein by Selection of Proper Target Population in Chronic Hepatitis B

PubMed Central

Chung, Jung Wha; Kim, Beom Hee; Lee, Chung Seop; Kim, Gi Hyun; Sohn, Hyung Rae; Min, Bo Young; Song, Joon Chang; Park, Hyun Kyung; Jang, Eun Sun; Yoon, Hyuk; Kim, Jaihwan; Shin, Cheol Min; Park, Young Soo; Hwang, Jin-Hyeok; Jeong, Sook-Hyang; Kim, Nayoung; Lee, Dong Ho; Lee, Jaebong; Ahn, Soyeon

2016-01-01

Although alpha-fetoprotein (AFP) is the most widely used biomarker in hepatocellular carcinoma (HCC) surveillance, disease activity may also increase AFP levels in chronic hepatitis B (CHB). Since nucleos(t)ide analog (NA) therapy may reduce not only HBV viral loads and transaminase levels but also the falsely elevated AFP levels in CHB, we tried to determine whether exposure to NA therapy influences AFP performance and whether selective application can optimize the performance of AFP testing in CHB during HCC surveillance. A retrospective cohort of 6,453 CHB patients who received HCC surveillance was constructed from the electronic clinical data warehouse. Covariates of AFP elevation were determined from 53,137 AFP measurements, and covariate-specific receiver operating characteristics regression analysis revealed that albumin levels and exposure to NA therapy were independent determinants of AFP performance. C statistics were largest in patients with albumin levels ≥ 3.7 g/dL who were followed without NA therapy during study period, whereas AFP performance was poorest when tested in patients with NA therapy during study and albumin levels were < 3.7 g/dL (difference in C statics = 0.35, p < 0.0001). Contrary to expectation, CHB patients with current or recent exposure to NA therapy showed poorer performance of AFP during HCC surveillance. Combination of concomitant albumin levels and status of NA therapy can identify subgroup of CHB patients who will show optimized AFP performance. PMID:27997559

Tumor mismatch repair immunohistochemistry and DNA MLH1 methylation testing of patients with endometrial cancer diagnosed at age younger than 60 years optimizes triage for population-level germline mismatch repair gene mutation testing.

PubMed

Buchanan, Daniel D; Tan, Yen Y; Walsh, Michael D; Clendenning, Mark; Metcalf, Alexander M; Ferguson, Kaltin; Arnold, Sven T; Thompson, Bryony A; Lose, Felicity A; Parsons, Michael T; Walters, Rhiannon J; Pearson, Sally-Ann; Cummings, Margaret; Oehler, Martin K; Blomfield, Penelope B; Quinn, Michael A; Kirk, Judy A; Stewart, Colin J; Obermair, Andreas; Young, Joanne P; Webb, Penelope M; Spurdle, Amanda B

2014-01-10

Clinicopathologic data from a population-based endometrial cancer cohort, unselected for age or family history, were analyzed to determine the optimal scheme for identification of patients with germline mismatch repair (MMR) gene mutations. Endometrial cancers from 702 patients recruited into the Australian National Endometrial Cancer Study (ANECS) were tested for MMR protein expression using immunohistochemistry (IHC) and for MLH1 gene promoter methylation in MLH1-deficient cases. MMR mutation testing was performed on germline DNA of patients with MMR-protein deficient tumors. Prediction of germline mutation status was compared for combinations of tumor characteristics, age at diagnosis, and various clinical criteria (Amsterdam, Bethesda, Society of Gynecologic Oncology, ANECS). Tumor MMR-protein deficiency was detected in 170 (24%) of 702 cases. Germline testing of 158 MMR-deficient cases identified 22 truncating mutations (3% of all cases) and four unclassified variants. Tumor MLH1 methylation was detected in 99 (89%) of 111 cases demonstrating MLH1/PMS2 IHC loss; all were germline MLH1 mutation negative. A combination of MMR IHC plus MLH1 methylation testing in women younger than 60 years of age at diagnosis provided the highest positive predictive value for the identification of mutation carriers at 46% versus ≤ 41% for any other criteria considered. Population-level identification of patients with MMR mutation-positive endometrial cancer is optimized by stepwise testing for tumor MMR IHC loss in patients younger than 60 years, tumor MLH1 methylation in individuals with MLH1 IHC loss, and germline mutations in patients exhibiting loss of MSH6, MSH2, or PMS2 or loss of MLH1/PMS2 with absence of MLH1 methylation.

Preparedness for pandemics: does variation among states affect the nation as a whole?

PubMed

Potter, Margaret A; Brown, Shawn T; Lee, Bruce Y; Grefenstette, John; Keane, Christopher R; Lin, Chyongchiou J; Quinn, Sandra C; Stebbins, Samuel; Sweeney, Patricia M; Burke, Donald S

2012-01-01

Since states' public health systems differ as to pandemic preparedness, this study explored whether such heterogeneity among states could affect the nation's overall influenza rate. The Centers for Disease Control and Prevention produced a uniform set of scores on a 100-point scale from its 2008 national evaluation of state preparedness to distribute materiel from the Strategic National Stockpile (SNS). This study used these SNS scores to represent each state's relative preparedness to distribute influenza vaccine in a timely manner and assumed that "optimal" vaccine distribution would reach at least 35% of the state's population within 4 weeks. The scores were used to determine the timing of vaccine distribution for each state: each 10-point decrement of score below 90 added an additional delay increment to the distribution time. A large-scale agent-based computational model simulated an influenza pandemic in the US population. In this synthetic population each individual or agent had an assigned household, age, workplace or school destination, daily commute, and domestic intercity air travel patterns. Simulations compared influenza case rates both nationally and at the state level under 3 scenarios: no vaccine distribution (baseline), optimal vaccine distribution in all states, and vaccine distribution time modified according to state-specific SNS score. Between optimal and SNS-modified scenarios, attack rates rose not only in low-scoring states but also in high-scoring states, demonstrating an interstate spread of infections. Influenza rates were sensitive to variation of the SNS-modified scenario (delay increments of 1 day versus 5 days), but the interstate effect remained. The effectiveness of a response activity such as vaccine distribution could benefit from national standards and preparedness funding allocated in part to minimize interstate disparities.

Clonal analysis of synovial fluid stem cells to characterize and identify stable mesenchymal stromal cell/mesenchymal progenitor cell phenotypes in a porcine model: a cell source with enhanced commitment to the chondrogenic lineage.

PubMed

Ando, Wataru; Kutcher, Josh J; Krawetz, Roman; Sen, Arindom; Nakamura, Norimasa; Frank, Cyril B; Hart, David A

2014-06-01

Previous studies have demonstrated that porcine synovial membrane stem cells can adhere to a cartilage defect in vivo through the use of a tissue-engineered construct approach. To optimize this model, we wanted to compare effectiveness of tissue sources to determine whether porcine synovial fluid, synovial membrane, bone marrow and skin sources replicate our understanding of synovial fluid mesenchymal stromal cells or mesenchymal progenitor cells from humans both at the population level and the single-cell level. Synovial fluid clones were subsequently isolated and characterized to identify cells with a highly characterized optimal phenotype. The chondrogenic, osteogenic and adipogenic potentials were assessed in vitro for skin, bone marrow, adipose, synovial fluid and synovial membrane-derived stem cells. Synovial fluid cells then underwent limiting dilution analysis to isolate single clonal populations. These clonal populations were assessed for proliferative and differentiation potential by use of standardized protocols. Porcine-derived cells demonstrated the same relationship between cell sources as that demonstrated previously for humans, suggesting that the pig may be an ideal preclinical animal model. Synovial fluid cells demonstrated the highest chondrogenic potential that was further characterized, demonstrating the existence of a unique clonal phenotype with enhanced chondrogenic potential. Porcine stem cells demonstrate characteristics similar to those in human-derived mesenchymal stromal cells from the same sources. Synovial fluid-derived stem cells contain an inherent phenotype that may be optimal for cartilage repair. This must be more fully investigated for future use in the in vivo tissue-engineered construct approach in this physiologically relevant preclinical porcine model. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Synthesis: Deriving a Core Set of Recommendations to Optimize Diabetes Care on a Global Scale.

PubMed

Mechanick, Jeffrey I; Leroith, Derek

2015-01-01

Diabetes afflicts 382 million people worldwide, with increasing prevalence rates and adverse effects on health, well-being, and society in general. There are many drivers for the complex presentation of diabetes, including environmental and genetic/epigenetic factors. The aim was to synthesize a core set of recommendations from information from 14 countries that can be used to optimize diabetes care on a global scale. Information from 14 papers in this special issue of Annals of Global Health was reviewed, analyzed, and sorted to synthesize recommendations. PubMed was searched for relevant studies on diabetes and global health. Key findings are as follows: (1) Population-based transitions distinguish region-specific diabetes care; (2) biological drivers for diabetes differ among various populations and need to be clarified scientifically; (3) principal resource availability determines quality-of-care metrics; and (4) governmental involvement, independent of economic barriers, improves the contextualization of diabetes care. Core recommendations are as follows: (1) Each nation should assess region-specific epidemiology, the scientific evidence base, and population-based transitions to establish risk-stratified guidelines for diagnosis and therapeutic interventions; (2) each nation should establish a public health imperative to provide tools and funding to successfully implement these guidelines; and (3) each nation should commit to education and research to optimize recommendations for a durable effect. Systematic acquisition of information about diabetes care can be analyzed, extrapolated, and then used to provide a core set of actionable recommendations that may be further studied and implemented to improve diabetes care on a global scale. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

More rapid climate change promotes evolutionary rescue through selection for increased dispersal distance.

PubMed

Boeye, Jeroen; Travis, Justin M J; Stoks, Robby; Bonte, Dries

2013-02-01

Species can either adapt to new conditions induced by climate change or shift their range in an attempt to track optimal environmental conditions. During current range shifts, species are simultaneously confronted with a second major anthropogenic disturbance, landscape fragmentation. Using individual-based models with a shifting climate window, we examine the effect of different rates of climate change on the evolution of dispersal distances through changes in the genetically determined dispersal kernel. Our results demonstrate that the rate of climate change is positively correlated to the evolved dispersal distances although too fast climate change causes the population to crash. When faced with realistic rates of climate change, greater dispersal distances evolve than those required for the population to keep track of the climate, thereby maximizing population size. Importantly, the greater dispersal distances that evolve when climate change is more rapid, induce evolutionary rescue by facilitating the population in crossing large gaps in the landscape. This could ensure population persistence in case of range shifting in fragmented landscapes. Furthermore, we highlight problems in using invasion speed as a proxy for potential range shifting abilities under climate change.

Optimization modeling to maximize population access to comprehensive stroke centers

PubMed Central

Branas, Charles C.; Kasner, Scott E.; Wolff, Catherine; Williams, Justin C.; Albright, Karen C.; Carr, Brendan G.

2015-01-01

Objective: The location of comprehensive stroke centers (CSCs) is critical to ensuring rapid access to acute stroke therapies; we conducted a population-level virtual trial simulating change in access to CSCs using optimization modeling to selectively convert primary stroke centers (PSCs) to CSCs. Methods: Up to 20 certified PSCs per state were selected for conversion to maximize the population with 60-minute CSC access by ground and air. Access was compared across states based on region and the presence of state-level emergency medical service policies preferentially routing patients to stroke centers. Results: In 2010, there were 811 Joint Commission PSCs and 0 CSCs in the United States. Of the US population, 65.8% had 60-minute ground access to PSCs. After adding up to 20 optimally located CSCs per state, 63.1% of the US population had 60-minute ground access and 86.0% had 60-minute ground/air access to a CSC. Across states, median CSC access was 55.7% by ground (interquartile range 35.7%–71.5%) and 85.3% by ground/air (interquartile range 59.8%–92.1%). Ground access was lower in Stroke Belt states compared with non–Stroke Belt states (32.0% vs 58.6%, p = 0.02) and lower in states without emergency medical service routing policies (52.7% vs 68.3%, p = 0.04). Conclusion: Optimal system simulation can be used to develop efficient care systems that maximize accessibility. Under optimal conditions, a large proportion of the US population will be unable to access a CSC within 60 minutes. PMID:25740858

Optimization modeling to maximize population access to comprehensive stroke centers.

PubMed

Mullen, Michael T; Branas, Charles C; Kasner, Scott E; Wolff, Catherine; Williams, Justin C; Albright, Karen C; Carr, Brendan G

2015-03-24

The location of comprehensive stroke centers (CSCs) is critical to ensuring rapid access to acute stroke therapies; we conducted a population-level virtual trial simulating change in access to CSCs using optimization modeling to selectively convert primary stroke centers (PSCs) to CSCs. Up to 20 certified PSCs per state were selected for conversion to maximize the population with 60-minute CSC access by ground and air. Access was compared across states based on region and the presence of state-level emergency medical service policies preferentially routing patients to stroke centers. In 2010, there were 811 Joint Commission PSCs and 0 CSCs in the United States. Of the US population, 65.8% had 60-minute ground access to PSCs. After adding up to 20 optimally located CSCs per state, 63.1% of the US population had 60-minute ground access and 86.0% had 60-minute ground/air access to a CSC. Across states, median CSC access was 55.7% by ground (interquartile range 35.7%-71.5%) and 85.3% by ground/air (interquartile range 59.8%-92.1%). Ground access was lower in Stroke Belt states compared with non-Stroke Belt states (32.0% vs 58.6%, p = 0.02) and lower in states without emergency medical service routing policies (52.7% vs 68.3%, p = 0.04). Optimal system simulation can be used to develop efficient care systems that maximize accessibility. Under optimal conditions, a large proportion of the US population will be unable to access a CSC within 60 minutes. © 2015 American Academy of Neurology.

Potential of Aqueous Ozone to Control Aflatoxigenic Fungi in Brazil Nuts

PubMed Central

Morales-Valle, Héctor; Venâncio, Armando

2013-01-01

This study aimed to verify the use of aqueous ozone as alternative technology for fungal control. Brazil nuts sterilized were inoculated with either 1 × 106 or 1 × 107 conidia mL−1 of Aspergillus flavus (MUM 9201) to determine optimal treatment parameters and different aqueous ozone contact times. These assays showed that the effect of ozone is almost immediate against A. flavus, and the optimum ozone concentration depended on the number of initial viable spores on the shell. The remaining viable spores in the ozone solution were recorded, and the rate of inactivation for each treatment was determined by assessing the ratio between the cfu of each treatment and the control. The ozonized nuts were also cultured to recover the fungal population. Aqueous ozone was effective in reducing the conidia of A. flavus and the natural fungal population associated with Brazil nuts. Aqueous ozone presented a great potential to reduce microorganisms counts in Brazil nuts with a great potential use in packing houses for decontamination step. PMID:25937982

Evaluating Strategies For Reducing Health Disparities By Addressing The Social Determinants Of Health

PubMed Central

Thornton, Rachel L. J.; Glover, Crystal M.; Cené, Crystal W.; Glik, Deborah C.; Henderson, Jeffrey A.; Williams, David R.

2017-01-01

Research reveals that the opportunities for healthy choices in homes, neighborhoods, schools, and workplaces can have decisive impacts on health. This article reviews scientific evidence from promising interventions focused on the social determinants of health, and describes ways in which they can improve population health and reduce health disparities. We show that there is sufficient evidence to support policy interventions targeted at education and early childhood; urban planning and community development; housing; income enhancements and supplements; and employment. When available, cost-effectiveness evaluations show that these interventions lead to long-term societal savings; however, more routine attention to cost considerations is needed for these interventions. We also discuss challenges to implementation, including the need for long-term financing in order to scale-up effective interventions for implementation at the local, state, or national level. Although we know enough to act, questions remain about how to optimally scale-up these interventions and maximize their benefits for the most vulnerable populations. PMID:27503966

The role of cold plasma and its composition on the growth of electromagnetic ion cyclotron waves in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Snelling, J. M.; Johnson, J.; Engebretson, M. J.; Kim, E. H.; Tian, S.

2017-12-01

While it is currently well accepted that the free energy for growth of electromagnetic ion cyclotron (EMIC) waves in Earth's magnetosphere comes from unstable configurations of hot anisotropic ions that are injected into the ring current, several questions remain about what controls the instability. A recent study of the occurrence of EMIC waves relative to the plasmapause in Vallen Probes Data showed that plasma density gradients or enhancements were not the dominant factor in determining the site of EMIC wave generation [Tetrick et al. 2017]. However, the factors that control wave growth on each of the branches are not fully understood. For example, in some cases, the measured anisotropy is not adequate to explain local instability, and the relative importance of the density and composition of a cold plasma population is still uncertain. Several intervals of EMIC wave activity are analyzed to determine the role of a cold population in driving instability on each of the wave branches. This study utilizes the WHAMP (Waves in Homogeneous Anisotropic Magnetized Plasma) stability code with plasma distributions optimized to fit the observed distributions including temperature anisotropy, loss cone, and ring beam populations.

Diagnostic Performance of Afternoon Urine Osmolality to Assess Optimal Hydration Status in an Adult Healthy Population.

PubMed

Hustrini, Ni Made; Siregar, Parlindungan; Nainggolan, Ginova; Harimurti, Kuntjoro

2017-04-01

optimal hydration represents adequate total daily fluid intake to compensate for daily water losses, ensure adequate urine output to reduce the risk of urolithiasis and renal function decline, and also avoid the production of arginine vasopressin (AVP). Twenty-four-hour urine osmolality has been used to assess hydration status, but it is challenging because of the possibility of spilling urine and limitation of daily activities. This study is aimed to determine the performance of the afternoon urine osmolality to assess the optimal hydration status compared with 24-hour urine osmolality. a cross sectional study was conducted on healthy employees aged 18-59 years at Universitas Indonesia Medical Faculty/Cipto Mangunkusumo Hospital, with consecutive sampling method. The ROC curve was analyzed to obtain the optimal cut off point and the accuracy of the afternoon urine osmolality in assessing the optimal hydration status. between August-September 2016 there were 120 subjects (73.8% female, median age 32 years) who met the study criteria with a median 24-hour urine osmolality 463.5 (95% CI, 136-1427) mOsm/kg H2O and median afternoon urine osmolality 513 (95% CI, 73-1267). We found moderate correlation (r=0.59; p<0.001) between afternoon urine osmolality and a 24-hour urine osmolality. Using ROC curve, the AUC value was 0.792 (95% CI, 0.708-0.875) with the cut off 528 mOsm/kg H2O. To assess the optimal hydration status, the afternoon urine osmolality had the sensitivity of 0.7 (95% CI, 0.585-0.795) and the specificity of 0.76 (95% CI, 0.626-0.857), Likelihood Ratio (LR) (+) 2.917 (95% CI, 1.74-4.889) and LR (-) 0.395 (95% CI, 0.267-0.583). afternoon urine osmolality can be used as a diagnostic tool to assess the optimal hydration status in healthy population with cut off 528 mOsm/kg H2O, sensitivity of 0.7, and specificity of 0.76.

Determining median urinary iodine concentration that indicates adequate iodine intake at population level.

PubMed Central

Delange, François; de Benoist, Bruno; Burgi, Hans

2002-01-01

OBJECTIVE: Urinary iodine concentration is the prime indicator of nutritional iodine status and is used to evaluate population-based iodine supplementation. In 1994, WHO, UNICEF and ICCIDD recommended median urinary iodine concentrations for populations of 100- 200 micro g/l, assuming the 100 micro g/l threshold would limit concentrations <50 micro g/l to 100 micro g/l. The total population was 55 892, including 35 661 (64%) schoolchildren. Median urinary iodine concentrations were 111-540 (median 201) micro g/l for all populations, 100-199 micro g/l in 23 (48%) populations and >/=200 micro g/l in 25 (52%). The frequencies of values <50 micro g/l were 0-20.8 (mean 4.8%) overall and 7.2% and 2.5% in populations with medians of 100-199 micro g/l and >200 micro g/l, respectively. The frequency reached 20% only in two places where iodine had been supplemented for <2 years. CONCLUSION: The frequency of urinary iodine concentrations <50 micro g/l in populations with median urinary iodine concentrations >/=100 micro g/l has been overestimated. The threshold of 100 micro g/l does not need to be increased. In populations, median urinary iodine concentrations of 100-200 micro g/l indicate adequate iodine intake and optimal iodine nutrition. PMID:12219154

An eHealth Intervention to Promote Physical Activity and Social Network of Single, Chronically Impaired Older Adults: Adaptation of an Existing Intervention Using Intervention Mapping.

PubMed

Boekhout, Janet M; Peels, Denise A; Berendsen, Brenda Aj; Bolman, Catherine Aw; Lechner, Lilian

2017-11-23

Especially for single older adults with chronic diseases, physical inactivity and a poor social network are regarded as serious threats to their health and independence. The Active Plus intervention is an automated computer-tailored eHealth intervention that has been proven effective to promote physical activity (PA) in the general population of adults older than 50 years. The aim of this study was to report on the methods and results of the systematic adaptation of Active Plus to the wishes and needs of the subgroup of single people older than 65 years who have one or more chronic diseases, as this specific target population may encounter specific challenges regarding PA and social network. The Intervention Mapping (IM) protocol was used to systematically adapt the existing intervention to optimally suit this specific target population. A literature study was performed, and quantitative as well as qualitative data were derived from health care professionals (by questionnaires, n=10) and the target population (by focus group interviews, n=14), which were then systematically integrated into the adapted intervention. As the health problems and the targeted behavior are largely the same in the original and adapted intervention, the outcome of the needs assessment was that the performance objectives remained the same. As found in the literature study and in data derived from health professionals and focus groups, the relative importance and operationalization of the relevant psychosocial determinants related to these objectives are different from the original intervention, resulting in a refinement of the change objectives to optimally fit the specific target population. This refinement also resulted in changes in the practical applications, program components, intervention materials, and the evaluation and implementation strategy for the subgroup of single, chronically impaired older adults. This study demonstrates that the adaptation of an existing intervention is an intensive process in which adopting the IM protocol is an invaluable tool. The study provides a broad insight in adapting interventions aimed at single older adults with a chronic disease. It is concluded that even when the new target population is a sizable segment of the original target population, the adapted intervention still needs considerable changes to optimally fit the needs and situational differences of the narrower target population. ©Janet M Boekhout, Denise A Peels, Brenda AJ Berendsen, Catherine AW Bolman, Lilian Lechner. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 23.11.2017.

Optimal information networks: Application for data-driven integrated health in populations

PubMed Central

Servadio, Joseph L.; Convertino, Matteo

2018-01-01

Development of composite indicators for integrated health in populations typically relies on a priori assumptions rather than model-free, data-driven evidence. Traditional variable selection processes tend not to consider relatedness and redundancy among variables, instead considering only individual correlations. In addition, a unified method for assessing integrated health statuses of populations is lacking, making systematic comparison among populations impossible. We propose the use of maximum entropy networks (MENets) that use transfer entropy to assess interrelatedness among selected variables considered for inclusion in a composite indicator. We also define optimal information networks (OINs) that are scale-invariant MENets, which use the information in constructed networks for optimal decision-making. Health outcome data from multiple cities in the United States are applied to this method to create a systemic health indicator, representing integrated health in a city. PMID:29423440

Applicability of meteor radiant determination methods depending on orbit type. II. Low-eccentric orbits

NASA Astrophysics Data System (ADS)

Svoren, J.; Neslusan, L.; Porubcan, V.

1994-08-01

All known parent bodies of meteor showers belong to bodies moving in high-eccentricity orbits (e => 0.5). Recently, asteroids in low-eccentricity orbits (e < 0.5) approaching the Earth's orbit, were suggested as another population of possible parent bodies of meteor streams. This paper deals with the problem of calculation of meteor radiants connected with the bodies in low-eccentricity orbits from the point of view of optimal results depending on the method applied. The paper is a continuation of our previous analysis of high-eccentricity orbits (Svoren, J., Neslusan, L., Porubcan, V.: 1993, Contrib. Astron. Obs. Skalnate Pleso 23, 23). Some additional methods resulting from mathematical modelling are presented and discussed together with Porter's, Steel-Baggaley's and Hasegawa's methods. In order to be able to compare how suitable the application of the individual radiant determination methods is, it is necessary to determine the accuracy with which they approximate real meteor orbits. To verify the accuracy with which the orbit of a meteoroid with at least one node at 1 AU fits the original orbit of the parent body, the Southworth-Hawkins D-criterion (Southworth, R.B., Hawkins, G.S.: 1963, Smithson. Contr. Astrophys. 7, 261) was applied. D <= 0.1 indicates a very good fit of orbits, 0.1 < D <= 0.2 is considered for a good fit and D > 0.2 means that the fit is rather poor and the change of orbit unrealistic. The optimal method, i.e. the one which results in the smallest D values for the population of low-eccentricity orbits, is that of adjusting the orbit by varying both the eccentricity and perihelion distance. A comparison of theoretical radiants obtained by various methods was made for typical representatives from each group of the NEA (near-Earth asteroids) objects.

Demography of soybean aphid (Homoptera: Aphididae) at summer temperatures.

PubMed

McCornack, B P; Ragsdale, D W; Venette, R C

2004-06-01

Soybean aphid, Aphis glycines Matsumura, is now widely established in soybean, Glycine max L., production areas of the northern United States and southern Canada and is becoming an important economic pest. Temperature effect on soybean aphid fecundity and survivorship is not well understood. We determined the optimal temperature for soybean aphid growth and reproduction on soybean under controlled conditions. We constructed life tables for soybean aphid at 20, 25, 30, and 35 degrees C with a photoperiod of 16:8 (L:D) h. Population growth rates were greatest at 25 degrees C. As temperature increased, net fecundity, gross fecundity, generation time, and life expectancy decreased. The prereproductive period did not differ between 20 and 30 degrees C; however, at 30 degrees C aphids required more degree-days (base 8.6 degrees C) to develop. Nymphs exposed to 35 degrees C did not complete development, and all individuals died within 11 d. Reproductive periods were significantly different at all temperatures, with aphids reproducing longer and producing more progeny at 20 and 25 degrees C than at 30 or 35 degrees C. Using a modification of the nonlinear Logan model, we estimated upper and optimal developmental thresholds to be 34.9 and 27.8 degrees C, respectively. At 25 degrees C, aphid populations doubled in 1.5 d; at 20 and 30 degrees C, populations doubled in 1.9 d.

Stratification strategy for evaluating the influence of diabetes complication severity index on the risk of hospitalization: a record linkage data in Western Australia.

PubMed

Ha, Ninh Thi; Harris, Mark; Robinson, Suzanne; Preen, David; Moorin, Rachael

2017-07-01

This study aimed to develop a risk stratification strategy for evaluating the relationship between complications of diabetes and the risk of diabetic-related hospitalization to accurately classify diabetes severity. The study used administrative health records for 40,624 individuals with diabetes aged ≥18years in Western Australian. The adapted Diabetes Complication Severity Index (DCSI), socio-demographic and clinical characteristics were used in random effects negative binomial and threshold effect models to determine the optimal stratification strategy for diabetes severity based on the homogeneity of the risk of hospitalization in response to variation of the DCSI. The optimal stratification of people with diabetes was specified by four sub-populations. The first sub-population was no complications with an inverse association with the risk of hospitalizations (coefficient-0.247, SE 0.03). Further three sub-populations with DCSI at one (coefficient 0.289, SE 0.01), two (coefficient 0.339, SE 0.01) and three or more (coefficient 0.381, SE 0.01) were used to accurately describe the impact of DCSI on the risk of hospitalization. A stratification into four subpopulations based on the homogeneous impact of diabetes DCSI on the risk of hospitalization may be more suitable for evaluating health care interventions and planning health care provision. Copyright © 2017 Elsevier Inc. All rights reserved.

CellSort: a support vector machine tool for optimizing fluorescence-activated cell sorting and reducing experimental effort.

PubMed

Yu, Jessica S; Pertusi, Dante A; Adeniran, Adebola V; Tyo, Keith E J

2017-03-15

High throughput screening by fluorescence activated cell sorting (FACS) is a common task in protein engineering and directed evolution. It can also be a rate-limiting step if high false positive or negative rates necessitate multiple rounds of enrichment. Current FACS software requires the user to define sorting gates by intuition and is practically limited to two dimensions. In cases when multiple rounds of enrichment are required, the software cannot forecast the enrichment effort required. We have developed CellSort, a support vector machine (SVM) algorithm that identifies optimal sorting gates based on machine learning using positive and negative control populations. CellSort can take advantage of more than two dimensions to enhance the ability to distinguish between populations. We also present a Bayesian approach to predict the number of sorting rounds required to enrich a population from a given library size. This Bayesian approach allowed us to determine strategies for biasing the sorting gates in order to reduce the required number of enrichment rounds. This algorithm should be generally useful for improve sorting outcomes and reducing effort when using FACS. Source code available at http://tyolab.northwestern.edu/tools/ . k-tyo@northwestern.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Computational design of nanoparticle drug delivery systems for selective targeting

NASA Astrophysics Data System (ADS)

Duncan, Gregg A.; Bevan, Michael A.

2015-09-01

Ligand-functionalized nanoparticles capable of selectively binding to diseased versus healthy cell populations are attractive for improved efficacy of nanoparticle-based drug and gene therapies. However, nanoparticles functionalized with high affinity targeting ligands may lead to undesired off-target binding to healthy cells. In this work, Monte Carlo simulations were used to quantitatively determine net surface interactions, binding valency, and selectivity between targeted nanoparticles and cell surfaces. Dissociation constant, KD, and target membrane protein density, ρR, are explored over a range representative of healthy and cancerous cell surfaces. Our findings show highly selective binding to diseased cell surfaces can be achieved with multiple, weaker affinity targeting ligands that can be further optimized by varying the targeting ligand density, ρL. Using the approach developed in this work, nanomedicines can be optimally designed for exclusively targeting diseased cells and tissues.Ligand-functionalized nanoparticles capable of selectively binding to diseased versus healthy cell populations are attractive for improved efficacy of nanoparticle-based drug and gene therapies. However, nanoparticles functionalized with high affinity targeting ligands may lead to undesired off-target binding to healthy cells. In this work, Monte Carlo simulations were used to quantitatively determine net surface interactions, binding valency, and selectivity between targeted nanoparticles and cell surfaces. Dissociation constant, KD, and target membrane protein density, ρR, are explored over a range representative of healthy and cancerous cell surfaces. Our findings show highly selective binding to diseased cell surfaces can be achieved with multiple, weaker affinity targeting ligands that can be further optimized by varying the targeting ligand density, ρL. Using the approach developed in this work, nanomedicines can be optimally designed for exclusively targeting diseased cells and tissues. Electronic supplementary information (ESI) available: Movie showing simulation renderings of targeted (ρL = 1820/μm2, KD = 120 μM) nanoparticle selective binding to cancer (ρR = 256/μm2) vs. healthy (ρR = 64/μm2) cell surfaces. Target membrane proteins have linear color scale depending on binding energy ranging from white when unbound (URL = 0) to red when tightly bound (URL = UM). See DOI: 10.1039/c5nr03691g

Evidence-based optimal number of radiotherapy fractions for cancer: A useful tool to estimate radiotherapy demand.

PubMed

Wong, Karen; Delaney, Geoff P; Barton, Michael B

2016-04-01

The recently updated optimal radiotherapy utilisation model estimated that 48.3% of all cancer patients should receive external beam radiotherapy at least once during their disease course. Adapting this model, we constructed an evidence-based model to estimate the optimal number of fractions for notifiable cancers in Australia to determine equipment and workload implications. The optimal number of fractions was calculated based on the frequency of specific clinical conditions where radiotherapy is indicated and the evidence-based recommended number of fractions for each condition. Sensitivity analysis was performed to assess the impact of variables on the model. Of the 27 cancer sites, the optimal number of fractions for the first course of radiotherapy ranged from 0 to 23.3 per cancer patient, and 1.5 to 29.1 per treatment course. Brain, prostate and head and neck cancers had the highest average number of fractions per course. Overall, the optimal number of fractions was 9.4 per cancer patient (range 8.7-10.0) and 19.4 per course (range 18.0-20.7). These results provide valuable data for radiotherapy services planning and comparison with actual practice. The model can be easily adapted by inserting population-specific epidemiological data thus making it applicable to other jurisdictions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Optimal control of the orientation and alignment of an asymmetric-top molecule with terahertz and laser pulses

NASA Astrophysics Data System (ADS)

Coudert, L. H.

2018-03-01

Quantum optimal control theory is applied to determine numerically the terahertz and nonresonant laser pulses leading, respectively, to the highest degree of orientation and alignment of the asymmetric-top H2S molecule. The optimized terahertz pulses retrieved for temperatures of zero and 50 K lead after 50 ps to an orientation with ⟨ΦZx⟩ = 0.959 73 and ⟨⟨ΦZx⟩⟩ = 0.742 30, respectively. For the zero temperature, the orientation is close to its maximum theoretical value; for the higher temperature, it is below the maximum theoretical value. The mechanism by which the terahertz pulse populates high lying rotational levels is elucidated. The 5 ps long optimized laser pulse calculated for a zero temperature leads to an alignment with ⟨ΦZy 2 ⟩ =0.944 16 and consists of several kick pulses with a duration of ≈0.1 ps. It is found that the timing of these kick pulses is such that it leads to an increase of the rotational energy of the molecule. The optimized laser pulse retrieved for a temperature of 20 K is 6 ps long and yields a lower alignment with ⟨⟨ΦZy 2 ⟩ ⟩ =0.717 20 .

Newborn screening of glucose-6-phosphate dehydrogenase deficiency in Guangxi, China: determination of optimal cutoff value to identify heterozygous female neonates.

PubMed

Fu, Chunyun; Luo, Shiyu; Li, Qifei; Xie, Bobo; Yang, Qi; Geng, Guoxing; Lin, Caijuan; Su, Jiasun; Zhang, Yue; Wang, Jin; Qin, Zailong; Luo, Jingsi; Chen, Shaoke; Fan, Xin

2018-01-16

The aim of this study is to assess the disease incidence and mutation spectrum of glucose-6-phosphate dehydrogenase (G6PD) deficiency in Guangxi, China, and to determine an optimal cutoff value to identify heterozygous female neonates. A total of 130, 635 neonates were screened from the year of 2013 to 2017. Neonates suspected for G6PD deficiency were further analyzed by quantitatively enzymatic assay and G6PD mutation analysis. The overall incidence of G6PD deficiency was 7.28%. A total of 14 G6PD mutations were identified, and different mutations lead to varying levels of G6PD enzymatic activities. The best cut-off value of G6PD activity in male subjects is 2.2 U/g Hb, same as conventional setting. In female population, however, the cut-off value is found to be 2.8 U/g Hb (sensitivity: 97.5%, specificity: 87.7%, AUC: 0.964) to best discriminate between normal and heterozygotes, and 1.6 U/g Hb (sensitivity: 82.2%, specificity: 85.9%, AUC: 0.871) between heterozygotes and deficient subjects. In conclusion, we have conducted a comprehensive newborn screening of G6PD deficiency in a large cohort of population from Guangxi, China, and first established a reliable cut-off value of G6PD activity to distinguish heterozygous females from either normal or deficient subjects.

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Validation of a dye stain assay for vaginally inserted HEC-filled microbicide applicators

PubMed Central

Katzen, Lauren L.; Fernández-Romero, José A.; Sarna, Avina; Murugavel, Kailapuri G.; Gawarecki, Daniel; Zydowsky, Thomas M.; Mensch, Barbara S.

2011-01-01

Background The reliability and validity of self-reports of vaginal microbicide use are questionable given the explicit understanding that participants are expected to comply with study protocols. Our objective was to optimize the Population Council's previously validated dye stain assay (DSA) and related procedures, and establish predictive values for the DSA's ability to identify vaginally inserted single-use, low-density polyethylene microbicide applicators filled with hydroxyethylcellulose gel. Methods Applicators, inserted by 252 female sex workers enrolled in a microbicide feasibility study in Southern India, served as positive controls for optimization and validation experiments. Prior to validation, optimal dye concentration and staining time were ascertained. Three validation experiments were conducted to determine sensitivity, specificity, negative predictive values and positive predictive values. Results The dye concentration of 0.05% (w/v) FD&C Blue No. 1 Granular Food Dye and staining time of five seconds were determined to be optimal and were used for the three validation experiments. There were a total of 1,848 possible applicator readings across validation experiments; 1,703 (92.2%) applicator readings were correct. On average, the DSA performed with 90.6% sensitivity, 93.9% specificity, and had a negative predictive value of 93.8% and a positive predictive value of 91.0%. No statistically significant differences between experiments were noted. Conclusions The DSA was optimized and successfully validated for use with single-use, low-density polyethylene applicators filled with hydroxyethylcellulose (HEC) gel. We recommend including the DSA in future microbicide trials involving vaginal gels in order to identify participants who have low adherence to dosing regimens. In doing so, we can develop strategies to improve adherence as well as investigate the association between product use and efficacy. PMID:21992983

Hybrid maize breeding with doubled haploids: I. One-stage versus two-stage selection for testcross performance.

PubMed

Longin, C Friedrich H; Utz, H Friedrich; Reif, Jochen C; Schipprack, Wolfgang; Melchinger, Albrecht E

2006-03-01

Optimum allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the optimum allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain deltaG(k) and the probability P(k) of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the optimum allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the optimum allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, optimum allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability P(k) of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, P(k) > 75% was reached only for genotypes belonging to the best 5% of the population. As the optimum allocation for P(k)(5%) was similar to that for deltaG(k), the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the optimum number of locations and on values of the optimization criteria.

Optimal Vaccination in a Stochastic Epidemic Model of Two Non-Interacting Populations

DTIC Science & Technology

2015-02-17

of diminishing returns from vacci- nation will generally take place at smaller vaccine allocations V compared to the deterministic model. Optimal...take place and small r0 values where it does not is illustrat- ed in Fig. 4C. As r0 is decreased, the region between the two instances of switching...approximately distribute vaccine in proportion to population size. For large r0 (r0 ≳ 2.9), two switches take place . In the deterministic optimal solution, a

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

PubMed

Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz

2014-01-01

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

Multiobjective evolutionary optimization of water distribution systems: Exploiting diversity with infeasible solutions.

PubMed

Tanyimboh, Tiku T; Seyoum, Alemtsehay G

2016-12-01

This article investigates the computational efficiency of constraint handling in multi-objective evolutionary optimization algorithms for water distribution systems. The methodology investigated here encourages the co-existence and simultaneous development including crossbreeding of subpopulations of cost-effective feasible and infeasible solutions based on Pareto dominance. This yields a boundary search approach that also promotes diversity in the gene pool throughout the progress of the optimization by exploiting the full spectrum of non-dominated infeasible solutions. The relative effectiveness of small and moderate population sizes with respect to the number of decision variables is investigated also. The results reveal the optimization algorithm to be efficient, stable and robust. It found optimal and near-optimal solutions reliably and efficiently. The real-world system based optimization problem involved multiple variable head supply nodes, 29 fire-fighting flows, extended period simulation and multiple demand categories including water loss. The least cost solutions found satisfied the flow and pressure requirements consistently. The best solutions achieved indicative savings of 48.1% and 48.2% based on the cost of the pipes in the existing network, for populations of 200 and 1000, respectively. The population of 1000 achieved slightly better results overall. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Remote sensing and ichthyoplankton ecology of coastal upwelling fronts off central California

NASA Astrophysics Data System (ADS)

Bjorkstedt, Eric Peter

1998-11-01

Recruitment to many marine populations is determined by processes affecting survival and transport of planktonic larvae. Coastal upwelling poses a trade-off between larval access to high productivity supported by upwelled nutrients and increased risk of offshore transport and failure to return to coastal habitats. I used plankton surveys, remote sensing, and a simple model to investigate the role of coastal upwelling fronts and behavior in pelagic ecology and recruitment success, focussing on rockfish (Sebastes spp.) off central California. Distributions of early stage larvae suggest that coastal upwelling fronts reduce offshore transport of rockfish larvae, in contrast to distributions of taxa with life histories that minimize larval exposure to strong upwelling. Coincident distributions of larval fish, prey (i.e., small copepods and invertebrate eggs) and phytoplankton patches indicate that coastal upwelling fronts provide enhanced foraging conditions for larvae. Thus, coastal upwelling fronts may allow coastal taxa to successfully exploit high productivity during the upwelling season while reducing the risk of offshore transport. I developed a novel method for utilizing a single HF radar to resolve currents and detect fronts that matched sea surface temperature fronts generated by coastal upwelling. Fronts and currents detected with NF radar affect distributions and transport of planktonic larval fish and intertidal barnacle larvae, demonstrating that remote sensing with HF radar can support field and modelling research on ecological dynamics in coastal marine systems. I used an empirically-based model that incorporated the advection-foraging trade-off and long-distance swimming as an active settlement behavior to investigate optimal settlement strategies as a function of pelagic transport and growth. For parameters loosely describing pelagic stages of rockfish, the model predicts optimal settling strategies (ages and sizes) for pelagic juveniles that roughly match observed values for settling rockfish and suggests optimal spawning locations for adults. The model suggests that offshore transport is more important than growth in determining recruitment success. Thus, coastal upwelling fronts may favor recruitment more by reducing offshore transport than by providing rich food resources. Results of this model represent an initial step towards determining the role of active settlement behaviors in population dynamics and life history evolution.

Optimizing habitat protection using demographic models of population viability.

Treesearch

Robert G. Haight; Brian Cypher; Patrick A. Kelly; Scott Phillips; Hugh P. Possingham; Katherine Ralls; Anthony M. Starfield; P.J. White; Daniel Williams

2002-01-01

Expanding habitat protection is a common tactic for species conservation. When unprotected habitat is privately owned, decisions must be made about which areas to protect by land purchase or conservation easement. To address this problem, we developed an optimization framework for choosing the habitat protection strategy that minimizes the risk of population extinction...

Optimal control problems of epidemic systems with parameter uncertainties: application to a malaria two-age-classes transmission model with asymptomatic carriers.

PubMed

Mwanga, Gasper G; Haario, Heikki; Capasso, Vicenzo

2015-03-01

The main scope of this paper is to study the optimal control practices of malaria, by discussing the implementation of a catalog of optimal control strategies in presence of parameter uncertainties, which is typical of infectious diseases data. In this study we focus on a deterministic mathematical model for the transmission of malaria, including in particular asymptomatic carriers and two age classes in the human population. A partial qualitative analysis of the relevant ODE system has been carried out, leading to a realistic threshold parameter. For the deterministic model under consideration, four possible control strategies have been analyzed: the use of Long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic and asymptomatic individuals. The numerical results show that using optimal control the disease can be brought to a stable disease free equilibrium when all four controls are used. The Incremental Cost-Effectiveness Ratio (ICER) for all possible combinations of the disease-control measures is determined. The numerical simulations of the optimal control in the presence of parameter uncertainty demonstrate the robustness of the optimal control: 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 designing of cost-effective strategies for disease controls with multiple interventions, even under considerable uncertainty of model parameters. Copyright © 2014 Elsevier Inc. All rights reserved.

Beverton-Holt discrete pest management models with pulsed chemical control and evolution of pesticide resistance

NASA Astrophysics Data System (ADS)

Liang, Juhua; Tang, Sanyi; Cheke, Robert A.

2016-07-01

Pest resistance to pesticides is usually managed by switching between different types of pesticides. The optimal switching time, which depends on the dynamics of the pest population and on the evolution of the pesticide resistance, is critical. Here we address how the dynamic complexity of the pest population, the development of resistance and the spraying frequency of pulsed chemical control affect optimal switching strategies given different control aims. To do this, we developed novel discrete pest population growth models with both impulsive chemical control and the evolution of pesticide resistance. Strong and weak threshold conditions which guarantee the extinction of the pest population, based on the threshold values of the analytical formula for the optimal switching time, were derived. Further, we addressed switching strategies in the light of chosen economic injury levels. Moreover, the effects of the complex dynamical behaviour of the pest population on the pesticide switching times were also studied. The pesticide application period, the evolution of pesticide resistance and the dynamic complexity of the pest population may result in complex outbreak patterns, with consequent effects on the pesticide switching strategies.

A method for the dynamic management of genetic variability in dairy cattle

PubMed Central

Colleau, Jean-Jacques; Moureaux, Sophie; Briend, Michèle; Bechu, Jérôme

2004-01-01

According to the general approach developed in this paper, dynamic management of genetic variability in selected populations of dairy cattle is carried out for three simultaneous purposes: procreation of young bulls to be further progeny-tested, use of service bulls already selected and approval of recently progeny-tested bulls for use. At each step, the objective is to minimize the average pairwise relationship coefficient in the future population born from programmed matings and the existing population. As a common constraint, the average estimated breeding value of the new population, for a selection goal including many important traits, is set to a desired value. For the procreation of young bulls, breeding costs are additionally constrained. Optimization is fully analytical and directly considers matings. Corresponding algorithms are presented in detail. The efficiency of these procedures was tested on the current Norman population. Comparisons between optimized and real matings, clearly showed that optimization would have saved substantial genetic variability without reducing short-term genetic gains. PMID:15231230

Optimization model of vaccination strategy for dengue transmission

NASA Astrophysics Data System (ADS)

Widayani, H.; Kallista, M.; Nuraini, N.; Sari, M. Y.

2014-02-01

Dengue fever is emerging tropical and subtropical disease caused by dengue virus infection. The vaccination should be done as a prevention of epidemic in population. The host-vector model are modified with consider a vaccination factor to prevent the occurrence of epidemic dengue in a population. An optimal vaccination strategy using non-linear objective function was proposed. The genetic algorithm programming techniques are combined with fourth-order Runge-Kutta method to construct the optimal vaccination. In this paper, the appropriate vaccination strategy by using the optimal minimum cost function which can reduce the number of epidemic was analyzed. The numerical simulation for some specific cases of vaccination strategy is shown.

Optimal fall indicators for slip induced falls on a cross-slope.

PubMed

Domone, Sarah; Lawrence, Daniel; Heller, Ben; Hendra, Tim; Mawson, Sue; Wheat, Jonathan

2016-08-01

Slip-induced falls are among the most common cause of major occupational injuries in the UK as well as being a major public health concern in the elderly population. This study aimed to determine the optimal fall indicators for fall detection models which could be used to reduce the detrimental consequences of falls. A total of 264 kinematic variables covering three-dimensional full body model translation and rotational measures were analysed during normal walking, successful recovery from slips and falls on a cross-slope. Large effect sizes were found for three kinematic variables which were able to distinguish falls from normal walking and successful recovery. Further work should consider other types of daily living activities as results show that the optimal kinematic fall indicators can vary considerably between movement types. Practitioner Summary: Fall detection models are used to minimise the adverse consequences of slip-induced falls, a major public health concern. Optimal fall indicators were derived from a comprehensive set of kinematic variables for slips on a cross-slope. Results suggest robust detection of falls is possible on a cross-slope but may be more difficult than level walking.

Calculating complete and exact Pareto front for multiobjective optimization: a new deterministic approach for discrete problems.

PubMed

Hu, Xiao-Bing; Wang, Ming; Di Paolo, Ezequiel

2013-06-01

Searching the Pareto front for multiobjective optimization problems usually involves the use of a population-based search algorithm or of a deterministic method with a set of different single aggregate objective functions. The results are, in fact, only approximations of the real Pareto front. In this paper, we propose a new deterministic approach capable of fully determining the real Pareto front for those discrete problems for which it is possible to construct optimization algorithms to find the k best solutions to each of the single-objective problems. To this end, two theoretical conditions are given to guarantee the finding of the actual Pareto front rather than its approximation. Then, a general methodology for designing a deterministic search procedure is proposed. A case study is conducted, where by following the general methodology, a ripple-spreading algorithm is designed to calculate the complete exact Pareto front for multiobjective route optimization. When compared with traditional Pareto front search methods, the obvious advantage of the proposed approach is its unique capability of finding the complete Pareto front. This is illustrated by the simulation results in terms of both solution quality and computational efficiency.

A network-based approach for resistance transmission in bacterial populations.

PubMed

Gehring, Ronette; Schumm, Phillip; Youssef, Mina; Scoglio, Caterina

2010-01-07

Horizontal transfer of mobile genetic elements (conjugation) is an important mechanism whereby resistance is spread through bacterial populations. The aim of our work is to develop a mathematical model that quantitatively describes this process, and to use this model to optimize antimicrobial dosage regimens to minimize resistance development. The bacterial population is conceptualized as a compartmental mathematical model to describe changes in susceptible, resistant, and transconjugant bacteria over time. This model is combined with a compartmental pharmacokinetic model to explore the effect of different plasma drug concentration profiles. An agent-based simulation tool is used to account for resistance transfer occurring when two bacteria are adjacent or in close proximity. In addition, a non-linear programming optimal control problem is introduced to minimize bacterial populations as well as the drug dose. Simulation and optimization results suggest that the rapid death of susceptible individuals in the population is pivotal in minimizing the number of transconjugants in a population. This supports the use of potent antimicrobials that rapidly kill susceptible individuals and development of dosage regimens that maintain effective antimicrobial drug concentrations for as long as needed to kill off the susceptible population. Suggestions are made for experiments to test the hypotheses generated by these simulations.

Colour compatibility between teeth and dental shade guides in Quinquagenarians and Septuagenarians.

PubMed

Cocking, C; Cevirgen, E; Helling, S; Oswald, M; Corcodel, N; Rammelsberg, P; Reinelt, G; Hassel, A J

2009-11-01

The aim of this investigation was to determine colour compatibility between dental shade guides, namely, VITA Classical (VC) and VITA 3D-Master (3D), and human teeth in quinquagenarians and septuagenarians. Tooth colour, described in terms of L*a*b* values of the middle third of facial tooth surface of 1391 teeth, was measured using VITA Easyshade in 195 subjects (48% female). These were compared with the colours (L*a*b* values) of the shade tabs of VC and 3D. The mean coverage error and the percentage of tooth colours being within a given colour difference (DeltaE(ab)) from the tabs of VC and 3D were calculated. For comparison, hypothetical, optimized, population-specific shade guides were additionally calculated based on discrete optimization techniques for optimizing coverage. Mean coverage error was DeltaE(ab) = 3.51 for VC and DeltaE(ab) = 2.96 for 3D. Coverage of tooth colours by the tabs of VC and 3D within DeltaE(ab) = 2 was 23% and 24%, respectively, (DeltaE(ab)

Temporal Data Set Reduction Based on D-Optimality for Quantitative FLIM-FRET Imaging.

PubMed

Omer, Travis; Intes, Xavier; Hahn, Juergen

2015-01-01

Fluorescence lifetime imaging (FLIM) when paired with Förster resonance energy transfer (FLIM-FRET) enables the monitoring of nanoscale interactions in living biological samples. FLIM-FRET model-based estimation methods allow the quantitative retrieval of parameters such as the quenched (interacting) and unquenched (non-interacting) fractional populations of the donor fluorophore and/or the distance of the interactions. The quantitative accuracy of such model-based approaches is dependent on multiple factors such as signal-to-noise ratio and number of temporal points acquired when sampling the fluorescence decays. For high-throughput or in vivo applications of FLIM-FRET, it is desirable to acquire a limited number of temporal points for fast acquisition times. Yet, it is critical to acquire temporal data sets with sufficient information content to allow for accurate FLIM-FRET parameter estimation. Herein, an optimal experimental design approach based upon sensitivity analysis is presented in order to identify the time points that provide the best quantitative estimates of the parameters for a determined number of temporal sampling points. More specifically, the D-optimality criterion is employed to identify, within a sparse temporal data set, the set of time points leading to optimal estimations of the quenched fractional population of the donor fluorophore. Overall, a reduced set of 10 time points (compared to a typical complete set of 90 time points) was identified to have minimal impact on parameter estimation accuracy (≈5%), with in silico and in vivo experiment validations. This reduction of the number of needed time points by almost an order of magnitude allows the use of FLIM-FRET for certain high-throughput applications which would be infeasible if the entire number of time sampling points were used.

A Heat Vulnerability Index and Adaptation Solutions for Pittsburgh, Pennsylvania.

PubMed

Bradford, Kathryn; Abrahams, Leslie; Hegglin, Miriam; Klima, Kelly

2015-10-06

With increasing evidence of global warming, many cities have focused attention on response plans to address their populations' vulnerabilities. Despite expected increased frequency and intensity of heat waves, the health impacts of such events in urban areas can be minimized with careful policy and economic investments. We focus on Pittsburgh, Pennsylvania and ask two questions. First, what are the top factors contributing to heat vulnerability and how do these characteristics manifest geospatially throughout Pittsburgh? Second, assuming the City wishes to deploy additional cooling centers, what placement will optimally address the vulnerability of the at risk populations? We use national census data, ArcGIS geospatial modeling, and statistical analysis to determine a range of heat vulnerability indices and optimal cooling center placement. We find that while different studies use different data and statistical calculations, all methods tested locate additional cooling centers at the confluence of the three rivers (Downtown), the northeast side of Pittsburgh (Shadyside/Highland Park), and the southeast side of Pittsburgh (Squirrel Hill). This suggests that for Pittsburgh, a researcher could apply the same factor analysis procedure to compare data sets for different locations and times; factor analyses for heat vulnerability are more robust than previously thought.

Phenotypic switching of populations of cells in a stochastic environment

NASA Astrophysics Data System (ADS)

Hufton, Peter G.; Lin, Yen Ting; Galla, Tobias

2018-02-01

In biology phenotypic switching is a common bet-hedging strategy in the face of uncertain environmental conditions. Existing mathematical models often focus on periodically changing environments to determine the optimal phenotypic response. We focus on the case in which the environment switches randomly between discrete states. Starting from an individual-based model we derive stochastic differential equations to describe the dynamics, and obtain analytical expressions for the mean instantaneous growth rates based on the theory of piecewise-deterministic Markov processes. We show that optimal phenotypic responses are non-trivial for slow and intermediate environmental processes, and systematically compare the cases of periodic and random environments. The best response to random switching is more likely to be heterogeneity than in the case of deterministic periodic environments, net growth rates tend to be higher under stochastic environmental dynamics. The combined system of environment and population of cells can be interpreted as host-pathogen interaction, in which the host tries to choose environmental switching so as to minimise growth of the pathogen, and in which the pathogen employs a phenotypic switching optimised to increase its growth rate. We discuss the existence of Nash-like mutual best-response scenarios for such host-pathogen games.

Whole dietary patterns to optimize cognitive function for military mission-readiness: a systematic review and recommendations for the field.

PubMed

Teo, Lynn; Crawford, Cindy; Yehuda, Rachel; Jaghab, Danny; Bingham, John J; Gallon, Matthew D; O'Connell, Meghan L; Chittum, Holly K; Arzola, Sonya M; Berry, Kevin

2017-06-01

Optimizing cognitive performance, particularly during times of high stress, is a prerequisite to mission-readiness among military personnel. It has been of interest to determine whether such performance could be enhanced through diet. This systematic review assesses the quality of the evidence for whole dietary patterns across various outcomes related to cognitive function in healthy adult populations to develop research recommendations for the military. PubMed, CINAHL, Embase, PsycInfo, and the Cochrane Library were searched. Peer-reviewed randomized controlled trials published in the English language were eligible. Fifteen included trials were assessed for methodological quality, and descriptive data were extracted. Of the 6 acceptable-quality studies, 1 demonstrated statistically nonsignificant results, whereas the other 5 showed conflicting results across the cognitive outcomes assessed. Due to the heterogeneity across the included studies, no recommendations could be reached concerning whether certain whole dietary patterns have an effect on cognitive outcomes in healthy populations. Specific recommendations for future research are offered. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pediatric tuberculous meningitis: Model-based approach to determining optimal doses of the anti-tuberculosis drugs rifampin and levofloxacin for children.

PubMed

Savic, R M; Ruslami, R; Hibma, J E; Hesseling, A; Ramachandran, G; Ganiem, A R; Swaminathan, S; McIlleron, H; Gupta, A; Thakur, K; van Crevel, R; Aarnoutse, R; Dooley, K E

2015-12-01

Pediatric tuberculous meningitis (TBM) is a highly morbid, often fatal disease. Standard treatment includes isoniazid, rifampin, pyrazinamide, and ethambutol. Current rifampin dosing achieves low cerebrospinal fluid (CSF) concentrations, and CSF penetration of ethambutol is poor. In adult trials, higher-dose rifampin and/or a fluoroquinolone reduced mortality and disability. To estimate optimal dosing of rifampin and levofloxacin for children, we compiled plasma and CSF pharmacokinetic (PK) and outcomes data from adult TBM trials plus plasma PK data from children. A population PK/pharmacodynamic (PD) model using adult data defined rifampin target exposures (plasma area under the curve (AUC)0-24 = 92 mg*h/L). Levofloxacin targets and rifampin pediatric drug disposition information were literature-derived. To attain target rifampin exposures, children require daily doses of at least 30 mg/kg orally or 15 mg/kg intravenously (i.v.). From our pediatric population PK model, oral levofloxacin doses needed to attain exposure targets were 19-33 mg/kg. Our results provide data-driven guidance to maximize pediatric TBM treatment while we await definitive trial results. © 2015 American Society for Clinical Pharmacology and Therapeutics.

A Heat Vulnerability Index and Adaptation Solutions for Pittsburgh, Pennsylvania

NASA Astrophysics Data System (ADS)

Klima, K.; Abrahams, L.; Bradford, K.; Hegglin, M.

2015-12-01

With increasing evidence of global warming, many cities have focused attention on response plans to address their populations' vulnerabilities. Despite expected increased frequency and intensity of heat waves, the health impacts of such events in urban areas can be minimized with careful policy and economic investments. We focus on Pittsburgh, Pennsylvania and ask two questions. First, what are the top factors contributing to heat vulnerability and how do these characteristics manifest geospatially throughout Pittsburgh? Second, assuming the City wishes to deploy additional cooling centers, what placement will optimally address the vulnerability of the at risk populations? We use national census data, ArcGIS geospatial modeling, and statistical analysis to determine a range of heat vulnerability indices and optimal cooling center placement. We find that while different studies use different data and statistical calculations, all methods tested locate additional cooling centers at the confluence of the three rivers (Downtown), the northeast side of Pittsburgh (Shadyside/ Highland Park), and the southeast side of Pittsburgh (Squirrel Hill). This suggests that for Pittsburgh, a researcher could apply the same factor analysis procedure to compare datasets for different locations and times; factor analyses for heat vulnerability are more robust than previously thought.

Evolving effective behaviours to interact with tag-based populations

NASA Astrophysics Data System (ADS)

Yucel, Osman; Crawford, Chad; Sen, Sandip

2015-07-01

Tags and other characteristics, externally perceptible features that are consistent among groups of animals or humans, can be used by others to determine appropriate response strategies in societies. This usage of tags can be extended to artificial environments, where agents can significantly reduce cognitive effort spent on appropriate strategy choice and behaviour selection by reusing strategies for interacting with new partners based on their tags. Strategy selection mechanisms developed based on this idea have successfully evolved stable cooperation in games such as the Prisoner's Dilemma game but relies upon payoff sharing and matching methods that limit the applicability of the tag framework. Our goal is to develop a general classification and behaviour selection approach based on the tag framework. We propose and evaluate alternative tag matching and adaptation schemes for a new, incoming individual to select appropriate behaviour against any population member of an existing, stable society. Our proposed approach allows agents to evolve both the optimal tag for the environment as well as appropriate strategies for existing agent groups. We show that these mechanisms will allow for robust selection of optimal strategies by agents entering a stable society and analyse the various environments where this approach is effective.

Developing a conservation strategy to maximize persistence of an endangered freshwater mussel species while considering management effectiveness and cost

USGS Publications Warehouse

Smith, David R.; McRae, Sarah E.; Augspurger, Tom; Ratcliffe, Judith A.; Nichols, Robert B.; Eads, Chris B.; Savidge, Tim; Bogan, Arthur E.

2015-01-01

We used a structured decision-making process to develop conservation strategies to increase persistence of Dwarf Wedgemussel (Alasmidonta heterodon) in North Carolina, USA, while accounting for uncertainty in management effectiveness and considering costs. Alternative conservation strategies were portfolios of management actions that differed by location of management actions on the landscape. Objectives of the conservation strategy were to maximize species persistence, maintain genetic diversity, maximize public support, and minimize management costs. We compared 4 conservation strategies: 1) the ‘status quo’ strategy represented current management, 2) the ‘protect the best’ strategy focused on protecting the best populations in the Tar River basin, 3) the ‘expand the distribution’ strategy focused on management of extant populations and establishment of new populations in the Neuse River basin, and 4) the ‘hybrid’ strategy combined elements of each strategy to balance conservation in the Tar and Neuse River basins. A population model informed requirements for population management, and experts projected performance of alternative strategies over a 20-y period. The optimal strategy depended on the relative value placed on competing objectives, which can vary among stakeholders. The protect the best and hybrid strategies were optimal across a wide range of relative values with 2 exceptions: 1) if minimizing management cost was of overriding concern, then status quo was optimal, or 2) if maximizing population persistence in the Neuse River basin was emphasized, then expand the distribution strategy was optimal. The optimal strategy was robust to uncertainty in management effectiveness. Overall, the structured decision process can help identify the most promising strategies for endangered species conservation that maximize conservation benefit given the constraint of limited funding.

Wound care in the neonatal intensive care unit.

PubMed

Fox, Miriam D

2011-01-01

The skin is a vital organ with key protective functions. Infants in the NICU are at risk for skin injury because of developmental immaturity and intensive care treatments. When skin injury occurs, the neonatal nurse is challenged to provide wound care to optimize functional and cosmetic healing. Optimal wound care requires basic knowledge of the mechanisms of injury, physiology of wound healing, host factors affecting wound healing, and wound assessment. This knowledge provides the basis for determining appropriate wound treatment, including dressing selection. Attention to pain issues associated with wound care is difficult because of the infant's developmental stage, but is essential because of the potentially negative life-long impact of pain. The premature infant's propensity for skin stripping limits the selection of appropriate dressing, as does the paucity of research examining wound care products in this population.

Bayesian Spatial Design of Optimal Deep Tubewell Locations in Matlab, Bangladesh.

PubMed

Warren, Joshua L; Perez-Heydrich, Carolina; Yunus, Mohammad

2013-09-01

We introduce a method for statistically identifying the optimal locations of deep tubewells (dtws) to be installed in Matlab, Bangladesh. Dtw installations serve to mitigate exposure to naturally occurring arsenic found at groundwater depths less than 200 meters, a serious environmental health threat for the population of Bangladesh. We introduce an objective function, which incorporates both arsenic level and nearest town population size, to identify optimal locations for dtw placement. Assuming complete knowledge of the arsenic surface, we then demonstrate how minimizing the objective function over a domain favors dtws placed in areas with high arsenic values and close to largely populated regions. Given only a partial realization of the arsenic surface over a domain, we use a Bayesian spatial statistical model to predict the full arsenic surface and estimate the optimal dtw locations. The uncertainty associated with these estimated locations is correctly characterized as well. The new method is applied to a dataset from a village in Matlab and the estimated optimal locations are analyzed along with their respective 95% credible regions.

Design and optimization of production parameters for boric acid crystals with the crystallization process in an MSMPR crystallizer using FBRM® and PVM® technologies

NASA Astrophysics Data System (ADS)

Kutluay, Sinan; Şahin, Ömer; Ceyhan, A. Abdullah; İzgi, M. Sait

2017-06-01

In crystallization studies, newly developed technologies, such as Focused Beam Reflectance Measurement (FBRM) and Particle Vision and Measurement (PVM) are applied for determining on-line monitoring of a representation of the Chord Length Distribution (CLD) and observe the photographs of crystals respectively; moreover recently they are widely used. Properly installed, the FBRM ensures on-line determination of the CLD, which is statistically associated to the Crystal Size Distribution (CSD). In industrial crystallization, CSD and mean crystal size as well as external habit and internal structure are important characteristics for further use of the crystals. In this paper, the effect of residence time, stirring speed, feeding rate, supersaturation level and the polyelectrolytes such as anionic polyacrylamide (APAM) and non-ionic polyacrylamide (NPAM) on the CLD as well as the shape of boric acid crystals were investigated by using the FBRM G600 and the PVM V819 probes respectively in an MSMPR (Mixed Suspension Mixed Product Removal) crystallizer. The CSD and kinetic data were determined experimentally using continuous MSMPR crystallizer running at steady state. The population density of nuclei, the nucleation rate and the growth rate were determined from the experimental population balance distribution when the steady state was reached.

Omega-3 fatty acids and changes in LBM: alone or in synergy for better muscle health?

PubMed

McDonald, Cameron; Bauer, Judy; Capra, Sandra

2013-06-01

Myopenia or muscle wasting due to ageing, chronic disease, and various medical interventions has been associated with increased mortality, morbidity, and poorer physical function. Attempts through nutrient and exercise interventions have been made to prevent this deterioration. In addition, while a measure of lean body mass (LBM) is associated with health outcomes, LBM function may be a better prognostic tool. Long-chain omega-3 fatty acids (LCn-3s) are nutrients that may mitigate LBM losses in noncancer populations. The purpose of this review is to determine whether LCn-3s have a role in LBM sparing in noncancer populations, to establish a minimum dose and duration of LCn-3s that will result in LBM change, and to summarise the potential effects of LCn-3s on LBM function when combined with an anabolic stimulus. Overall, in noncancer populations, LCn-3s have limited utility in sparing LBM during energy balance, energy restriction, or in conjunction with aerobic exercise. Further investigations are required to determine the appropriate dose and duration of LCn-3s for optimal LBM function. Finally, compelling evidence exists for LCn-3s in conjunction with an anabolic stimulus to improve LBM function and quality. Functionality of LBM tissue is an important outcome for population health, and LCn-3s show some promise, albeit pending further study.

Optimal intervention strategies for cholera outbreak by education and chlorination

NASA Astrophysics Data System (ADS)

Bakhtiar, Toni

2016-01-01

This paper discusses the control of infectious diseases in the framework of optimal control approach. A case study on cholera control was studied by considering two control strategies, namely education and chlorination. We distinct the former control into one regarding person-to-person behaviour and another one concerning person-to-environment conduct. Model are divided into two interacted populations: human population which follows an SIR model and pathogen population. Pontryagin maximum principle was applied in deriving a set of differential equations which consists of dynamical and adjoin systems as optimality conditions. Then, the fourth order Runge-Kutta method was exploited to numerically solve the equation system. An illustrative example was provided to assess the effectiveness of the control strategies toward a set of control scenarios.

Particle swarm optimization of ascent trajectories of multistage launch vehicles

NASA Astrophysics Data System (ADS)

Pontani, Mauro

2014-02-01

Multistage launch vehicles are commonly employed to place spacecraft and satellites in their operational orbits. If the rocket characteristics are specified, the optimization of its ascending trajectory consists of determining the optimal control law that leads to maximizing the final mass at orbit injection. The numerical solution of a similar problem is not trivial and has been pursued with different methods, for decades. This paper is concerned with an original approach based on the joint use of swarming theory and the necessary conditions for optimality. The particle swarm optimization technique represents a heuristic population-based optimization method inspired by the natural motion of bird flocks. Each individual (or particle) that composes the swarm corresponds to a solution of the problem and is associated with a position and a velocity vector. The formula for velocity updating is the core of the method and is composed of three terms with stochastic weights. As a result, the population migrates toward different regions of the search space taking advantage of the mechanism of information sharing that affects the overall swarm dynamics. At the end of the process the best particle is selected and corresponds to the optimal solution to the problem of interest. In this work the three-dimensional trajectory of the multistage rocket is assumed to be composed of four arcs: (i) first stage propulsion, (ii) second stage propulsion, (iii) coast arc (after release of the second stage), and (iv) third stage propulsion. The Euler-Lagrange equations and the Pontryagin minimum principle, in conjunction with the Weierstrass-Erdmann corner conditions, are employed to express the thrust angles as functions of the adjoint variables conjugate to the dynamics equations. The use of these analytical conditions coming from the calculus of variations leads to obtaining the overall rocket dynamics as a function of seven parameters only, namely the unknown values of the initial state and costate components, the coast duration, and the upper stage thrust duration. In addition, a simple approach is introduced and successfully applied with the purpose of satisfying exactly the path constraint related to the maximum dynamical pressure in the atmospheric phase. The basic version of the swarming technique, which is used in this research, is extremely simple and easy to program. Nevertheless, the algorithm proves to be capable of yielding the optimal rocket trajectory with a very satisfactory numerical accuracy.

Optimization of digital droplet polymerase chain reaction for quantification of genetically modified organisms

PubMed Central

Gerdes, Lars; Iwobi, Azuka; Busch, Ulrich; Pecoraro, Sven

2016-01-01

Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called ‘rain’. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based ‘experience matrix’ that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event. PMID:27077048

Optimization of digital droplet polymerase chain reaction for quantification of genetically modified organisms.

PubMed

Gerdes, Lars; Iwobi, Azuka; Busch, Ulrich; Pecoraro, Sven

2016-03-01

Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

Exact solutions of the population balance equation including particle transport, using group analysis

NASA Astrophysics Data System (ADS)

Lin, Fubiao; Meleshko, Sergey V.; Flood, Adrian E.

2018-06-01

The population balance equation (PBE) has received an unprecedented amount of attention in recent years from both academics and industrial practitioners because of its long history, widespread use in engineering, and applicability to a wide variety of particulate and discrete-phase processes. However it is typically impossible to obtain analytical solutions, although in almost every case a numerical solution of the PBEs can be obtained. In this article, the symmetries of PBEs with homogeneous coagulation kernels involving aggregation, breakage and growth processes and particle transport in one dimension are found by direct solving the determining equations. Using the optimal system of one and two-dimensional subalgebras, all invariant solutions and reduced equations are obtained. In particular, an explicit analytical physical solution is also presented.

Motor unit recruitment by size does not provide functional advantages for motor performance

PubMed Central

Dideriksen, Jakob L; Farina, Dario

2013-01-01

It is commonly assumed that the orderly recruitment of motor units by size provides a functional advantage for the performance of movements compared with a random recruitment order. On the other hand, the excitability of a motor neuron depends on its size and this is intrinsically linked to its innervation number. A range of innervation numbers among motor neurons corresponds to a range of sizes and thus to a range of excitabilities ordered by size. Therefore, if the excitation drive is similar among motor neurons, the recruitment by size is inevitably due to the intrinsic properties of motor neurons and may not have arisen to meet functional demands. In this view, we tested the assumption that orderly recruitment is necessarily beneficial by determining if this type of recruitment produces optimal motor output. Using evolutionary algorithms and without any a priori assumptions, the parameters of neuromuscular models were optimized with respect to several criteria for motor performance. Interestingly, the optimized model parameters matched well known neuromuscular properties, but none of the optimization criteria determined a consistent recruitment order by size unless this was imposed by an association between motor neuron size and excitability. Further, when the association between size and excitability was imposed, the resultant model of recruitment did not improve the motor performance with respect to the absence of orderly recruitment. A consistent observation was that optimal solutions for a variety of criteria of motor performance always required a broad range of innervation numbers in the population of motor neurons, skewed towards the small values. These results indicate that orderly recruitment of motor units in itself does not provide substantial functional advantages for motor control. Rather, the reason for its near-universal presence in human movements is that motor functions are optimized by a broad range of innervation numbers. PMID:24144879

Motor unit recruitment by size does not provide functional advantages for motor performance.

PubMed

Dideriksen, Jakob L; Farina, Dario

2013-12-15

It is commonly assumed that the orderly recruitment of motor units by size provides a functional advantage for the performance of movements compared with a random recruitment order. On the other hand, the excitability of a motor neuron depends on its size and this is intrinsically linked to its innervation number. A range of innervation numbers among motor neurons corresponds to a range of sizes and thus to a range of excitabilities ordered by size. Therefore, if the excitation drive is similar among motor neurons, the recruitment by size is inevitably due to the intrinsic properties of motor neurons and may not have arisen to meet functional demands. In this view, we tested the assumption that orderly recruitment is necessarily beneficial by determining if this type of recruitment produces optimal motor output. Using evolutionary algorithms and without any a priori assumptions, the parameters of neuromuscular models were optimized with respect to several criteria for motor performance. Interestingly, the optimized model parameters matched well known neuromuscular properties, but none of the optimization criteria determined a consistent recruitment order by size unless this was imposed by an association between motor neuron size and excitability. Further, when the association between size and excitability was imposed, the resultant model of recruitment did not improve the motor performance with respect to the absence of orderly recruitment. A consistent observation was that optimal solutions for a variety of criteria of motor performance always required a broad range of innervation numbers in the population of motor neurons, skewed towards the small values. These results indicate that orderly recruitment of motor units in itself does not provide substantial functional advantages for motor control. Rather, the reason for its near-universal presence in human movements is that motor functions are optimized by a broad range of innervation numbers.

Economic modeling of sealing primary molars using a "value of information" approach.

PubMed

Ney, J P; van der Goes, D N; Chi, D L

2014-09-01

The objective was to evaluate 2 primary molar sealant strategies for publicly insured children using an "expected value of perfect information" (EVPI) approach. We converted a 10,000-observation tooth-level cost-effectiveness simulation model comparing 2 primary molar sealant strategies - always seal (AS) and standard care (SC) - with a 1,250-observation child-level model. Costs per child per restoration or extraction averted were estimated. Opportunity losses under the AS strategy were determined for children for whom SC was the optimal choice. We determined the EVPI by multiplying mean opportunity losses by the projected incident population of publicly insured 3-year-olds in the US over 10 years with costs discounted at 2%. All analyses were conducted under assumptions of high and low intrachild correlations between at-risk teeth. The AS strategy cost $43.68 over SC (95% CI: -$5.50, $92.86) per child per restoration or extraction averted under the high intrachild correlation assumption and $15.54 (95% CI $7.86, $23.20) under the low intrachild correlation. Under high intrachild correlation, mean opportunity losses were $80.28 (95% CI: $76.39, $84.17) per child, and AS was the optimal strategy in 31% of children. Under low correlation, mean opportunity losses were $14.61 (95% CI: $12.20, $17.68) and AS was the optimal strategy in 87% of children. The EVPI was calculated at $530,813,740 and $96,578,389 (for high and low intrachild correlation, respectively), for a projected total incident population of 8,059,712 children. On average, always sealing primary molars is more effective than standard care, but widespread implementation of this preventive approach among publicly insured children would result in large opportunity losses. Additional research is needed to identify the subgroups of publicly insured children who would benefit the most from this effective and potentially cost-saving public health intervention. © International & American Associations for Dental Research.

Determination of the optimal mesh parameters for Iguassu centrifuge flow and separation calculations

NASA Astrophysics Data System (ADS)

Romanihin, S. M.; Tronin, I. V.

2016-09-01

We present the method and the results of the determination for optimal computational mesh parameters for axisymmetric modeling of flow and separation in the Iguasu gas centrifuge. The aim of this work was to determine the mesh parameters which provide relatively low computational cost whithout loss of accuracy. We use direct search optimization algorithm to calculate optimal mesh parameters. Obtained parameters were tested by the calculation of the optimal working regime of the Iguasu GC. Separative power calculated using the optimal mesh parameters differs less than 0.5% from the result obtained on the detailed mesh. Presented method can be used to determine optimal mesh parameters of the Iguasu GC with different rotor speeds.

Genetic Algorithm for Optimization: Preprocessor and Algorithm

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam A.

2006-01-01

Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.

A triple fouling layers perspective on evaluation of membrane fouling under different scenarios of membrane bioreactor operation

PubMed Central

2014-01-01

One of the main factors affecting membrane fouling in MBRs is operational conditions. In this study the influence of aeration rate, filtration mode, and SRT on hollow fiber membrane fouling was investigated using a triple fouling layers perspective. The sludge microbial population distribution was also determined by PCR method. Through various applied operational scenarios the optimal conditions were: aeration rate of 15 LPM; relaxation mode with 40s duration and 8 min. interval; and SRT of 30 days. The similarity between SMP variations in triple fouling layers with its corresponding hydraulic resistance confirmed the effect of SMP on membrane fouling. Among three fouling fractions, the upper (rinsed) layer found to have the most effect on membrane fouling which implies the critical role of aeration, but as for multilateral effects of aeration, the optimal aeration rate should be determined more precisely. Relaxation interval was more effective than its duration for fouling control. SRT variations in addition to influencing the amount of SMP, also affect on the structure of these material. At longer SRTs (20, 30 days) a greater percentage of SMP could penetrate into the membrane pores and for shorter SRTs they accumulate more on membrane surface. Results showed that there is a very good correlation between total hydraulic resistance (Log R) and protein to carbohydrate ratio at the rinsed layer (P1/C1). Considering significant effects of aeration and SRT conditions on this ratio (according to data), it is very determinative to apply the optimal aeration and SRT conditions. PMID:25002969

A novel metaheuristic for continuous optimization problems: Virus optimization algorithm

NASA Astrophysics Data System (ADS)

Liang, Yun-Chia; Rodolfo Cuevas Juarez, Josue

2016-01-01

A novel metaheuristic for continuous optimization problems, named the virus optimization algorithm (VOA), is introduced and investigated. VOA is an iteratively population-based method that imitates the behaviour of viruses attacking a living cell. The number of viruses grows at each replication and is controlled by an immune system (a so-called 'antivirus') to prevent the explosive growth of the virus population. The viruses are divided into two classes (strong and common) to balance the exploitation and exploration effects. The performance of the VOA is validated through a set of eight benchmark functions, which are also subject to rotation and shifting effects to test its robustness. Extensive comparisons were conducted with over 40 well-known metaheuristic algorithms and their variations, such as artificial bee colony, artificial immune system, differential evolution, evolutionary programming, evolutionary strategy, genetic algorithm, harmony search, invasive weed optimization, memetic algorithm, particle swarm optimization and simulated annealing. The results showed that the VOA is a viable solution for continuous optimization.

Optimal fire histories for biodiversity conservation.

PubMed

Kelly, Luke T; Bennett, Andrew F; Clarke, Michael F; McCarthy, Michael A

2015-04-01

Fire is used as a management tool for biodiversity conservation worldwide. A common objective is to avoid population extinctions due to inappropriate fire regimes. However, in many ecosystems, it is unclear what mix of fire histories will achieve this goal. We determined the optimal fire history of a given area for biological conservation with a method that links tools from 3 fields of research: species distribution modeling, composite indices of biodiversity, and decision science. We based our case study on extensive field surveys of birds, reptiles, and mammals in fire-prone semi-arid Australia. First, we developed statistical models of species' responses to fire history. Second, we determined the optimal allocation of successional states in a given area, based on the geometric mean of species relative abundance. Finally, we showed how conservation targets based on this index can be incorporated into a decision-making framework for fire management. Pyrodiversity per se did not necessarily promote vertebrate biodiversity. Maximizing pyrodiversity by having an even allocation of successional states did not maximize the geometric mean abundance of bird species. Older vegetation was disproportionately important for the conservation of birds, reptiles, and small mammals. Because our method defines fire management objectives based on the habitat requirements of multiple species in the community, it could be used widely to maximize biodiversity in fire-prone ecosystems. © 2014 Society for Conservation Biology.

Locating helicopter emergency medical service bases to optimise population coverage versus average response time.

PubMed

Garner, Alan A; van den Berg, Pieter L

2017-10-16

New South Wales (NSW), Australia has a network of multirole retrieval physician staffed helicopter emergency medical services (HEMS) with seven bases servicing a jurisdiction with population concentrated along the eastern seaboard. The aim of this study was to estimate optimal HEMS base locations within NSW using advanced mathematical modelling techniques. We used high resolution census population data for NSW from 2011 which divides the state into areas containing 200-800 people. Optimal HEMS base locations were estimated using the maximal covering location problem facility location optimization model and the average response time model, exploring the number of bases needed to cover various fractions of the population for a 45 min response time threshold or minimizing the overall average response time to all persons, both in green field scenarios and conditioning on the current base structure. We also developed a hybrid mathematical model where average response time was optimised based on minimum population coverage thresholds. Seven bases could cover 98% of the population within 45mins when optimised for coverage or reach the entire population of the state within an average of 21mins if optimised for response time. Given the existing bases, adding two bases could either increase the 45 min coverage from 91% to 97% or decrease the average response time from 21mins to 19mins. Adding a single specialist prehospital rapid response HEMS to the area of greatest population concentration decreased the average state wide response time by 4mins. The optimum seven base hybrid model that was able to cover 97.75% of the population within 45mins, and all of the population in an average response time of 18 mins included the rapid response HEMS model. HEMS base locations can be optimised based on either percentage of the population covered, or average response time to the entire population. We have also demonstrated a hybrid technique that optimizes response time for a given number of bases and minimum defined threshold of population coverage. Addition of specialized rapid response HEMS services to a system of multirole retrieval HEMS may reduce overall average response times by improving access in large urban areas.

Strategies for optimizing maternal nutrition to promote infant development.

PubMed

Hambidge, K Michael; Krebs, Nancy F

2018-06-22

The growing appreciation of the multi-faceted importance of optimal maternal nutrition to the health and development of the infant and young child is tempered by incompletely resolved strategies for combatting challenges. To review the importance of maternal nutrition and strategies being employed to optimize outcomes. Selected data from recent literature with special focus on rationale for and currently published results of maternal nutrition supplements, including lipid based nutrition supplements. 1) An impelling rationale for improving the maternal and in utero environment of low resource populations has emerged to achieve improved fetal and post-natal growth and development. 2) Based partly on population increases in adult height over one-two generations, much can be achieved by reducing poverty. 3) Maternal, newborn and infant characteristics associated with low resource environments include evidence of undernutrition, manifested by underweight and impaired linear growth. 4) Apart from broad public health and educational initiatives, to date, most specific efforts to improve fetal growth and development have included maternal nutrition interventions during gestation. 5) The relatively limited but real benefits of both iron/folic acid (IFA) and multiple micronutrient (MMN) maternal supplements during gestation have now been reasonably defined. 6) Recent investigations of a maternal lipid-based primarily micronutrient supplement (LNS) have not demonstrated a consistent benefit beyond MMN alone. 7) However, effects of both MMN and LNS appear to be enhanced by commencing early in gestation. Poor maternal nutritional status is one of a very few specific factors in the human that not only contributes to impaired fetal and early post-natal growth but for which maternal interventions have demonstrated improved in utero development, documented primarily by both improvements in low birth weights and by partial corrections of impaired birth length. A clearer definition of the benefits achievable by interventions specifically focused on correcting maternal nutrition deficits should not be limited to improvements in the quality of maternal nutrition supplements, but on the cumulative quantity and timing of interventions (also recognizing the heterogeneity between populations). Finally, in an ideal world these steps are only a prelude to improvements in the total environment in which optimal nutrition and other health determinants can be achieved.

Adaptive harvest management for the Svalbard population of Pink-Footed Geese: 2014 progress summary

USGS Publications Warehouse

Johnson, Fred A.; Madsen, J.

2015-01-01

During the summer of 2013 we computed an optimal harvest strategy for the 3-year period 2013 – 2015. The strategy suggested that the appropriate annual harvest quota is 15 thousand. The 1-year harvest strategy calculated to determine whether an emergency closure of the hunting season is required this year suggested an allowable harvest of 25.0 thousand; thus, a hunting-season closure is not warranted.  If the harvest quota of 15 thousand were met in the coming hunting season, the next population count would be expected to be 71.0 thousand.  If only the most recent 4-year mean harvest were realized (11.3 thousand), a population size of 74.8 thousand would be expected.  Simulations suggest that it will take approximately seven years at current harvest levels to reduce population size to the goal of 60 thousand.  However, it is possible that the extension of the forthcoming hunting season in Denmark could result in a total harvest approaching 15 thousand; in this case, simulations suggest it would only take about three years to reach the goal.

Optimal birth control of age-dependent competitive species III. Overtaking problem

NASA Astrophysics Data System (ADS)

He, Ze-Rong; Cheng, Ji-Shu; Zhang, Chun-Guo

2008-01-01

A study is made of an overtaking optimal problem for a population system consisting of two competing species, which is controlled by fertilities. The existence of optimal policy is proved and a maximum principle is carefully derived under less restrictive conditions. Weak and strong turnpike properties of optimal trajectories are established.

More rapid climate change promotes evolutionary rescue through selection for increased dispersal distance

PubMed Central

Boeye, Jeroen; Travis, Justin M J; Stoks, Robby; Bonte, Dries

2013-01-01

Species can either adapt to new conditions induced by climate change or shift their range in an attempt to track optimal environmental conditions. During current range shifts, species are simultaneously confronted with a second major anthropogenic disturbance, landscape fragmentation. Using individual-based models with a shifting climate window, we examine the effect of different rates of climate change on the evolution of dispersal distances through changes in the genetically determined dispersal kernel. Our results demonstrate that the rate of climate change is positively correlated to the evolved dispersal distances although too fast climate change causes the population to crash. When faced with realistic rates of climate change, greater dispersal distances evolve than those required for the population to keep track of the climate, thereby maximizing population size. Importantly, the greater dispersal distances that evolve when climate change is more rapid, induce evolutionary rescue by facilitating the population in crossing large gaps in the landscape. This could ensure population persistence in case of range shifting in fragmented landscapes. Furthermore, we highlight problems in using invasion speed as a proxy for potential range shifting abilities under climate change. PMID:23467649

Monitoring the spread of myxoma virus in rabbit Oryctolagus cuniculus populations on the southern tablelands of New South Wales, Australia. I. Natural occurrence of myxomatosis.

PubMed Central

Merchant, J. C.; Kerr, P. J.; Simms, N. G.; Robinson, A. J.

2003-01-01

A survey of rabbit populations in the southern tablelands of New South Wales, Australia, was carried out to establish the pattern of occurrence of myxomatosis in preparation for a deliberate release of myxoma virus. Myxomatosis was first detected in December and cases were found on most sites through to May. The serological profiles of rabbit populations suggested that their susceptibility to myxoma virus was generally low in winter and highest in spring and summer reflecting the presence of increasing numbers of susceptible young rabbits. This was consistent with the pattern of rabbit breeding, as determined from the distribution of births and reproductive activity in females and males, which occurred maximally in spring and early summer. The serology and age structure of rabbit populations on sites suggested that some rabbit populations can escape an annual myxomatosis epizootic. Although fleas were present on rabbits throughout the year and therefore not considered to be a limiting factor in the spread of myxomatosis, their numbers peaked at times coincident with peak rabbit breeding. It was concluded that mid to late spring was an optimal time for a deliberate release. PMID:12613753

Monitoring the spread of myxoma virus in rabbit Oryctolagus cuniculus populations on the southern tablelands of New South Wales, Australia. I. Natural occurrence of myxomatosis.

PubMed

Merchant, J C; Kerr, P J; Simms, N G; Robinson, A J

2003-02-01

A survey of rabbit populations in the southern tablelands of New South Wales, Australia, was carried out to establish the pattern of occurrence of myxomatosis in preparation for a deliberate release of myxoma virus. Myxomatosis was first detected in December and cases were found on most sites through to May. The serological profiles of rabbit populations suggested that their susceptibility to myxoma virus was generally low in winter and highest in spring and summer reflecting the presence of increasing numbers of susceptible young rabbits. This was consistent with the pattern of rabbit breeding, as determined from the distribution of births and reproductive activity in females and males, which occurred maximally in spring and early summer. The serology and age structure of rabbit populations on sites suggested that some rabbit populations can escape an annual myxomatosis epizootic. Although fleas were present on rabbits throughout the year and therefore not considered to be a limiting factor in the spread of myxomatosis, their numbers peaked at times coincident with peak rabbit breeding. It was concluded that mid to late spring was an optimal time for a deliberate release.

Self-extinction through optimizing selection.

PubMed

Parvinen, Kalle; Dieckmann, Ulf

2013-09-21

Evolutionary suicide is a process in which selection drives a viable population to extinction. So far, such selection-driven self-extinction has been demonstrated in models with frequency-dependent selection. This is not surprising, since frequency-dependent selection can disconnect individual-level and population-level interests through environmental feedback. Hence it can lead to situations akin to the tragedy of the commons, with adaptations that serve the selfish interests of individuals ultimately ruining a population. For frequency-dependent selection to play such a role, it must not be optimizing. Together, all published studies of evolutionary suicide have created the impression that evolutionary suicide is not possible with optimizing selection. Here we disprove this misconception by presenting and analyzing an example in which optimizing selection causes self-extinction. We then take this line of argument one step further by showing, in a further example, that selection-driven self-extinction can occur even under frequency-independent selection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Super-linear Precision in Simple Neural Population Codes

NASA Astrophysics Data System (ADS)

Schwab, David; Fiete, Ila

2015-03-01

A widely used tool for quantifying the precision with which a population of noisy sensory neurons encodes the value of an external stimulus is the Fisher Information (FI). Maximizing the FI is also a commonly used objective for constructing optimal neural codes. The primary utility and importance of the FI arises because it gives, through the Cramer-Rao bound, the smallest mean-squared error achievable by any unbiased stimulus estimator. However, it is well-known that when neural firing is sparse, optimizing the FI can result in codes that perform very poorly when considering the resulting mean-squared error, a measure with direct biological relevance. Here we construct optimal population codes by minimizing mean-squared error directly and study the scaling properties of the resulting network, focusing on the optimal tuning curve width. We then extend our results to continuous attractor networks that maintain short-term memory of external stimuli in their dynamics. Here we find similar scaling properties in the structure of the interactions that minimize diffusive information loss.

Use of HOMA-IR to diagnose non-alcoholic fatty liver disease: a population-based and inter-laboratory study.

PubMed

Isokuortti, Elina; Zhou, You; Peltonen, Markku; Bugianesi, Elisabetta; Clement, Karine; Bonnefont-Rousselot, Dominique; Lacorte, Jean-Marc; Gastaldelli, Amalia; Schuppan, Detlef; Schattenberg, Jörn M; Hakkarainen, Antti; Lundbom, Nina; Jousilahti, Pekka; Männistö, Satu; Keinänen-Kiukaanniemi, Sirkka; Saltevo, Juha; Anstee, Quentin M; Yki-Järvinen, Hannele

2017-10-01

Recent European guidelines for non-alcoholic fatty liver disease (NAFLD) call for reference values for HOMA-IR. In this study, we aimed to determine: (1) the upper limit of normal HOMA-IR in two population-based cohorts; (2) the HOMA-IR corresponding to NAFLD; (3) the effect of sex and PNPLA3 genotype at rs738409 on HOMA-IR; and (4) inter-laboratory variations in HOMA-IR. We identified healthy individuals in two population-based cohorts (FINRISK 2007 [n = 5024] and the Programme for Prevention of Type 2 Diabetes in Finland [FIN-D2D; n = 2849]) to define the upper 95th percentile of HOMA-IR. Non-obese individuals with normal fasting glucose levels, no excessive alcohol use, no known diseases and no use of any drugs were considered healthy. The optimal HOMA-IR cut-off for NAFLD (liver fat ≥5.56%, based on the Dallas Heart Study) was determined in 368 non-diabetic individuals (35% with NAFLD), whose liver fat was measured using proton magnetic resonance spectroscopy ( 1 H-MRS). Samples from ten individuals were simultaneously analysed for HOMA-IR in seven European laboratories. The upper 95th percentiles of HOMA-IR were 1.9 and 2.0 in healthy individuals in the FINRISK (n = 1167) and FIN-D2D (n = 459) cohorts. Sex or PNPLA3 genotype did not influence these values. The optimal HOMA-IR cut-off for NAFLD was 1.9 (sensitivity 87%, specificity 79%). A HOMA-IR of 2.0 corresponded to normal liver fat (<5.56% on 1 H-MRS) in linear regression analysis. The 2.0 HOMA-IR measured in Helsinki corresponded to 1.3, 1.6, 1.8, 1.8, 2.0 and 2.1 in six other laboratories. The inter-laboratory CV% of HOMA-IR was 25% due to inter-assay variation in insulin (25%) rather than glucose (5%) measurements. The upper limit of HOMA-IR in population-based cohorts closely corresponds to that of normal liver fat. Standardisation of insulin assays would be the first step towards definition of normal values for HOMA-IR.

Evaluation of Residual Static Corrections by Hybrid Genetic Algorithm Steepest Ascent Autostatics Inversion.Application southern Algerian fields

NASA Astrophysics Data System (ADS)

Eladj, Said; bansir, fateh; ouadfeul, sid Ali

2016-04-01

The application of genetic algorithm starts with an initial population of chromosomes representing a "model space". Chromosome chains are preferentially Reproduced based on Their fitness Compared to the total population. However, a good chromosome has a Greater opportunity to Produce offspring Compared To other chromosomes in the population. The advantage of the combination HGA / SAA is the use of a global search approach on a large population of local maxima to Improve Significantly the performance of the method. To define the parameters of the Hybrid Genetic Algorithm Steepest Ascent Auto Statics (HGA / SAA) job, we Evaluated by testing in the first stage of "Steepest Ascent," the optimal parameters related to the data used. 1- The number of iterations "Number of hill climbing iteration" is equal to 40 iterations. This parameter defines the participation of the algorithm "SA", in this hybrid approach. 2- The minimum eigenvalue for SA '= 0.8. This is linked to the quality of data and S / N ratio. To find an implementation performance of hybrid genetic algorithms in the inversion for estimating of the residual static corrections, tests Were Performed to determine the number of generation of HGA / SAA. Using the values of residual static corrections already calculated by the Approaches "SAA and CSAA" learning has Proved very effective in the building of the cross-correlation table. To determine the optimal number of generation, we Conducted a series of tests ranging from [10 to 200] generations. The application on real seismic data in southern Algeria allowed us to judge the performance and capacity of the inversion with this hybrid method "HGA / SAA". This experience Clarified the influence of the corrections quality estimated from "SAA / CSAA" and the optimum number of generation hybrid genetic algorithm "HGA" required to have a satisfactory performance. Twenty (20) generations Were enough to Improve continuity and resolution of seismic horizons. This Will allow us to achieve a more accurate structural interpretation Key words: Hybrid Genetic Algorithm, number of generations, model space, local maxima, Number of hill climbing iteration, Minimum eigenvalue, cross-correlation table

Making it stick: chasing the optimal stem cells for cardiac regeneration

PubMed Central

Quijada, Pearl; Sussman, Mark A

2014-01-01

Despite the increasing use of stem cells for regenerative-based cardiac therapy, the optimal stem cell population(s) remains in a cloud of uncertainty. In the past decade, the field has witnessed a surge of researchers discovering stem cell populations reported to directly and/or indirectly contribute to cardiac regeneration through processes of cardiomyogenic commitment and/or release of cardioprotective paracrine factors. This review centers upon defining basic biological characteristics of stem cells used for sustaining cardiac integrity during disease and maintenance of communication between the cardiac environment and stem cells. Given the limited successes achieved so far in regenerative therapy, the future requires development of unprecedented concepts involving combinatorial approaches to create and deliver the optimal stem cell(s) that will enhance myocardial healing. PMID:25340282

The value of the wechsler intelligence scale for children-fourth edition digit span as an embedded measure of effort: an investigation into children with dual diagnoses.

PubMed

Loughan, Ashlee R; Perna, Robert; Hertza, Jeremy

2012-11-01

The Test of Memory Malingering (TOMM) is a measure of test-taking effort which has traditionally been utilized with adults, but which more recently has demonstrated utility with children. The purpose of this study was to investigate whether the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) Digit Span, commonly used in neuropsychological evaluations, can also be functional as an embedded measure by detecting effort in children with dual diagnoses; a population yet to be investigated. Participants (n = 51) who completed neuropsychological evaluations including the TOMM, WISC-IV, Wisconsin Card Sorting Test, Children's Memory Scale, and Delis-Kaplan Executive Function System were divided into two groups: Optimal Effort and Suboptimal Effort, based on their TOMM Trial 2 scores. Digit Span findings suggest a useful scaled score of ≤4 resulted in optimal cutoff scores, yielding specificity of 91% and sensitivity of 43%. This study supports previous research that the WISC-IV Digit Span has good utility in determining optimal effort, even in children with dual diagnosis or comorbidities.

Diel Variation in Population Size and Ice Nucleation Activity of Pseudomonas syringae on Snap Bean Leaflets.

PubMed

Hirano, S S; Upper, C D

1989-03-01

The extent to which diel changes in the physical environment affect changes in population size and ice nucleation activity of Pseudomonas syringae on snap bean leaflets was determined under field conditions. To estimate bacterial population size and ice nucleation activity, bean leaflets were harvested at 2-h intervals during each of three 26-h periods. A tube nucleation test was used to assay individual leaflets for ice nuclei. Population sizes of P. syringae were determined by dilution plating of leaflet homogenates. The overall diel changes in P. syringae population sizes differed during each of the 26-h periods. In one 26-h period, there was a continuous increase in the logarithm of P. syringae population size despite intense solar radiation, absence of free moisture on leaf surfaces, and low relative humidity during the day. A mean doubling time of approximately 4.9 h was estimated for the 28-fold increase in P. syringae population size that occurred from 0900 to 0900 h during the 26-h period. However, doubling times of 3.3 and 1.9 h occurred briefly during this period from 1700 to 2300 h and from 0100 to 0700 h, respectively. Thus, growth rates of P. syringae in association with leaves in the field were of the same order of magnitude as optimal rates measured in the laboratory. The frequency with which leaflets bore ice nuclei active at -2.0, -2.2, and -2.5 degrees C varied greatly within each 26-h period. These large diel changes were inversely correlated primarily with the diel changes in air temperature and reflected changes in nucleation frequency rather than changes in population size of P. syringae. Thus, the response of bacterial ice nucleation activity to the physical environment was distinct from the changes in population size of ice nucleation-active P. syringae.

Achieving true sustainability of zoo populations.

PubMed

Lacy, Robert C

2013-01-01

For the last 30 years, cooperative management of irreplaceable animal populations in zoos and aquariums has focused primarily on the goal of minimizing genetic decay within defined time frames, and large advances have been made in technologies to optimize genetic management of closed populations. However, recent analyses have shown that most zoo programs are not projected to meet their stated goals. This has been described as a lack of achieving "sustainability" of the populations, yet by definition a goal of managed decay is not a plan for sustainability. True sustainability requires management of the resource in manner that does not deplete its value for the future. Achieving such sustainability for many managed populations may require changing from managing isolated populations to managing populations that are part of a broader metapopulation, with carefully considered exchange between populations across a spectrum of ex situ to in situ. Managing zoo populations as components of comprehensive conservation strategies for the species will require research on determinants of various kinds of genetic, physiological, behavioral, and morphological variation and their roles in population viability, development of an array of management techniques and tools, training of population managers in metapopulation management and integrated conservation planning, and projections of impacts of management strategies on the viability of the captive populations and all populations that are interactively managed or affected. Such a shift in goals and methods would result in zoo population management being an ongoing part of species conservation rather than short-term or isolated from species conservation. Zoo Biol. 32:19-26, 2013. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.

Self-emergence of Lexicon Consensus in a Population of Autonomous Agents by Means of Evolutionary Strategies

NASA Astrophysics Data System (ADS)

Maravall, Darío; de Lope, Javier; Domínguez, Raúl

In Multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of evolutionary strategies to the self-emergence of a common lexicon in a population of agents. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the agents or the states of the environment itself) into symbols or signals we check whether it is possible for the population to converge in an autonomous, decentralized way to a common lexicon, so that the communication efficiency of the entire population is optimal. We have conducted several experiments, from the simplest case of a 2×2 association matrix (i.e. two meanings and two symbols) to a 3×3 lexicon case and in both cases we have attained convergence to the optimal communication system by means of evolutionary strategies. To analyze the convergence of the population of agents we have defined the population's consensus when all the agents (i.e. the 100% of the population) share the same association matrix or lexicon. As a general conclusion we have shown that evolutionary strategies are powerful enough optimizers to guarantee the convergence to lexicon consensus in a population of autonomous agents.

Population pharmacokinetic modelling of rupatadine solution in 6-11 year olds and optimisation of the experimental design in younger children.

PubMed

Santamaría, Eva; Estévez, Javier Alejandro; Riba, Jordi; Izquierdo, Iñaki; Valle, Marta

2017-01-01

To optimise a pharmacokinetic (PK) study design of rupatadine for 2-5 year olds by using a population PK model developed with data from a study in 6-11 year olds. The design optimisation was driven by the need to avoid children's discomfort in the study. PK data from 6-11 year olds with allergic rhinitis available from a previous study were used to construct a population PK model which we used in simulations to assess the dose to administer in a study in 2-5 year olds. In addition, an optimal design approach was used to determine the most appropriate number of sampling groups, sampling days, total samples and sampling times. A two-compartmental model with first-order absorption and elimination, with clearance dependent on weight adequately described the PK of rupatadine for 6-11 year olds. The dose selected for a trial in 2-5 year olds was 2.5 mg, as it provided a Cmax below the 3 ng/ml threshold. The optimal study design consisted of four groups of children (10 children each), a maximum sampling window of 2 hours in two clinic visits for drawing three samples on day 14 and one on day 28 coinciding with the final examination of the study. A PK study design was optimised in order to prioritise avoidance of discomfort for enrolled 2-5 year olds by taking only four blood samples from each child and minimising the length of hospital stays.

Evaluation of different obesity indices as predictors of type 2 diabetes mellitus in a Chinese population.

PubMed

Xiao, Xianchao; Liu, Yujia; Sun, Chenglin; Gang, Xiaokun; Cheng, Jie; Tian, Suyan; Gao, Ying; Lv, You; Sun, Zhonghua; Li, Yazhen; He, Ping; Liu, Yang; Wang, Gang; Gao, Yuan; Zhu, Liwen; Liu, Yan; Wang, Guixia

2015-05-01

The aim of the present study was to compare correlation coefficients between anthropometric indices and blood glucose level, and to determine optimal cutoff points of obesity indices in a Chinese population. 2419 males and 5140 females participated in this study in Changchun city. Weight, height, WC (waist circumference) and hip circumference were measured; and BMI (body mass index), WHtR (waist height ratio), WHR (waist hip ratio) and BAI (body adiposity index) were calculated by formulas. FPG (fasting plasma glucose), PPG (post-load plasma glucose), HbA1c (glycosylated hemoglobin) and FSI (fasting serum insulin) were measured. WHtR had the highest partial correlation coefficients with blood glucose and HbA1c in both males and females; however, BAI had the lowest coefficients. AUC (area under receiver operating characteristic curves) for WHtR in screening type 2 diabetes mellitus were higher than other indices. We confirmed that the optimal cutoff points of obesity for WHtR, WHR, WC, BMI and BAI were 0.55, 0.92, 88.1, 25.9 and 28.1 in males, and 0.52, 0.85, 81.6, 24.6 and 31.0 in females, respectively. Central obesity correlates more closely to glucose metabolism in Chinese population than general obesity. WHtR is the best index to predict type 2 diabetes mellitus in Chinese adults. © 2014 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Was Wright Right? The Canonical Genetic Code is an Empirical Example of an Adaptive Peak in Nature; Deviant Genetic Codes Evolved Using Adaptive Bridges

PubMed Central

2010-01-01

The canonical genetic code is on a sub-optimal adaptive peak with respect to its ability to minimize errors, and is close to, but not quite, optimal. This is demonstrated by the near-total adjacency of synonymous codons, the similarity of adjacent codons, and comparisons of frequency of amino acid usage with number of codons in the code for each amino acid. As a rare empirical example of an adaptive peak in nature, it shows adaptive peaks are real, not merely theoretical. The evolution of deviant genetic codes illustrates how populations move from a lower to a higher adaptive peak. This is done by the use of “adaptive bridges,” neutral pathways that cross over maladaptive valleys by virtue of masking of the phenotypic expression of some maladaptive aspects in the genotype. This appears to be the general mechanism by which populations travel from one adaptive peak to another. There are multiple routes a population can follow to cross from one adaptive peak to another. These routes vary in the probability that they will be used, and this probability is determined by the number and nature of the mutations that happen along each of the routes. A modification of the depiction of adaptive landscapes showing genetic distances and probabilities of travel along their multiple possible routes would throw light on this important concept. PMID:20711776

Variation of Select Flavonols and Chlorogenic Acid Content of Elderberry Collected Throughout the Eastern United States

PubMed Central

Mudge, Elizabeth; Applequist, Wendy L.; Finley, Jamie; Lister, Patience; Townesmith, Andrew K.; Walker, Karen M.; Brown, Paula N.

2016-01-01

American elderberries are commonly collected from wild plants for use as food and medicinal products. The degree of phytochemical variation amongst wild populations has not been established and might affect the overall quality of elderberry dietary supplements. The three major flavonols identified in elderberries are rutin, quercetin and isoquercetin. Variation in the flavonols and chlorogenic acid was determined for 107 collections of elderberries from throughout the eastern United States using an optimized high performance liquid chromatography with ultraviolet detection method. The mean content was 71.9 mg per 100g fresh weight with variation ranging from 7.0 to 209.7 mg per 100 g fresh weight within the collected population. Elderberries collected from southeastern regions had significantly higher contents in comparison with those in more northern regions. The variability of the individual flavonol and chlorogenic acid profiles of the berries was complex and likely influenced by multiple factors. Several outliers were identified based on unique phytochemical profiles in comparison with average populations. This is the first study to determine the inherent variability of American elderberries from wild collections and can be used to identify potential new cultivars that may produce fruits of unique or high-quality phytochemical content for the food and dietary supplement industries. PMID:26877585

Detection of genomic loci associated with environmental variables using generalized linear mixed models.

PubMed

Lobréaux, Stéphane; Melodelima, Christelle

2015-02-01

We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress. Copyright © 2014 Elsevier Inc. All rights reserved.

Mosquitoes Transmit Unique West Nile Virus Populations during Each Feeding Episode.

PubMed

Grubaugh, Nathan D; Fauver, Joseph R; Rückert, Claudia; Weger-Lucarelli, James; Garcia-Luna, Selene; Murrieta, Reyes A; Gendernalik, Alex; Smith, Darci R; Brackney, Doug E; Ebel, Gregory D

2017-04-25

Arthropod-borne viruses (arboviruses), such as Zika virus, chikungunya virus, and West Nile virus (WNV), pose continuous threats to emerge and cause large epidemics. Often, these events are associated with novel virus variants optimized for local transmission that first arise as minorities within a host. Thus, the conditions that regulate the frequency of intrahost variants are important determinants of emergence. Here, we describe the dynamics of WNV genetic diversity during its transmission cycle. By temporally sampling saliva from individual mosquitoes, we demonstrate that virus populations expectorated by mosquitoes are highly diverse and unique to each feeding episode. After transmission to birds, however, most genetic diversity is removed by strong purifying selection. Further, transmission of potentially mosquito-adaptive WNV variants is strongly influenced by genetic drift in mosquitoes. These results highlight the complex evolutionary forces a novel virus variant must overcome to alter infection phenotypes at the population level. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

System and method of cylinder deactivation for optimal engine torque-speed map operation

DOEpatents

Sujan, Vivek A; Frazier, Timothy R; Follen, Kenneth; Moon, Suk-Min

2014-11-11

This disclosure provides a system and method for determining cylinder deactivation in a vehicle engine to optimize fuel consumption while providing the desired or demanded power. In one aspect, data indicative of terrain variation is utilized in determining a vehicle target operating state. An optimal active cylinder distribution and corresponding fueling is determined from a recommendation from a supervisory agent monitoring the operating state of the vehicle of a subset of the total number of cylinders, and a determination as to which number of cylinders provides the optimal fuel consumption. Once the optimal cylinder number is determined, a transmission gear shift recommendation is provided in view of the determined active cylinder distribution and target operating state.

Physiological Trade-Offs Along a Fast-Slow Lifestyle Continuum in Fishes: What Do They Tell Us about Resistance and Resilience to Hypoxia?

PubMed

Stoffels, Rick J

2015-01-01

It has recently been suggested that general rules of change in ecological communities might be found through the development of functional relationships between species traits and performance. The physiological, behavioural and life-history traits of fishes are often organised along a fast-slow lifestyle continuum (FSLC). With respect to resistance (capacity for population to resist change) and resilience (capacity for population to recover from change) to environmental hypoxia, the literature suggests that traits enhancing resilience may come at the expense of traits promoting resistance to hypoxia; a trade-off may exist. Here I test whether three fishes occupying different positions along the FSLC trade-off resistance and resilience to environmental hypoxia. Static respirometry experiments were used to determine resistance, as measured by critical oxygen tension (Pcrit), and capacity for (RC) and magnitude of metabolic reduction (RM). Swimming respirometry experiments were used to determine aspects of resilience: critical (Ucrit) and optimal swimming speed (Uopt), and optimal cost of transport (COTopt). Results pertaining to metabolic reduction suggest a resistance gradient across species described by the inequality Melanotaenia fluviatilis (fast lifestyle) < Hypseleotris sp. (intermediate lifestyle) < Mogurnda adspersa (slow lifestyle). The Ucrit and COTopt data suggest a resilience gradient described by the reverse inequality, and so the experiments generally indicate that three fishes occupying different positions on the FSLC trade-off resistance and resilience to hypoxia. However, the scope of inferences that can be drawn from an individual study is narrow, and so steps towards general, trait-based rules of fish community change along environmental gradients are discussed.

Evaluating scenarios of locations and capacities for vaccine storage in Nigeria.

PubMed

Hirsh Bar Gai, Dor; Graybill, Zachary; Voevodsky, Paule; Shittu, Ekundayo

2018-06-07

Many developing countries still face the prevalence of preventable childhood diseases because their vaccine supply chain systems are inadequate by design or structure to meet the needs of their populations. Currently, Nigeria is evaluating options in the redesign of the country's vaccine supply chain. Using Nigeria as a case study, the objective is to evaluate different regional supply chain scenarios to identify the cost minimizing optimal hub locations and storage capacities for doses of different vaccines to achieve a 100% fill rate. First, we employ a shortest-path optimization routine to determine hub locations. Second, we develop a total cost minimizing routine based on stochastic optimization to determine the optimal capacities at the hubs. This model uses vaccine supply data between 2011 and 2014 provided by Nigeria's National Primary Health Care Development Agency (NPHCDA) on Tuberculosis, Polio, Yellow Fever, Tetanus Toxoid, and Hepatitis B. We find that a two-regional system with no central hub (NC2) cut costs by 23% to achieve a 100% fill rate when compared to optimizing the existing chain of six regions with a central hub (EC6). While the government's leading redesign alternative - no central three-hub system (Gov NC3) - reduces costs by 21% compared with the current EC6, it is more expensive than our NC2 system by 3%. In terms of capacity increases, optimizing the current system requires 42% more capacity than our NC2 system. Although the proposed Gov NC3 system requires the least increase in storage capacity, it requires the most distance to achieve a 100% coverage and about 15% more than our NC2. Overall, we find that improving the current system with a central hub and all its variants, even with optimal regional hub locations, require more storage capacities and are costlier than systems without a central hub. While this analysis prescribes the no central hub with two regions (NC2) as the least cost scenario, it is imperative to note that other configurations have benefits and comparative tradeoffs. Our approach and results offer some guidance for future vaccine supply chain redesigns in countries with similar layouts to Nigeria's. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluating mallard adaptive management models with time series

USGS Publications Warehouse

Conn, P.B.; Kendall, W.L.

2004-01-01

Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these suggestions should help lower the probability of erroneous learning in mallard ABM and adaptive management in general.

Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Chiu, Y.; Nishikawa, T.

2013-12-01

With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

Computational design optimization for microfluidic magnetophoresis

PubMed Central

Plouffe, Brian D.; Lewis, Laura H.; Murthy, Shashi K.

2011-01-01

Current macro- and microfluidic approaches for the isolation of mammalian cells are limited in both efficiency and purity. In order to design a robust platform for the enumeration of a target cell population, high collection efficiencies are required. Additionally, the ability to isolate pure populations with minimal biological perturbation and efficient off-chip recovery will enable subcellular analyses of these cells for applications in personalized medicine. Here, a rational design approach for a simple and efficient device that isolates target cell populations via magnetic tagging is presented. In this work, two magnetophoretic microfluidic device designs are described, with optimized dimensions and operating conditions determined from a force balance equation that considers two dominant and opposing driving forces exerted on a magnetic-particle-tagged cell, namely, magnetic and viscous drag. Quantitative design criteria for an electromagnetic field displacement-based approach are presented, wherein target cells labeled with commercial magnetic microparticles flowing in a central sample stream are shifted laterally into a collection stream. Furthermore, the final device design is constrained to fit on standard rectangular glass coverslip (60 (L)×24 (W)×0.15 (H) mm3) to accommodate small sample volume and point-of-care design considerations. The anticipated performance of the device is examined via a parametric analysis of several key variables within the model. It is observed that minimal currents (<500 mA) are required to generate magnetic fields sufficient to separate cells from the sample streams flowing at rate as high as 7 ml∕h, comparable to the performance of current state-of-the-art magnet-activated cell sorting systems currently used in clinical settings. Experimental validation of the presented model illustrates that a device designed according to the derived rational optimization can effectively isolate (∼100%) a magnetic-particle-tagged cell population from a homogeneous suspension even in a low abundance. Overall, this design analysis provides a rational basis to select the operating conditions, including chamber and wire geometry, flow rates, and applied currents, for a magnetic-microfluidic cell separation device. PMID:21526007

Identifying Cost-Effective Dynamic Policies to Control Epidemics

PubMed Central

Yaesoubi, Reza; Cohen, Ted

2016-01-01

We describe a mathematical decision model for identifying dynamic health policies for controlling epidemics. These dynamic policies aim to select the best current intervention based on accumulating epidemic data and the availability of resources at each decision point. We propose an algorithm to approximate dynamic policies that optimize the population’s net health benefit, a performance measure which accounts for both health and monetary outcomes. We further illustrate how dynamic policies can be defined and optimized for the control of a novel viral pathogen, where a policy maker must decide (i) when to employ or lift a transmission-reducing intervention (e.g. school closure) and (ii) how to prioritize population members for vaccination when a limited quantity of vaccines first become available. Within the context of this application, we demonstrate that dynamic policies can produce higher net health benefit than more commonly described static policies that specify a pre-determined sequence of interventions to employ throughout epidemics. PMID:27449759

Dose-finding study of carbamylated monomeric allergoid tablets in grass-allergic rhinoconjunctivitis patients.

PubMed

Mösges, Ralph; Rohdenburg, Christina; Eichel, Andrea; Zadoyan, Gregor; Kasche, Elena-Manja; Shah-Hosseini, Kija; Lehmacher, Walter; Schmalz, Petra; Compalati, Enrico

2017-11-01

To determine the optimal effective and safe dose of sublingual immunotherapy tablets containing carbamylated monomeric allergoids in patients with grass pollen-induced allergic rhinoconjunctivitis. In this prospective, randomized, double-blind, active-controlled, multicenter, Phase II study, four different daily doses were applied preseasonally for 12 weeks. Of 158 randomized adults, 155 subjects (safety population) received 300 units of allergy (UA)/day (n = 36), 600 UA/day (n = 43), 1000 UA/day (n = 39), or 2000 UA/day (n = 37). After treatment, 54.3, 47.6, 59.0 and 51.4% of patients, respectively, ceased to react to the highest allergen concentration in a conjunctival provocation test. Furthermore, the response threshold improved in 70.4, 62.9, 76.7 and 66.7% of patients, respectively. No serious adverse events occurred. This study found 1000 UA/day to be the optimal effective and safe dose.

Influence of Sequential vs. Simultaneous Dual-Task Exercise Training on Cognitive Function in Older Adults.

PubMed

Tait, Jamie L; Duckham, Rachel L; Milte, Catherine M; Main, Luana C; Daly, Robin M

2017-01-01

Emerging research indicates that exercise combined with cognitive training may improve cognitive function in older adults. Typically these programs have incorporated sequential training, where exercise and cognitive training are undertaken separately. However, simultaneous or dual-task training, where cognitive and/or motor training are performed simultaneously with exercise, may offer greater benefits. This review summary provides an overview of the effects of combined simultaneous vs. sequential training on cognitive function in older adults. Based on the available evidence, there are inconsistent findings with regard to the cognitive benefits of sequential training in comparison to cognitive or exercise training alone. In contrast, simultaneous training interventions, particularly multimodal exercise programs in combination with secondary tasks regulated by sensory cues, have significantly improved cognition in both healthy older and clinical populations. However, further research is needed to determine the optimal characteristics of a successful simultaneous training program for optimizing cognitive function in older people.

Locally optimal extracellular stimulation for chaotic desynchronization of neural populations.

PubMed

Wilson, Dan; Moehlis, Jeff

2014-10-01

We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process.

Cooperative combinatorial optimization: evolutionary computation case study.

PubMed

Burgin, Mark; Eberbach, Eugene

2008-01-01

This paper presents a formalization of the notion of cooperation and competition of multiple systems that work toward a common optimization goal of the population using evolutionary computation techniques. It is proved that evolutionary algorithms are more expressive than conventional recursive algorithms, such as Turing machines. Three classes of evolutionary computations are introduced and studied: bounded finite, unbounded finite, and infinite computations. Universal evolutionary algorithms are constructed. Such properties of evolutionary algorithms as completeness, optimality, and search decidability are examined. A natural extension of evolutionary Turing machine (ETM) model is proposed to properly reflect phenomena of cooperation and competition in the whole population.

Impact of population growth and population ethics on climate change mitigation policy

PubMed Central

Scovronick, Noah; Budolfson, Mark B.; Dennig, Francis; Fleurbaey, Marc; Siebert, Asher; Socolow, Robert H.; Spears, Dean; Wagner, Fabian

2017-01-01

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period’s discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing—rather than merely cost savings—again depends on the ethical approach to valuing population. PMID:29087298

Impact of population growth and population ethics on climate change mitigation policy.

PubMed

Scovronick, Noah; Budolfson, Mark B; Dennig, Francis; Fleurbaey, Marc; Siebert, Asher; Socolow, Robert H; Spears, Dean; Wagner, Fabian

2017-11-14

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period's discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing-rather than merely cost savings-again depends on the ethical approach to valuing population. Copyright © 2017 the Author(s). Published by PNAS.

The effect of Fisher information matrix approximation methods in population optimal design calculations.

PubMed

Strömberg, Eric A; Nyberg, Joakim; Hooker, Andrew C

2016-12-01

With the increasing popularity of optimal design in drug development it is important to understand how the approximations and implementations of the Fisher information matrix (FIM) affect the resulting optimal designs. The aim of this work was to investigate the impact on design performance when using two common approximations to the population model and the full or block-diagonal FIM implementations for optimization of sampling points. Sampling schedules for two example experiments based on population models were optimized using the FO and FOCE approximations and the full and block-diagonal FIM implementations. The number of support points was compared between the designs for each example experiment. The performance of these designs based on simulation/estimations was investigated by computing bias of the parameters as well as through the use of an empirical D-criterion confidence interval. Simulations were performed when the design was computed with the true parameter values as well as with misspecified parameter values. The FOCE approximation and the Full FIM implementation yielded designs with more support points and less clustering of sample points than designs optimized with the FO approximation and the block-diagonal implementation. The D-criterion confidence intervals showed no performance differences between the full and block diagonal FIM optimal designs when assuming true parameter values. However, the FO approximated block-reduced FIM designs had higher bias than the other designs. When assuming parameter misspecification in the design evaluation, the FO Full FIM optimal design was superior to the FO block-diagonal FIM design in both of the examples.

The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading.

PubMed

Beck, Roy W; Connor, Crystal G; Mullen, Deborah M; Wesley, David M; Bergenstal, Richard M

2017-08-01

HbA 1c is a v aluable metric for comparing treatment groups in a randomized trial, for assessing glycemic trends in a population over time, or for cross-sectional comparisons of glycemic control in different populations. However, what is not widely appreciated is that HbA 1c may not be a good indicator of an individual patient's glycemic control because of the wide range of mean glucose concentrations and glucose profiles that can be associated with a given HbA 1c level. To illustrate this point, we plotted mean glucose measured with continuous glucose monitoring (CGM) versus central laboratory-measured HbA 1c in 387 participants in three randomized trials, showing that not infrequently HbA 1c may underestimate or overestimate mean glucose, sometimes substantially. Thus, if HbA 1c is to be used to assess glycemic control, it is imperative to know the patient's actual mean glucose to understand how well HbA 1c is an indicator of the patient's glycemic control. With knowledge of the mean glucose, an estimated HbA 1c (eA1C) can be calculated with the formula provided in this article to compare with the measured HbA 1c . Estimating glycemic control from HbA 1c alone is in essence applying a population average to an individual, which can be misleading. Thus, a patient's CGM glucose profile has considerable value for optimizing his or her diabetes management. In this era of personalized, precision medicine, there are few better examples with respect to the fallacy of applying a population average to a specific patient rather than using specific information about the patient to determine the optimal approach to treatment. © 2017 by the American Diabetes Association.

Lessons Learned from the Deployment of a Hydrologic Science Observations Data Model

NASA Astrophysics Data System (ADS)

Beran, B.; Valentine, D.; Zaslavsky, I.; van Ingen, C.

2007-12-01

The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. The CUAHSI Observations Data Model (ODM) is a data model to store hydrologic observations data in a system designed to optimize data retrieval for integrated analysis of information collected by multiple investigators. The ODM v1, provides a distinct view into what information the community has determined is important to store, and what data views the community. As we began to work with ODM v1, we discovered the problem with the approach of tightly linking the community views of data to the database model. Design decisions for ODM v1 hindered the ability to utilize the datamodel as an aggregated information catalog need for the cyberinfrastructure. Different development groups had different approaches to populating the datamodel, and handling the complexity. The approaches varied from populating the ODM with a bare minimum of constraints to creating a fully constrained datamodel. This made the integration of different tools, difficult. In the end, we decided to utilize the fully populate model which ensure maximum compatibility with the data sources. Groups also discovered that while the data model central concept was optimized for data retrieval of individual observation. In practice, the concept of data series is better to manage data, yet there is no link between data series and data value in ODM v1. We are beginning to develop ODM v2 as a series of profiles. By utilizing profiles, we intend to make the core information model smaller, more manageable, and simpler to understand and populate. We intend to keep the community semantics, improve the linkages between data series and data values, and enhance data discovery for the CUAHSI cyberinfrastructure.

Relationship of nutritional status to health and societal participation in children with cerebral palsy.

PubMed

Samson-Fang, Lisa; Fung, Ellen; Stallings, Virginia A; Conaway, Mark; Worley, Gordon; Rosenbaum, Peter; Calvert, Randy; O'donnell, Maureen; Henderson, Richard C; Chumlea, W Cameron; Liptak, Gregory S; Stevenson, Richard D

2002-11-01

To describe nutritional status in a population-based sample of children with moderate or severe cerebral palsy (CP) and to explore the relationships between nutritional status and health and functional outcomes. A population-based strategy was used to enroll children with CP at 6 geographic sites. Research assistants performed anthropometric assessment, determined severity of motor impairment, and interviewed caregivers with the Child Health Questionnaire and a questionnaire designed specifically for this study. Anthropometric measures were converted to Z scores and the relationship between health and nutritional status was assessed using regression models. Among the 235 participants, indicators of malnutrition were common. Poor nutritional status correlated with increased health care utilization (hospitalizations, doctor visits) and decreased participation in usual activities by the child and parent. Malnutrition is common in children with moderate or severe CP and associated with poorer health status and limitations in societal participation. Further studies are needed to determine the nature of these associations and how to manage nutrition in children with CP to optimize growth and health outcomes.

Physiology of folic acid in health and disease.

PubMed

Stanger, O

2002-04-01

Folates are important cofactors in the transfer and utilization of one-carbon-groups and play a key role in the remethylation of methionine thus providing essential methyl groups for numerous biological reactions. Furthermore, folates donate one-carbon units in the process of DNA-biosynthesis with implications for the regulation of gene expression, transcription, chromatine structure, genomic repair and genomic stability. As the role of folate deficiency in atherosclerotic cardiovascular disease, neurological and neuropsychiatric disorders, in congenital defects and carcinogenesis has become better understood, folate has been recognized as having great potential to prevent these many disorders through folate supplementation for the general population. Folate acts directly to produce antioxidant effects, interactions with enzyme endothelial NO synthase (eNOS) and effects on cofactor bioavailability of NO. Folate acts indirectly to lower homocysteine levels and insure optimal functioning of the methylation cycle. Folate metabolism provides an interesting example of gene-environmental interaction. A great part of the population, especially subgroups with higher demand, appears to have suboptimal folate intake, as determined through more sensitive parameters now widely determined. The available data strongly suggest that criteria for "folate deficiency" may have to be redefined.

Deriving the reference value from the circadian motor active patterns in the "non-dementia" population, compared to the "dementia" population: What is the amount of physical activity conducive to the good circadian rhythm.

PubMed

Kodama, Ayuto; Kume, Yu; Tsugaruya, Megumi; Ishikawa, Takashi

2016-01-01

The circadian rhythm in older adults is commonly known to change with a decrease in physical activity. However, the association between circadian rhythm metrics and physical activity remains unclear. The objective of this study was to examine circadian activity patterns in older people with and without dementia and to determine the amount of physical activity conducive to a good circadian measurement. Circadian parameters were collected from 117 older community-dwelling people (66 subjects without dementia and 52 subjects with dementia); the parameters were measured continuously using actigraphy for 7 days. A receiver operating characteristic (ROC) curve was applied to determine reference values for the circadian rhythm parameters, consisting of interdaily stability (IS), intradaily variability (IV), and relative amplitude (RA), in older subjects. The ROC curve revealed reference values of 0.55 for IS, 1.10 for IV, and 0.82 for RA. In addition, as a result of the ROC curve in the moderate-to-vigorous physical Activity (MVPA) conducive to the reference value of the Non-parametric Circadian Rhythm Analysis per day, the optimal reference values were 51 minutes for IV and 55 minutes for RA. However, the IS had no classification accuracy. Our results demonstrated the reference values derived from the circadian parameters of older Japanese population with or without dementia. Also, we determined the MVPA conducive to a good circadian rest-active pattern. This reference value for physical activity conducive to a good circadian rhythm might be useful for developing a new index for health promotion in the older community-dwelling population.

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence.

PubMed

Jiang, Hao; Ching, Wai-Ki; Qiu, Yushan; Cheng, Xiao-Qing

2017-12-14

Positive semi-definiteness is a critical property in kernel methods for Support Vector Machine (SVM) by which efficient solutions can be guaranteed through convex quadratic programming. However, a lot of similarity functions in applications do not produce positive semi-definite kernels. We propose projection method by constructing projection matrix on indefinite kernels. As a generalization of the spectrum method (denoising method and flipping method), the projection method shows better or comparable performance comparing to the corresponding indefinite kernel methods on a number of real world data sets. Under the Bregman matrix divergence theory, we can find suggested optimal λ in projection method using unconstrained optimization in kernel learning. In this paper we focus on optimal λ determination, in the pursuit of precise optimal λ determination method in unconstrained optimization framework. We developed a perturbed von-Neumann divergence to measure kernel relationships. We compared optimal λ determination with Logdet Divergence and perturbed von-Neumann Divergence, aiming at finding better λ in projection method. Results on a number of real world data sets show that projection method with optimal λ by Logdet divergence demonstrate near optimal performance. And the perturbed von-Neumann Divergence can help determine a relatively better optimal projection method. Projection method ia easy to use for dealing with indefinite kernels. And the parameter embedded in the method can be determined through unconstrained optimization under Bregman matrix divergence theory. This may provide a new way in kernel SVMs for varied objectives.

Clinical feasibility of exercise-based A-V interval optimization for cardiac resynchronization: a pilot study.

PubMed

Choudhuri, Indrajit; MacCarter, Dean; Shaw, Rachael; Anderson, Steve; St Cyr, John; Niazi, Imran

2014-11-01

One-third of eligible patients fail to respond to cardiac resynchronization therapy (CRT). Current methods to "optimize" the atrio-ventricular (A-V) interval are performed at rest, which may limit its efficacy during daily activities. We hypothesized that low-intensity cardiopulmonary exercise testing (CPX) could identify the most favorable physiologic combination of specific gas exchange parameters reflecting pulmonary blood flow or cardiac output, stroke volume, and left atrial pressure to guide determination of the optimal A-V interval. We assessed relative feasibility of determining the optimal A-V interval by three methods in 17 patients who underwent optimization of CRT: (1) resting echocardiographic optimization (the Ritter method), (2) resting electrical optimization (intrinsic A-V interval and QRS duration), and (3) during low-intensity, steady-state CPX. Five sequential, incremental A-V intervals were programmed in each method. Assessment of cardiopulmonary stability and potential influence on the CPX-based method were assessed. CPX and determination of a physiological optimal A-V interval was successfully completed in 94.1% of patients, slightly higher than the resting echo-based approach (88.2%). There was a wide variation in the optimal A-V delay determined by each method. There was no observed cardiopulmonary instability or impact of the implant procedure that affected determination of the CPX-based optimized A-V interval. Determining optimized A-V intervals by CPX is feasible. Proposed mechanisms explaining this finding and long-term impact require further study. ©2014 Wiley Periodicals, Inc.

Obesity and skin and soft tissue infections: how to optimize antimicrobial usage for prevention and treatment?

PubMed

Grupper, Mordechai; Nicolau, David P

2017-04-01

Skin and soft tissue infections (SSTIs) are prevalent in the obese population, with rising trend expected. Although numerous antibiotics are available for the prevention and treatment of SSTIs, their characterization in obese patients is not a regulatory mandate. Consequently, information that carries importance for optimizing the dosing regimen in the obese population may not be readily available. This review focuses on the most recent pharmacokinetic and pharmacodynamic data on this topic with attention to cefazolin for surgical prophylaxis as well as antibiotics that are active against methicillin-resistant Staphylococcus aureus (MRSA). Moreover, the implications for optimizing SSTIs prevention and treatment in the obese population will also be discussed. On the basis of pharmacokinetic/pharmacodynamic considerations, most studies found a perioperative prophylactic cefazolin regimen of 2 g to be reasonable in the case of obese patients undergoing cesarean delivery or bariatric surgery. There is general paucity of data regarding the pharmacokinetic/pharmacodynamic characteristics of antimicrobials active against MRSA in obese patients, especially for the target tissue. Therapeutic drug monitoring has been correlated with pharmacokinetic/pharmacodynamic optimization for vancomycin and teicoplanin, and should be used in these cases. There is more supportive evidence for the use of oxazolidinones (linezolid and tedizolid), daptomycin and lipoglycopeptides (telavancin, dalbavancin and oritavancin) in the management of SSTIs in this population. The pharmacokinetic/pharmacodynamic approach, which can be used as a basis or supplement to clinical trials, provides valuable data and decision-making tools for optimizing regimens used for both prevention and treatment of SSTIs in the obese population. Important pharmacokinetic/pharmacodynamic characteristics of antibiotics, such as the penetration into the subcutaneous tissue and the probability of reaching the pharmacodynamic, target dictate efficacy, and thus should be taken into account and further investigated.

Protection against trichothecene mycotoxins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1983-01-01

Trichothecenes and their effects on humans have attracted national and international attention because of their reported use in warfare. This study arose out of a concern about such uses and the potential harm these substances could cause among civilian and military populations that might be exposed to them. Accordingly, this report is intended to assist in the protection not only of U.S. Armed Forces against the adverse effects of trichothecenes but also of civilian populations that may come into contact with these toxins during peace or war. The committee concentrated on the following two major objectives: (1) examination of themore » environmental and biological behavior of the trichothecene class of mycotoxins to determine what protective measures can be taken and (2) development of the means for optimizing the protection of human beings against the effects of trichothecenes through appropriate prophylaxes and treatments.« less

The stability of colorectal cancer mathematical models

NASA Astrophysics Data System (ADS)

Khairudin, Nur Izzati; Abdullah, Farah Aini

2013-04-01

Colorectal cancer is one of the most common types of cancer. To better understand about the kinetics of cancer growth, mathematical models are used to provide insight into the progression of this natural process which enables physicians and oncologists to determine optimal radiation and chemotherapy schedules and develop a prognosis, both of which are indispensable for treating cancer. This thesis investigates the stability of colorectal cancer mathematical models. We found that continuous saturating feedback is the best available model of colorectal cancer growth. We also performed stability analysis. The result shows that cancer progress in sequence of genetic mutations or epigenetic which lead to a very large number of cells population until become unbounded. The cell population growth initiate and its saturating feedback is overcome when mutation changes causing the net per-capita growth rate of stem or transit cells exceed critical threshold.

Uncertainty-Based Multi-Objective Optimization of Groundwater Remediation Design

NASA Astrophysics Data System (ADS)

Singh, A.; Minsker, B.

2003-12-01

Management of groundwater contamination is a cost-intensive undertaking filled with conflicting objectives and substantial uncertainty. A critical source of this uncertainty in groundwater remediation design problems comes from the hydraulic conductivity values for the aquifer, upon which the prediction of flow and transport of contaminants are dependent. For a remediation solution to be reliable in practice it is important that it is robust over the potential error in the model predictions. This work focuses on incorporating such uncertainty within a multi-objective optimization framework, to get reliable as well as Pareto optimal solutions. Previous research has shown that small amounts of sampling within a single-objective genetic algorithm can produce highly reliable solutions. However with multiple objectives the noise can interfere with the basic operations of a multi-objective solver, such as determining non-domination of individuals, diversity preservation, and elitism. This work proposes several approaches to improve the performance of noisy multi-objective solvers. These include a simple averaging approach, taking samples across the population (which we call extended averaging), and a stochastic optimization approach. All the approaches are tested on standard multi-objective benchmark problems and a hypothetical groundwater remediation case-study; the best-performing approach is then tested on a field-scale case at Umatilla Army Depot.

Hygiene behaviour and associated factors among in-school adolescents in nine African countries.

PubMed

Pengpid, Supa; Peltzer, Karl

2011-06-01

This report examines hygiene behaviour and associated factors among 13-15 year old in-school adolescents in nine African countries. The total sample included 25,760 school children aged 13-15 years from nationally representative samples from nine African countries. We examined the prevalence of and relationship between tooth brushing, hand washing before eating, hand washing after toileting, hand washing with soap and a range of psychosocial factors such as socio-demographic characteristics, health behaviour, mental health or well-being and protective factors. Overall, sub-optimal hygiene behaviour was reported, the proportions of school children reporting optimal (>once a day) tooth brushing (77.3%) was higher than the proportions reported for washing their hands regularly before meals (62.2%), after toileting (58.4%) and washing their hands with soap (35.0%). In multivariate analysis higher education, health-enhancing behaviours such as daily fruits or vegetable consumption, and protective factors such as caregiver supervision were associated with tooth brushing, hand washing before meals, hand washing after toileting and washing of hands with soap. The cross-national data on hygiene behaviour from nine African countries found sub-optimal hygiene behaviour. Various determinants of optimal hygiene behaviour were identified that can guide programmes to improve hygiene behaviour of this adolescent population.

Performing aggressive code optimization with an ability to rollback changes made by the aggressive optimizations

DOEpatents

Gschwind, Michael K

2013-07-23

Mechanisms for aggressively optimizing computer code are provided. With these mechanisms, a compiler determines an optimization to apply to a portion of source code and determines if the optimization as applied to the portion of source code will result in unsafe optimized code that introduces a new source of exceptions being generated by the optimized code. In response to a determination that the optimization is an unsafe optimization, the compiler generates an aggressively compiled code version, in which the unsafe optimization is applied, and a conservatively compiled code version in which the unsafe optimization is not applied. The compiler stores both versions and provides them for execution. Mechanisms are provided for switching between these versions during execution in the event of a failure of the aggressively compiled code version. Moreover, predictive mechanisms are provided for predicting whether such a failure is likely.

Genetic polymorphisms of pharmacogenomic VIP variants in the Yi population from China.

PubMed

Yan, Mengdan; Li, Dianzhen; Zhao, Guige; Li, Jing; Niu, Fanglin; Li, Bin; Chen, Peng; Jin, Tianbo

2018-03-30

Drug response and target therapeutic dosage are different among individuals. The variability is largely genetically determined. With the development of pharmacogenetics and pharmacogenomics, widespread research have provided us a wealth of information on drug-related genetic polymorphisms, and the very important pharmacogenetic (VIP) variants have been identified for the major populations around the world whereas less is known regarding minorities in China, including the Yi ethnic group. Our research aims to screen the potential genetic variants in Yi population on pharmacogenomics and provide a theoretical basis for future medication guidance. In the present study, 80 VIP variants (selected from the PharmGKB database) were genotyped in 100 unrelated and healthy Yi adults recruited for our research. Through statistical analysis, we made a comparison between the Yi and other 11 populations listed in the HapMap database for significant SNPs detection. Two specific SNPs were subsequently enrolled in an observation on global allele distribution with the frequencies downloaded from ALlele FREquency Database. Moreover, F-statistics (Fst), genetic structure and phylogenetic tree analyses were conducted for determination of genetic similarity between the 12 ethnic groups. Using the χ2 tests, rs1128503 (ABCB1), rs7294 (VKORC1), rs9934438 (VKORC1), rs1540339 (VDR) and rs689466 (PTGS2) were identified as the significantly different loci for further analysis. The global allele distribution revealed that the allele "A" of rs1540339 and rs9934438 were more frequent in Yi people, which was consistent with the most populations in East Asia. F-statistics (Fst), genetic structure and phylogenetic tree analyses demonstrated that the Yi and CHD shared a closest relationship on their genetic backgrounds. Additionally, Yi was considered similar to the Han people from Shaanxi province among the domestic ethnic populations in China. Our results demonstrated significant differences on several polymorphic SNPs and supplement the pharmacogenomic information for the Yi population, which could provide new strategies for optimizing clinical medication in accordance with the genetic determinants of drug toxicity and efficacy. Copyright © 2018 Elsevier B.V. All rights reserved.

Exploring optimum cut-off scores to screen for probable posttraumatic stress disorder within a sample of UK treatment-seeking veterans

PubMed Central

Murphy, Dominic; Ross, Jana; Ashwick, Rachel; Armour, Cherie; Busuttil, Walter

2017-01-01

ABSTRACT Background: Previous research exploring the psychometric properties of the scores of measures of posttraumatic stress disorder (PTSD) suggests there is variation in their functioning depending on the target population. To date, there has been little study of these properties within UK veteran populations. Objective: This study aimed to determine optimally efficient cut-off values for the Impact of Event Scale-Revised (IES-R) and the PTSD Checklist for DSM-5 (PCL-5) that can be used to assess for differential diagnosis of presumptive PTSD. Methods: Data from a sample of 242 UK veterans assessed for mental health difficulties were analysed. The criterion-related validity of the PCL-5 and IES-R were evaluated against the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5). Kappa statistics were used to assess the level of agreement between the DSM-IV and DSM-5 classification systems. Results: The optimal cut-off scores observed within this sample were 34 or above on the PCL-5 and 46 or above on the IES-R. The PCL-5 cut-off is similar to the previously reported values, but the IES-R cut-off identified in this study is higher than has previously been recommended. Overall, a moderate level of agreement was found between participants screened positive using the DSM-IV and DSM-5 classification systems of PTSD. Conclusions: Our findings suggest that the PCL-5 and IES-R can be used as brief measures within veteran populations presenting at secondary care to assess for PTSD. The use of a higher cut-off for the IES-R may be helpful for differentiating between veterans who present with PTSD and those who may have some sy`mptoms of PTSD but are sub-threshold for meeting a diagnosis. Further, the use of more accurate optimal cut-offs may aid clinicians to better monitor changes in PTSD symptoms during and after treatment. PMID:29435200

Exploring optimum cut-off scores to screen for probable posttraumatic stress disorder within a sample of UK treatment-seeking veterans.

PubMed

Murphy, Dominic; Ross, Jana; Ashwick, Rachel; Armour, Cherie; Busuttil, Walter

2017-01-01

Background : Previous research exploring the psychometric properties of the scores of measures of posttraumatic stress disorder (PTSD) suggests there is variation in their functioning depending on the target population. To date, there has been little study of these properties within UK veteran populations. Objective : This study aimed to determine optimally efficient cut-off values for the Impact of Event Scale-Revised (IES-R) and the PTSD Checklist for DSM-5 (PCL-5) that can be used to assess for differential diagnosis of presumptive PTSD. Methods : Data from a sample of 242 UK veterans assessed for mental health difficulties were analysed. The criterion-related validity of the PCL-5 and IES-R were evaluated against the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5). Kappa statistics were used to assess the level of agreement between the DSM-IV and DSM-5 classification systems. Results : The optimal cut-off scores observed within this sample were 34 or above on the PCL-5 and 46 or above on the IES-R. The PCL-5 cut-off is similar to the previously reported values, but the IES-R cut-off identified in this study is higher than has previously been recommended. Overall, a moderate level of agreement was found between participants screened positive using the DSM-IV and DSM-5 classification systems of PTSD. Conclusions : Our findings suggest that the PCL-5 and IES-R can be used as brief measures within veteran populations presenting at secondary care to assess for PTSD. The use of a higher cut-off for the IES-R may be helpful for differentiating between veterans who present with PTSD and those who may have some sy`mptoms of PTSD but are sub-threshold for meeting a diagnosis. Further, the use of more accurate optimal cut-offs may aid clinicians to better monitor changes in PTSD symptoms during and after treatment.

Household water demand and welfare loss for future Europe

NASA Astrophysics Data System (ADS)

Bernhard, Jeroen; Reynaud, Arnaud; Lanzanova, Denis; de Roo, Ad

2015-04-01

Matching the availability of water to its demand in Europe is a major challenge for the future due to expected economic and demographic developments and climate change. This means there is a growing need to estimate future water demand and to optimize the water allocation to all end users to counteract welfare loss. At the European scale it is currently not possible to assess the impact of social and economic changes on future water demand or to prioritize water allocation amongst different sectors based on economic damage without extensive use of assumptions and generalizations. Indeed, our review of existing regional optimization models for Europe reveals that the social-economic component of the water use system needs to be improved by complementing them with detailed water use estimates and cost/benefit functions in order to determine the optimal situation. Our study contributes to closing this knowledge gap for the European household sector by quantifying future water demand and the effect of water pricing, as well as providing a method for the calculation of monetary damage due to unmet demand at the highest spatial resolution possible. We used a water demand function approach in which household water consumption depends upon some exogenous drivers including water price, household income, population and household characteristics and climate conditions. For each European country, the annual water consumption per capita was calculated at regional level (NUTS3) and subsequently disaggregated to five kilometer grid level based on a population density map. In order to produce estimates of water demand, the evolution of the explanatory variables of the water demand functions and population density map were simulated until 2050 based on related variables such as GDP and demographic projections. The results of this study will be integrated into the JRC hydro-economic modelling framework for an assessment of the Water-Agriculture-Energy-Ecosystems Nexus.

Determination of Ammonia Oxidizing Bacteria and Nitrate Oxidizing Bacteria in Wastewater and Bioreactors

NASA Technical Reports Server (NTRS)

Francis, Somilez Asya

2014-01-01

The process of water purification has many different physical, chemical, and biological processes. One part of the biological process is the task of ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB). Both play critical roles in the treatment of wastewater by oxidizing toxic compounds. The broad term is nitrification, a naturally occurring process that is carried out by AOB and NOB by using oxidation to convert ammonia to nitrite and nitrite to nitrate. To monitor this biological activity, bacterial staining was performed on wastewater contained in inoculum tanks and biofilm samples from bioreactors. Using microscopy and qPCR, the purpose of this experiment was to determine if the population of AOB and NOB in wastewater and membrane bioreactors changed depending on temperature and hibernation conditions to determine the optimal parameters for AOB/NOB culture to effectively clean wastewater.

Optimal savings and the value of population.

PubMed

Arrow, Kenneth J; Bensoussan, Alain; Feng, Qi; Sethi, Suresh P

2007-11-20

We study a model of economic growth in which an exogenously changing population enters in the objective function under total utilitarianism and into the state dynamics as the labor input to the production function. We consider an arbitrary population growth until it reaches a critical level (resp. saturation level) at which point it starts growing exponentially (resp. it stops growing altogether). This requires population as well as capital as state variables. By letting the population variable serve as the surrogate of time, we are still able to depict the optimal path and its convergence to the long-run equilibrium on a two-dimensional phase diagram. The phase diagram consists of a transient curve that reaches the classical curve associated with a positive exponential growth at the time the population reaches the critical level. In the case of an asymptotic population saturation, we expect the transient curve to approach the equilibrium as the population approaches its saturation level. Finally, we characterize the approaches to the classical curve and to the equilibrium.

Optimal savings and the value of population

PubMed Central

Arrow, Kenneth J.; Bensoussan, Alain; Feng, Qi; Sethi, Suresh P.

2007-01-01

We study a model of economic growth in which an exogenously changing population enters in the objective function under total utilitarianism and into the state dynamics as the labor input to the production function. We consider an arbitrary population growth until it reaches a critical level (resp. saturation level) at which point it starts growing exponentially (resp. it stops growing altogether). This requires population as well as capital as state variables. By letting the population variable serve as the surrogate of time, we are still able to depict the optimal path and its convergence to the long-run equilibrium on a two-dimensional phase diagram. The phase diagram consists of a transient curve that reaches the classical curve associated with a positive exponential growth at the time the population reaches the critical level. In the case of an asymptotic population saturation, we expect the transient curve to approach the equilibrium as the population approaches its saturation level. Finally, we characterize the approaches to the classical curve and to the equilibrium. PMID:17984059

On the Water-Food Nexus: an Optimization Approach for Water and Food Security

NASA Astrophysics Data System (ADS)

Mortada, Sarah; Abou Najm, Majdi; Yassine, Ali; Alameddine, Ibrahim; El-Fadel, Mutasem

2016-04-01

Water and food security is facing increased challenges with population increase, climate and land use change, as well as resource depletion coupled with pollution and unsustainable practices. Coordinated and effective management of limited natural resources have become an imperative to meet these challenges by optimizing the usage of resources under various constraints. In this study, an optimization model is developed for optimal resource allocation towards sustainable water and food security under nutritional, socio-economic, agricultural, environmental, and natural resources constraints. The core objective of this model is to maximize the composite water-food security status by recommending an optimal water and agricultural strategy. The model balances between the healthy nutritional demand side and the constrained supply side while considering the supply chain in between. It equally ensures that the population achieves recommended nutritional guidelines and population food-preferences by quantifying an optimum agricultural and water policy through transforming optimum food demands into optimum cropping policy given the water and land footprints of each crop or agricultural product. Through this process, water and food security are optimized considering factors that include crop-food transformation (food processing), water footprints, crop yields, climate, blue and green water resources, irrigation efficiency, arable land resources, soil texture, and economic policies. The model performance regarding agricultural practices and sustainable food and water security was successfully tested and verified both at a hypothetical and pilot scale levels.

Abdomen disease diagnosis in CT images using flexiscale curvelet transform and improved genetic algorithm.

PubMed

Sethi, Gaurav; Saini, B S

2015-12-01

This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.

Relationships of maternal body size and morphology with egg and clutch size in the diamondback terrapin, Malaclemys terrapin (Testudines: Emydidae)

USGS Publications Warehouse

Kern, Maximilian M.; Guzy, Jacquelyn C.; Lovich, Jeffrey E.; Gibbons, J. Whitfield; Dorcas, Michael E.

2016-01-01

Because resources are finite, female animals face trade-offs between the size and number of offspring they are able to produce during a single reproductive event. Optimal egg size (OES) theory predicts that any increase in resources allocated to reproduction should increase clutch size with minimal effects on egg size. Variations of OES predict that egg size should be optimized, although not necessarily constant across a population, because optimality is contingent on maternal phenotypes, such as body size and morphology, and recent environmental conditions. We examined the relationships among body size variables (pelvic aperture width, caudal gap height, and plastron length), clutch size, and egg width of diamondback terrapins from separate but proximate populations at Kiawah Island and Edisto Island, South Carolina. We found that terrapins do not meet some of the predictions of OES theory. Both populations exhibited greater variation in egg size among clutches than within, suggesting an absence of optimization except as it may relate to phenotype/habitat matching. We found that egg size appeared to be constrained by more than just pelvic aperture width in Kiawah terrapins but not in the Edisto population. Terrapins at Edisto appeared to exhibit osteokinesis in the caudal region of their shells, which may aid in the oviposition of large eggs.

Association of carbohydrate and fat intake with metabolic syndrome.

PubMed

Kwon, Yu-Jin; Lee, Hye-Sun; Lee, Ji-Won

2018-04-01

In Asia, dietary pattern has been changed with increased intake of refined carbohydrates, sugar, and saturated fat, while the prevalence of metabolic syndrome (MetS) is on the rise. However, it remains unclear whether a high-carbohydrate or a high-fat diet is more metabolically harmful, and the optimal amount of carbohydrates and fat has not been determined. The aim of our study was to examine the role of carbohydrate and fat intake in MetS in a Korean population. Data were obtained from a large, population-based, cross-sectional study (6737 males and 8845 females). The subjects were divided into nine groups based on carbohydrate and fat proportion, and multiple logistic regression analysis was performed after adjusting for confounding variables. Regardless of fat intake, the risk of MetS significantly increased in males with higher carbohydrate proportions (of total energy intake). In females, the risk of MetS was significantly elevated only in those with both the highest carbohydrate proportion and lowest fat proportion. A high carbohydrate proportion was associated with a higher prevalence of MetS in males, and a high carbohydrate proportion combined with a low fat proportion was associated with MetS in females. Our results indicate that reduction of excessive carbohydrate intake paired with an adequate fat intake, taking into consideration optimal types of fat, is useful for MetS prevention. Longitudinal studies are needed to clarify the optimal types and amounts of carbohydrate and fat proportions as well as the mechanism underlying these relationships. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Desynchronization boost by non-uniform coordinated reset stimulation in ensembles of pulse-coupled neurons

PubMed Central

Lücken, Leonhard; Yanchuk, Serhiy; Popovych, Oleksandr V.; Tass, Peter A.

2013-01-01

Several brain diseases are characterized by abnormal neuronal synchronization. Desynchronization of abnormal neural synchrony is theoretically compelling because of the complex dynamical mechanisms involved. We here present a novel type of coordinated reset (CR) stimulation. CR means to deliver phase resetting stimuli at different neuronal sub-populations sequentially, i.e., at times equidistantly distributed in a stimulation cycle. This uniform timing pattern seems to be intuitive and actually applies to the neural network models used for the study of CR so far. CR resets the population to an unstable cluster state from where it passes through a desynchronized transient, eventually resynchronizing if left unperturbed. In contrast, we show that the optimal stimulation times are non-uniform. Using the model of weakly pulse-coupled neurons with phase response curves, we provide an approach that enables to determine optimal stimulation timing patterns that substantially maximize the desynchronized transient time following the application of CR stimulation. This approach includes an optimization search for clusters in a low-dimensional pulse coupled map. As a consequence, model-specific non-uniformly spaced cluster states cause considerably longer desynchronization transients. Intriguingly, such a desynchronization boost with non-uniform CR stimulation can already be achieved by only slight modifications of the uniform CR timing pattern. Our results suggest that the non-uniformness of the stimulation times can be a medically valuable parameter in the calibration procedure for CR stimulation, where the latter has successfully been used in clinical and pre-clinical studies for the treatment of Parkinson's disease and tinnitus. PMID:23750134

Vitamin D deficiency at birth among military dependants in Hawai'i.

PubMed

Palmer, Eldon G; Ramirez-Enriquez, Emmanuel; Frioux, Sarah M; Tyree, Melissa M

2013-03-01

Vitamin D has long been known to be essential in bone mineralization as well as calcium and phosphate regulation. An increasing body of literature suggests that Vitamin D is also key in many other areas to include immune function, brain development, prevention of autoimmune disease, and prevention of certain types of cancers. Studies also suggest that, with decreased sun exposure due to concern for skin cancer risk, much of the world's population is becoming increasingly deficient in vitamin D. Our hypothesis was that vitamin D deficiency exists, and can be detected, even in sunny climates such as the state of Hawai'i. To test this hypothesis, eighty-six cord blood samples were collected in the process of routine clinical testing. These samples were tested for 25-hydroxy vitamin D via liquid chromatography mass spectroscopy. Percent deficiency (<20ng/mL) and insufficiency (20-31.9ng/mL) were determined by statistical analysis. Forty-six percent (n=37) of cord blood samples tested were deficient in vitamin D; 47 percent (n=38) of samples had insufficient 25-OH vitamin D. Only 7 percent (n=6) of samples showed vitamin D concentrations at the recommended levels. A vast majority of military dependents in Hawai'i have less than optimal vitamin D levels at birth. Further investigation of vitamin D supplementation during pregnancy is required to optimize vitamin D status at birth. We conclude that a vast majority of military dependents in Hawai'i have less than optimal vitamin D levels at birth supporting the recommendation for supplementation in this population.

Climatic niche and flowering and fruiting phenology of an epiphytic plant

PubMed Central

Barve, Narayani; Martin, Craig E.; Peterson, A. Townsend

2015-01-01

Species have geographic distributions constrained by combinations of abiotic factors, biotic factors and dispersal-related factors. Abiotic requirements vary across the life stages for a species; for plant species, a particularly important life stage is when the plant flowers and develops seeds. A previous year-long experiment showed that ambient temperature of 5–35 °C, relative humidity of >50 % and ≤15 consecutive rainless days are crucial abiotic conditions for Spanish moss (Tillandsia usneoides L.). Here, we explore whether these optimal physiological intervals relate to the timing of the flowering and fruiting periods of Spanish moss across its range. As Spanish moss has a broad geographic range, we examined herbarium specimens to detect and characterize flowering/fruiting periods for the species across the Americas; we used high-temporal-resolution climatic data to assess the availability of optimal conditions for Spanish moss populations during each population's flowering period. We explored how long populations experience suboptimal conditions and found that most populations experience suboptimal conditions in at least one environmental dimension. Flowering and fruiting periods of Spanish moss populations are either being optimized for one or a few parameters or may be adjusted such that all parameters are suboptimal. Spanish moss populations appear to be constrained most closely by minimum temperature during this period. PMID:26359490

Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish

PubMed Central

Torrente-Vilara, Gislene; Quilodran, Claudio; Rodrigues da Costa Doria, Carolina; Montoya-Burgos, Juan I.

2017-01-01

Understanding the processes that drive population genetic divergence in the Amazon is challenging because of the vast scale, the environmental richness and the outstanding biodiversity of the region. We addressed this issue by determining the genetic structure of the widespread Amazonian common sardine fish Triportheus albus (Characidae). We then examined the influence, on this species, of all previously proposed population-structuring factors, including isolation-by-distance, isolation-by-barrier (the Teotônio Falls) and isolation-by-environment using variables that describe floodplain and water characteristics. The population genetics analyses revealed an unusually strong structure with three geographical groups: Negro/Tapajós rivers, Lower Madeira/Central Amazon, and Upper Madeira. Distance-based redundancy analyses showed that the optimal model for explaining the extreme genetic structure contains all proposed structuring factors and accounts for up to 70% of the genetic structure. We further quantified the contribution of each factor via a variance-partitioning analysis. Our results demonstrate that multiple factors, often proposed as individual drivers of population divergence, have acted in conjunction to divide T. albus into three genetic lineages. Because the conjunction of multiple long-standing population-structuring processes may lead to population reproductive isolation, that is, the onset of speciation, we suggest that the multifactorial population-structuring processes highlighted in this study could account for the high speciation rate characterising the Amazon Basin. PMID:29261722

Body mass index, waist circumference and waist-to-hip ratio cut-off points for categorisation of obesity among Omani Arabs.

PubMed

Al-Lawati, Jawad A; Jousilahti, Pekka

2008-01-01

There are no data on optimal cut-off points to classify obesity among Omani Arabs. The existing cut-off points were obtained from studies of European populations. To determine gender-specific optimal cut-off points for body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) associated with elevated prevalent cardiovascular disease (CVD) risk among Omani Arabs. A community-based cross-sectional study. The survey was conducted in the city of Nizwa in Oman in 2001. The study contained a probabilistic random sample of 1421 adults aged > or =20 years. Prevalent CVD risk was defined as the presence of at least two of the following three risk factors: hyperglycaemia, hypertension and dyslipidaemia. Logistic regression and receiver-operating characteristic (ROC) curve analyses were used to determine optimal cut-off points for BMI, WC and WHR in relation to the area under the curve (AUC), sensitivity and specificity. Over 87% of Omanis had at least one CVD risk factor (38% had hyperglycaemia, 19% hypertension and 34.5% had high total cholesterol). All three indices including BMI (AUC = 0.766), WC (AUC = 0.772) and WHR (AUC = 0.767) predicted prevalent CVD risk factors equally well. The optimal cut-off points for men and women respectively were 23.2 and 26.8 kg m-2 for BMI, 80.0 and 84.5 cm for WC, and 0.91 and 0.91 for WHR. To identify Omani subjects of Arab ethnicity at high risk of CVD, cut-off points lower than currently recommended for BMI, WC and WHR are needed for men while higher cut-off points are suggested for women.

Relationship between heart rate and quiescent interval of the cardiac cycle in children using MRI.

PubMed

Zhang, Wei; Bogale, Saivivek; Golriz, Farahnaz; Krishnamurthy, Rajesh

2017-11-01

Imaging the heart in children comes with the challenge of constant cardiac motion. A prospective electrocardiography-triggered CT scan allows for scanning during a predetermined phase of the cardiac cycle with least motion. This technique requires knowing the optimal quiescent intervals of cardiac cycles in a pediatric population. To evaluate high-temporal-resolution cine MRI of the heart in children to determine the relationship of heart rate to the optimal quiescent interval within the cardiac cycle. We included a total of 225 consecutive patients ages 0-18 years who had high-temporal-resolution cine steady-state free-precession sequence performed as part of a magnetic resonance imaging (MRI) or magnetic resonance angiography study of the heart. We determined the location and duration of the quiescent interval in systole and diastole for heart rates ranging 40-178 beats per minute (bpm). We performed the Wilcoxon signed rank test to compare the duration of quiescent interval in systole and diastole for each heart rate group. The duration of the quiescent interval at heart rates <80 bpm and >90 bpm was significantly longer in diastole and systole, respectively (P<.0001 for all ranges, except for 90-99 bpm [P=.02]). For heart rates 80-89 bpm, diastolic interval was longer than systolic interval, but the difference was not statistically significant (P=.06). We created a chart depicting optimal quiescent intervals across a range of heart rates that could be applied for prospective electrocardiography-triggered CT imaging of the heart. The optimal quiescent interval at heart rates <80 bpm is in diastole and at heart rates ≥90 bpm is in systole. The period of quiescence at heart rates 80-89 bpm is uniformly short in systole and diastole.

Applying Central Composite Design and Response Surface Methodology to Optimize Growth and Biomass Production of Haemophilus influenzae Type b.

PubMed

Momen, Seyed Bahman; Siadat, Seyed Davar; Akbari, Neda; Ranjbar, Bijan; Khajeh, Khosro

2016-06-01

Haemophilus influenzae type b (Hib) is the leading cause of bacterial meningitis, otitis media, pneumonia, cellulitis, bacteremia, and septic arthritis in infants and young children. The Hib capsule contains the major virulence factor, and is composed of polyribosyl ribitol phosphate (PRP) that can induce immune system response. Vaccines consisting of Hib capsular polysaccharide (PRP) conjugated to a carrier protein are effective in the prevention of the infections. However, due to costly processes in PRP production, these vaccines are too expensive. To enhance biomass, in this research we focused on optimizing Hib growth with respect to physical factors such as pH, temperature, and agitation by using a response surface methodology (RSM). We employed a central composite design (CCD) and a response surface methodology to determine the optimum cultivation conditions for growth and biomass production of H. influenzae type b. The treatment factors investigated were initial pH, agitation, and temperature, using shaking flasks. After Hib cultivation and determination of dry biomass, analysis of experimental data was performed by the RSM-CCD. The model showed that temperature and pH had an interactive effect on Hib biomass production. The dry biomass produced in shaking flasks was about 5470 mg/L, which was under an initial pH of 8.5, at 250 rpm and 35° C. We found CCD and RSM very effective in optimizing Hib culture conditions, and Hib biomass production was greatly influenced by pH and incubation temperature. Therefore, optimization of the growth factors to maximize Hib production can lead to 1) an increase in bacterial biomass and PRP productions, 2) lower vaccine prices, 3) vaccination of more susceptible populations, and 4) lower risk of Hib infections.

Local adaptation in migrated interior Douglas-fir seedlings is mediated by ectomycorrhizas and other soil factors.

PubMed

Pickles, Brian J; Twieg, Brendan D; O'Neill, Gregory A; Mohn, William W; Simard, Suzanne W

2015-08-01

Separating edaphic impacts on tree distributions from those of climate and geography is notoriously difficult. Aboveground and belowground factors play important roles, and determining their relative contribution to tree success will greatly assist in refining predictive models and forestry strategies in a changing climate. In a common glasshouse, seedlings of interior Douglas-fir (Pseudotsuga menziesii var. glauca) from multiple populations were grown in multiple forest soils. Fungicide was applied to half of the seedlings to separate soil fungal and nonfungal impacts on seedling performance. Soils of varying geographic and climatic distance from seed origin were compared, using a transfer function approach. Seedling height and biomass were optimized following seed transfer into drier soils, whereas survival was optimized when elevation transfer was minimised. Fungicide application reduced ectomycorrhizal root colonization by c. 50%, with treated seedlings exhibiting greater survival but reduced biomass. Local adaptation of Douglas-fir populations to soils was mediated by soil fungi to some extent in 56% of soil origin by response variable combinations. Mediation by edaphic factors in general occurred in 81% of combinations. Soil biota, hitherto unaccounted for in climate models, interacts with biogeography to influence plant ranges in a changing climate. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Life satisfaction in adult survivors of childhood brain tumors.

PubMed

Crom, Deborah B; Li, Zhenghong; Brinkman, Tara M; Hudson, Melissa M; Armstrong, Gregory T; Neglia, Joseph; Ness, Kirsten K

2014-01-01

Adult survivors of childhood brain tumors experience multiple, significant, lifelong deficits as a consequence of their malignancy and therapy. Current survivorship literature documents the substantial impact such impairments have on survivors' physical health and quality of life. Psychosocial reports detail educational, cognitive, and emotional limitations characterizing survivors as especially fragile, often incompetent, and unreliable in evaluating their circumstances. Anecdotal data suggest some survivors report life experiences similar to those of healthy controls. The aim of our investigation was to determine whether life satisfaction in adult survivors of childhood brain tumors differs from that of healthy controls and to identify potential predictors of life satisfaction in survivors. This cross-sectional study compared 78 brain tumor survivors with population-based matched controls. Chi-square tests, t tests, and linear regression models were used to investigate patterns of life satisfaction and identify potential correlates. Results indicated that life satisfaction of adult survivors of childhood brain tumors was similar to that of healthy controls. Survivors' general health expectations emerged as the primary correlate of life satisfaction. Understanding life satisfaction as an important variable will optimize the design of strategies to enhance participation in follow-up care, reduce suffering, and optimize quality of life in this vulnerable population. © 2014 by Association of Pediatric Hematology/Oncology Nurses.

A Health Services Research Agenda for Bariatric Surgery Within the Veterans Health Administration.

PubMed

Funk, L M; Gunnar, W; Dominitz, J A; Eisenberg, D; Frayne, S; Maggard-Gibbons, M; Kalarchian, M A; Livingston, E; Sanchez, V; Smith, B R; Weidenbacher, H; Maciejewski, Matthew L

2017-04-01

In 2016, the Veterans Health Administration (VHA) held a Weight Management State of the Art conference to identify evidence gaps and develop a research agenda for population-based weight management for veterans. Included were behavioral, pharmacologic, and bariatric surgery workgroups. This article summarizes the bariatric surgery workgroup (BSWG) findings and recommendations for future research. The BSWG agreed that there is evidence from randomized trials and large observational studies suggesting that bariatric surgery is superior to medical therapy for short- and intermediate-term remission of type 2 diabetes, long-term weight loss, and long-term survival. Priority evidence gaps include long-term comorbidity remission, mental health, substance abuse, and health care costs. Evidence of the role of endoscopic weight loss options is also lacking. The BSWG also noted the limited evidence regarding optimal timing for bariatric surgery referral, barriers to bariatric surgery itself, and management of high-risk bariatric surgery patients. Clinical trials of pre- and post-surgery interventions may help to optimize patient outcomes. A registry of overweight and obese veterans and a workforce assessment to determine the VHA's capacity to increase bariatric surgery access were recommended. These will help inform policy modifications and focus the research agenda to improve the ability of the VHA to deliver population-based weight management.

High-sensitivity detection of cardiac troponin I with UV LED excitation for use in point-of-care immunoassay.

PubMed

Rodenko, Olga; Eriksson, Susann; Tidemand-Lichtenberg, Peter; Troldborg, Carl Peder; Fodgaard, Henrik; van Os, Sylvana; Pedersen, Christian

2017-08-01

High-sensitivity cardiac troponin assay development enables determination of biological variation in healthy populations, more accurate interpretation of clinical results and points towards earlier diagnosis and rule-out of acute myocardial infarction. In this paper, we report on preliminary tests of an immunoassay analyzer employing an optimized LED excitation to measure on a standard troponin I and a novel research high-sensitivity troponin I assay. The limit of detection is improved by factor of 5 for standard troponin I and by factor of 3 for a research high-sensitivity troponin I assay, compared to the flash lamp excitation. The obtained limit of detection was 0.22 ng/L measured on plasma with the research high-sensitivity troponin I assay and 1.9 ng/L measured on tris-saline-azide buffer containing bovine serum albumin with the standard troponin I assay. We discuss the optimization of time-resolved detection of lanthanide fluorescence based on the time constants of the system and analyze the background and noise sources in a heterogeneous fluoroimmunoassay. We determine the limiting factors and their impact on the measurement performance. The suggested model can be generally applied to fluoroimmunoassays employing the dry-cup concept.

[Stimulation parameters for automatic examination of color vision].

PubMed

Sommerhalder, J; Pelizzone, M; Roth, A

1997-05-01

We have developed a polyvalent computer controlled instrument, which uses the "two equation method" (Rayleigh and Moreland equations) to measure human colour vision. This "colorimeter" (or anomaloscope) was used to determine the influence of some important stimulation parameters. The influence of stimulus exposure time, observation field size, absolute stimulus luminance, saturation and luminance mismatches between mixture and reference stimuli were measured on our computer controlled colorimeter. All subjects were normal observers. 1) An exposure time of 2s was found to be optimal for clinical work. 2) The Moreland equation on a 7 degrees observation field yields results in which population variability is comparable to a Rayleigh equation on a 2 degrees field. 3) A retinal illuminance between 40 and 1000 trolands can be used for automated Moreland matches. 4) The saturation of the reference field for the Moreland match can be preset to a fixed value. 5) It is important to vary automatically the radiance of the reference field to provide an approximate luminance match as the ratio of primaries in the mixture field is changed. These measurements allows us to determine optimal conditions for automated colour vision examinations and to make recommendations for an international standard.

Exploring Relationships between Canopy Architecture, Light Distribution, and Photosynthesis in Contrasting Rice Genotypes Using 3D Canopy Reconstruction

PubMed Central

Burgess, Alexandra J.; Retkute, Renata; Herman, Tiara; Murchie, Erik H.

2017-01-01

The arrangement of leaf material is critical in determining the light environment, and subsequently the photosynthetic productivity of complex crop canopies. However, links between specific canopy architectural traits and photosynthetic productivity across a wide genetic background are poorly understood for field grown crops. The architecture of five genetically diverse rice varieties—four parental founders of a multi-parent advanced generation intercross (MAGIC) population plus a high yielding Philippine variety (IR64)—was captured at two different growth stages using a method for digital plant reconstruction based on stereocameras. Ray tracing was employed to explore the effects of canopy architecture on the resulting light environment in high-resolution, whilst gas exchange measurements were combined with an empirical model of photosynthesis to calculate an estimated carbon gain and total light interception. To further test the impact of different dynamic light patterns on photosynthetic properties, an empirical model of photosynthetic acclimation was employed to predict the optimal light-saturated photosynthesis rate (Pmax) throughout canopy depth, hypothesizing that light is the sole determinant of productivity in these conditions. First, we show that a plant type with steeper leaf angles allows more efficient penetration of light into lower canopy layers and this, in turn, leads to a greater photosynthetic potential. Second the predicted optimal Pmax responds in a manner that is consistent with fractional interception and leaf area index across this germplasm. However, measured Pmax, especially in lower layers, was consistently higher than the optimal Pmax indicating factors other than light determine photosynthesis profiles. Lastly, varieties with more upright architecture exhibit higher maximum quantum yield of photosynthesis indicating a canopy-level impact on photosynthetic efficiency. PMID:28567045

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Comparing a Coevolutionary Genetic Algorithm for Multiobjective Optimization

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Kraus, William F.; Haith, Gary L.; Clancy, Daniel (Technical Monitor)

2002-01-01

We present results from a study comparing a recently developed coevolutionary genetic algorithm (CGA) against a set of evolutionary algorithms using a suite of multiobjective optimization benchmarks. The CGA embodies competitive coevolution and employs a simple, straightforward target population representation and fitness calculation based on developmental theory of learning. Because of these properties, setting up the additional population is trivial making implementation no more difficult than using a standard GA. Empirical results using a suite of two-objective test functions indicate that this CGA performs well at finding solutions on convex, nonconvex, discrete, and deceptive Pareto-optimal fronts, while giving respectable results on a nonuniform optimization. On a multimodal Pareto front, the CGA finds a solution that dominates solutions produced by eight other algorithms, yet the CGA has poor coverage across the Pareto front.

Improving the Distribution of Rural Health Houses Using Elicitation and GIS in Khuzestan Province (the Southwest of Iran).

PubMed

Mohammadi, Ali; Valinejadi, Ali; Sakipour, Sara; Hemmat, Morteza; Zarei, Javad; Askari Majdabadi, Hesamedin

2017-08-27

Rural health houses constitute a major provider of some primary health services in the villages of Iran. Given the challenges of providing health services in rural areas, health houses should be established based on the criteria of health network systems (HNSs). The value of these criteria and their precedence over others have not yet been thoroughly investigated. The present study was conducted to propose a model for improving the distribution of rural health houses in HNSs. The present applied study was conducted in Khuzestan province in the southwest of Iran in 2014-2016. First, the descriptive and spatial data required were collected and entered into ArcGIS after modifications, and the Geodatabase was then created. Based on the criteria of the HNS and according to experts' opinions, the main criteria and the sub-criteria for an optimal site selection were determined. To determine the criteria's coefficient of importance (ie, their weight), the main criteria and the sub-criteria were compared in pairs according to experts' opinions. The results of the pairwise comparisons were entered into Expert Choice and the weight of the main criteria and the sub-criteria were determined using the analytic hierarchy process (AHP). The application layers were then formed in geographic information system (GIS). A model was ultimately proposed in the GIS for the optimal distribution of rural health houses by overlaying the weighting layers and the other layers related to villages and rural health houses. Based on the experts' opinions, six criteria were determined as the main criteria for an optimal site selection for rural health houses, including welfare infrastructures, population, dispersion, accessibility, corresponding routes, distance to the rural health center and the absence of natural barriers to accessibility. Of the main criteria proposed, the highest weight was given to "population" (0.506). The priorities suggested in the proposed model for establishing rural health houses are presented within five zoning levels -from excellent to very poor. The results of the study showed that the proposed model can help provide a better picture of the distribution of rural health houses. The GIS is recommended to be used as a means of making the HNS more efficient. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Vitamin D deficiency is common among adults in Wallonia (Belgium, 51°30' North): findings from the Nutrition, Environment and Cardio-Vascular Health study.

PubMed

Hoge, Axelle; Donneau, Anne-Françoise; Streel, Sylvie; Kolh, Philippe; Chapelle, Jean-Paul; Albert, Adelin; Cavalier, Etienne; Guillaume, Michèle

2015-08-01

Data on the vitamin D status of the population of Wallonia (Belgium, 51°30' North) are scarce. This study was carried out to estimate vitamin D deficiency, identify potential determinants, and analyze their relationship with vitamin D supplementation. We tested the hypothesis that vitamin D deficiency is common in the general population, particularly among subjects without supplementation. Vitamin D deficiency was defined as a serum level of 25-hydroxyvitamin D (25(OH)D) concentration less than 50nmol/L. Data were analyzed from 915 participants of the Nutrition, Environment and Cardio-Vascular Health cross-sectional survey. The median (interquartile range) 25(OH)D level was 53.1 (37.8-69.9) nmol/L, and 44.7% of the subjects were vitamin D deficient. Subjects without vitamin D supplementation were more concerned by vitamin D deficiency than those with supplementation (odds ratio [OR], 3.35; P < .0001). From a multivariate standpoint, the potential determinants of vitamin D deficiency among subjects without vitamin D supplementation were season, specifically spring and winter (OR, 7.36 and 6.44, respectively), obesity (OR, 2.19), low household income (OR, 1.73), and lack of solarium use (OR, 1.79). For subjects with supplementation, the only determinant observed for vitamin D deficiency was obesity (OR, 5.00). This work evidenced the high prevalence of 25(OH)D deficiency in the general population, especially among nonsupplemented subjects with obesity, low household income, and/or lack of light. Vitamin D supplementation looks effective in our population, especially via a stabilization of vitamin D coverage throughout the seasons. The best dietary strategy to achieve optimal 25(OH)D concentrations all year round in the general population requires more research. Copyright © 2015 Elsevier Inc. All rights reserved.

Design of a digital phantom population for myocardial perfusion SPECT imaging research.

PubMed

Ghaly, Michael; Du, Yong; Fung, George S K; Tsui, Benjamin M W; Links, Jonathan M; Frey, Eric

2014-06-21

Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.

Design of a digital phantom population for myocardial perfusion SPECT imaging research

NASA Astrophysics Data System (ADS)

Ghaly, Michael; Du, Yong; Fung, George S. K.; Tsui, Benjamin M. W.; Links, Jonathan M.; Frey, Eric

2014-06-01

Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.

Cyclic public goods games: Compensated coexistence among mutual cheaters stabilized by optimized penalty taxation

NASA Astrophysics Data System (ADS)

Griffin, Christopher; Belmonte, Andrew

2017-05-01

We study the problem of stabilized coexistence in a three-species public goods game in which each species simultaneously contributes to one public good while freeloading off another public good ("cheating"). The proportional population growth is governed by an appropriately modified replicator equation, depending on the returns from the public goods and the cost. We show that the replicator dynamic has at most one interior unstable fixed point and that the population becomes dominated by a single species. We then show that by applying an externally imposed penalty, or "tax" on success can stabilize the interior fixed point, allowing for the symbiotic coexistence of all species. We show that the interior fixed point is the point of globally minimal total population growth in both the taxed and untaxed cases. We then formulate an optimal taxation problem and show that it admits a quasilinearization, resulting in novel necessary conditions for the optimal control. In particular, the optimal control problem governing the tax rate must solve a certain second-order ordinary differential equation.

On the Improvement of Convergence Performance for Integrated Design of Wind Turbine Blade Using a Vector Dominating Multi-objective Evolution Algorithm

NASA Astrophysics Data System (ADS)

Wang, L.; Wang, T. G.; Wu, J. H.; Cheng, G. P.

2016-09-01

A novel multi-objective optimization algorithm incorporating evolution strategies and vector mechanisms, referred as VD-MOEA, is proposed and applied in aerodynamic- structural integrated design of wind turbine blade. In the algorithm, a set of uniformly distributed vectors is constructed to guide population in moving forward to the Pareto front rapidly and maintain population diversity with high efficiency. For example, two- and three- objective designs of 1.5MW wind turbine blade are subsequently carried out for the optimization objectives of maximum annual energy production, minimum blade mass, and minimum extreme root thrust. The results show that the Pareto optimal solutions can be obtained in one single simulation run and uniformly distributed in the objective space, maximally maintaining the population diversity. In comparison to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation for handling complex problems of multi-variables, multi-objectives and multi-constraints. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrated design of wind turbine blade.

Cyclic public goods games: Compensated coexistence among mutual cheaters stabilized by optimized penalty taxation.

PubMed

Griffin, Christopher; Belmonte, Andrew

2017-05-01

We study the problem of stabilized coexistence in a three-species public goods game in which each species simultaneously contributes to one public good while freeloading off another public good ("cheating"). The proportional population growth is governed by an appropriately modified replicator equation, depending on the returns from the public goods and the cost. We show that the replicator dynamic has at most one interior unstable fixed point and that the population becomes dominated by a single species. We then show that by applying an externally imposed penalty, or "tax" on success can stabilize the interior fixed point, allowing for the symbiotic coexistence of all species. We show that the interior fixed point is the point of globally minimal total population growth in both the taxed and untaxed cases. We then formulate an optimal taxation problem and show that it admits a quasilinearization, resulting in novel necessary conditions for the optimal control. In particular, the optimal control problem governing the tax rate must solve a certain second-order ordinary differential equation.

A Grouping Particle Swarm Optimizer with Personal-Best-Position Guidance for Large Scale Optimization.

PubMed

Guo, Weian; Si, Chengyong; Xue, Yu; Mao, Yanfen; Wang, Lei; Wu, Qidi

2017-05-04

Particle Swarm Optimization (PSO) is a popular algorithm which is widely investigated and well implemented in many areas. However, the canonical PSO does not perform well in population diversity maintenance so that usually leads to a premature convergence or local optima. To address this issue, we propose a variant of PSO named Grouping PSO with Personal- Best-Position (Pbest) Guidance (GPSO-PG) which maintains the population diversity by preserving the diversity of exemplars. On one hand, we adopt uniform random allocation strategy to assign particles into different groups and in each group the losers will learn from the winner. On the other hand, we employ personal historical best position of each particle in social learning rather than the current global best particle. In this way, the exemplars diversity increases and the effect from the global best particle is eliminated. We test the proposed algorithm to the benchmarks in CEC 2008 and CEC 2010, which concern the large scale optimization problems (LSOPs). By comparing several current peer algorithms, GPSO-PG exhibits a competitive performance to maintain population diversity and obtains a satisfactory performance to the problems.

Heuristic query optimization for query multiple table and multiple clausa on mobile finance application

NASA Astrophysics Data System (ADS)

Indrayana, I. N. E.; P, N. M. Wirasyanti D.; Sudiartha, I. KG

2018-01-01

Mobile application allow many users to access data from the application without being limited to space, space and time. Over time the data population of this application will increase. Data access time will cause problems if the data record has reached tens of thousands to millions of records.The objective of this research is to maintain the performance of data execution for large data records. One effort to maintain data access time performance is to apply query optimization method. The optimization used in this research is query heuristic optimization method. The built application is a mobile-based financial application using MySQL database with stored procedure therein. This application is used by more than one business entity in one database, thus enabling rapid data growth. In this stored procedure there is an optimized query using heuristic method. Query optimization is performed on a “Select” query that involves more than one table with multiple clausa. Evaluation is done by calculating the average access time using optimized and unoptimized queries. Access time calculation is also performed on the increase of population data in the database. The evaluation results shown the time of data execution with query heuristic optimization relatively faster than data execution time without using query optimization.

When to stop managing or surveying cryptic threatened species

PubMed Central

Chadès, Iadine; McDonald-Madden, Eve; McCarthy, Michael A.; Wintle, Brendan; Linkie, Matthew; Possingham, Hugh P.

2008-01-01

Threatened species become increasingly difficult to detect as their populations decline. Managers of such cryptic threatened species face several dilemmas: if they are not sure the species is present, should they continue to manage for that species or invest the limited resources in surveying? We find optimal solutions to this problem using a Partially Observable Markov Decision Process and rules of thumb derived from an analytical approximation. We discover that managing a protected area for a cryptic threatened species can be optimal even if we are not sure the species is present. The more threatened and valuable the species is, relative to the costs of management, the more likely we are to manage this species without determining its continued persistence by using surveys. If a species remains unseen, our belief in the persistence of the species declines to a point where the optimal strategy is to shift resources from saving the species to surveying for it. Finally, when surveys lead to a sufficiently low belief that the species is extant, we surrender resources to other conservation actions. We illustrate our findings with a case study using parameters based on the critically endangered Sumatran tiger (Panthera tigris sumatrae), and we generate rules of thumb on how to allocate conservation effort for any cryptic species. Using Partially Observable Markov Decision Processes in conservation science, we determine the conditions under which it is better to abandon management for that species because our belief that it continues to exist is too low. PMID:18779594

Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis

PubMed Central

Meng, Xiang; Firczuk, Helena; Pietroni, Paola; Westbrook, Richard; Dacheux, Estelle; Mendes, Pedro; McCarthy, John E.G.

2017-01-01

Gene expression noise influences organism evolution and fitness. The mechanisms determining the relationship between stochasticity and the functional role of translation machinery components are critical to viability. eIF4G is an essential translation factor that exerts strong control over protein synthesis. We observe an asymmetric, approximately bell-shaped, relationship between the average intracellular abundance of eIF4G and rates of cell population growth and global mRNA translation, with peak rates occurring at normal physiological abundance. This relationship fits a computational model in which eIF4G is at the core of a multi-component–complex assembly pathway. This model also correctly predicts a plateau-like response of translation to super-physiological increases in abundance of the other cap-complex factors, eIF4E and eIF4A. Engineered changes in eIF4G abundance amplify noise, demonstrating that minimum stochasticity coincides with physiological abundance of this factor. Noise is not increased when eIF4E is overproduced. Plasmid-mediated synthesis of eIF4G imposes increased global gene expression stochasticity and reduced viability because the intrinsic noise for this factor influences total cellular gene noise. The naturally evolved eIF4G gene expression noise minimum maps within the optimal activity zone dictated by eIF4G's mechanistic role. Rate control and noise are therefore interdependent and have co-evolved to share an optimal physiological abundance point. PMID:27928055

When to stop managing or surveying cryptic threatened species.

PubMed

Chadès, Iadine; McDonald-Madden, Eve; McCarthy, Michael A; Wintle, Brendan; Linkie, Matthew; Possingham, Hugh P

2008-09-16

Threatened species become increasingly difficult to detect as their populations decline. Managers of such cryptic threatened species face several dilemmas: if they are not sure the species is present, should they continue to manage for that species or invest the limited resources in surveying? We find optimal solutions to this problem using a Partially Observable Markov Decision Process and rules of thumb derived from an analytical approximation. We discover that managing a protected area for a cryptic threatened species can be optimal even if we are not sure the species is present. The more threatened and valuable the species is, relative to the costs of management, the more likely we are to manage this species without determining its continued persistence by using surveys. If a species remains unseen, our belief in the persistence of the species declines to a point where the optimal strategy is to shift resources from saving the species to surveying for it. Finally, when surveys lead to a sufficiently low belief that the species is extant, we surrender resources to other conservation actions. We illustrate our findings with a case study using parameters based on the critically endangered Sumatran tiger (Panthera tigris sumatrae), and we generate rules of thumb on how to allocate conservation effort for any cryptic species. Using Partially Observable Markov Decision Processes in conservation science, we determine the conditions under which it is better to abandon management for that species because our belief that it continues to exist is too low.

Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions.

PubMed

Howard, David M; Pong-Wong, Ricardo; Knap, Pieter W; Kremer, Valentin D; Woolliams, John A

2018-05-10

Optimal contributions selection (OCS) provides animal breeders with a framework for maximising genetic gain for a predefined rate of inbreeding. Simulation studies have indicated that the source of the selective advantage of OCS is derived from breeding decisions being more closely aligned with estimates of Mendelian sampling terms ([Formula: see text]) of selection candidates, rather than estimated breeding values (EBV). This study represents the first attempt to assess the source of the selective advantage provided by OCS using a commercial pig population and by testing three hypotheses: (1) OCS places more emphasis on [Formula: see text] compared to EBV for determining which animals were selected as parents, (2) OCS places more emphasis on [Formula: see text] compared to EBV for determining which of those parents were selected to make a long-term genetic contribution (r), and (3) OCS places more emphasis on [Formula: see text] compared to EBV for determining the magnitude of r. The population studied also provided an opportunity to investigate the convergence of r over time. Selection intensity limited the number of males available for analysis, but females provided some evidence that the selective advantage derived from applying an OCS algorithm resulted from greater weighting being placed on [Formula: see text] during the process of decision-making. Male r were found to converge initially at a faster rate than female r, with approximately 90% convergence achieved within seven generations across both sexes. This study of commercial data provides some support to results from theoretical and simulation studies that the source of selective advantage from OCS comes from [Formula: see text]. The implication that genomic selection (GS) improves estimation of [Formula: see text] should allow for even greater genetic gains for a predefined rate of inbreeding, once the synergistic benefits of combining OCS and GS are realised.

Criterion and Concurrent Validity of the activPAL™ Professional Physical Activity Monitor in Adolescent Females

PubMed Central

Dowd, Kieran P.; Harrington, Deirdre M.; Donnelly, Alan E.

2012-01-01

Background The activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer. Methodologies Thirty adolescent females (15 developmental; 15 cross-validation) aged 15–18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96, p<0.01) with the ActiGraph count function. Levels of agreement for sitting, standing, and stepping between direct observation and the activPAL and ActiGraph were 100%, 98.1%, 99.2% and 100%, 0%, 100%, respectively. Conclusions These findings suggest that the activPAL is a valid, objective measurement tool that can be used for both the measurement of physical activity and sedentary behaviours in an adolescent female population. PMID:23094069

Minimization of socioeconomic disruption for displaced populations following disasters.

PubMed

El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr

2010-07-01

In the aftermath of catastrophic natural disasters such as hurricanes, tsunamis and earthquakes, emergency management agencies come under intense pressure to provide temporary housing to address the large-scale displacement of the vulnerable population. Temporary housing is essential to enable displaced families to reestablish their normal daily activities until permanent housing solutions can be provided. Temporary housing decisions, however, have often been criticized for their failure to fulfil the socioeconomic needs of the displaced families within acceptable budgets. This paper presents the development of (1) socioeconomic disruption metrics that are capable of quantifying the socioeconomic impacts of temporary housing decisions on displaced populations; and (2) a robust multi-objective optimization model for temporary housing that is capable of simultaneously minimizing socioeconomic disruptions and public expenditures in an effective and efficient manner. A large-scale application example is optimized to illustrate the use of the model and demonstrate its capabilities ingenerating optimal plans for realistic temporary housing problems.

Determinants of psychology service utilization in a palliative care outpatient population.

PubMed

Azuero, Casey; Allen, Rebecca Sue; Kvale, Elizabeth; Azuero, Andres; Parmelee, Patricia

2014-06-01

Research has demonstrated that treating cancer patients' psychological and physical health leads to improved overall health. This may be especially true for palliative care patients facing serious illness. This study examines the proportion and determinants of psychology service utilization in an outpatient palliative care population. Data from an existing clinical database in an outpatient palliative clinic utilizing a collaborative care model to deliver psychology services were explored. This study was framed by Andersen's Behavioral Model of Health Service Use, which incorporates three main components: predisposing, enabling, and need factors to model health service utilization. The sample (N = 149) was majority middle aged, female, and White with a primary diagnosis of cancer. Cross-tabulations were conducted to determine how many patients who met screening criteria for depression or anxiety sought psychology services. Logistic regression analyses were conducted to assess for predisposing, enabling, and need factor determinants of psychology service utilization. Among patients who met criteria for moderate depression or anxiety, 50% did not access readily available psychology services. Enabling factors were the strongest determinant of psychology utilization. Factors associated with need for psychology services (i.e., emotional distress and psychological symptom burden) did not reach significance in determining psychology service use. This study extends current knowledge about psychology utilization to palliative care outpatients receiving care within a collaborative care model. Directions for future research include further investigation of care models that optimize enabling strategies to enhance access to these services, and examination of patient-reported barriers to receiving this care. Copyright © 2013 John Wiley & Sons, Ltd.

How Ebola impacts social dynamics in gorillas: a multistate modelling approach.

PubMed

Genton, Céline; Pierre, Amandine; Cristescu, Romane; Lévréro, Florence; Gatti, Sylvain; Pierre, Jean-Sébastien; Ménard, Nelly; Le Gouar, Pascaline

2015-01-01

Emerging infectious diseases can induce rapid changes in population dynamics and threaten population persistence. In socially structured populations, the transfers of individuals between social units, for example, from breeding groups to non-breeding groups, shape population dynamics. We suggest that diseases may affect these crucial transfers. We aimed to determine how disturbance by an emerging disease affects demographic rates of gorillas, especially transfer rates within populations and immigration rates into populations. We compared social dynamics and key demographic parameters in a gorilla population affected by Ebola using a long-term observation data set including pre-, during and post-outbreak periods. We also studied a population of undetermined epidemiological status in order to assess whether this population was affected by the disease. We developed a multistate model that can handle transition between social units while optimizing the number of states. During the Ebola outbreak, social dynamics displayed increased transfers from a breeding to a non-breeding status for both males and females. Six years after the outbreak, demographic and most of social dynamics parameters had returned to their initial rates, suggesting a certain resilience in the response to disruption. The formation of breeding groups increased just after Ebola, indicating that environmental conditions were still attractive. However, population recovery was likely delayed because compensatory immigration was probably impeded by the potential impact of Ebola in the surrounding areas. The population of undetermined epidemiological status behaved similarly to the other population before Ebola. Our results highlight the need to integrate social dynamics in host-population demographic models to better understand the role of social structure in the sensitivity and the response to disease disturbances. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Urban Forest Ecosystem Service Optimization, Tradeoffs, and Disparities

NASA Astrophysics Data System (ADS)

Bodnaruk, E.; Kroll, C. N.; Endreny, T. A.; Hirabayashi, S.; Yang, Y.

2014-12-01

Urban land area and the proportion of humanity living in cities is growing, leading to increased urban air pollution, temperature, and stormwater runoff. These changes can exacerbate respiratory and heat-related illnesses and affect ecosystem functioning. Urban trees can help mitigate these threats by removing air pollutants, mitigating urban heat island effects, and infiltrating and filtering stormwater. The urban environment is highly heterogeneous, and there is no tool to determine optimal locations to plant or protect trees. Using spatially explicit land cover, weather, and demographic data within biophysical ecosystem service models, this research expands upon the iTree urban forest tools to produce a new decision support tool (iTree-DST) that will explore the development and impacts of optimal tree planting. It will also heighten awareness of environmental justice by incorporating the Atkinson Index to quantify disparities in health risks and ecosystem services across vulnerable and susceptible populations. The study area is Baltimore City, a location whose urban forest and environmental justice concerns have been studied extensively. The iTree-DST is run at the US Census block group level and utilizes a local gradient approach to calculate the change in ecosystem services with changing tree cover across the study area. Empirical fits provide ecosystem service gradients for possible tree cover scenarios, greatly increasing the speed and efficiency of the optimization procedure. Initial results include an evaluation of the performance of the gradient method, optimal planting schemes for individual ecosystem services, and an analysis of tradeoffs and synergies between competing objectives.

Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

PubMed

Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

2018-01-01

For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Density-dependent selection on mate search and evolution of Allee effects.

PubMed

Berec, Luděk; Kramer, Andrew M; Bernhauerová, Veronika; Drake, John M

2018-01-01

Sexually reproducing organisms require males and females to find each other. Increased difficulty of females finding mates as male density declines is the most frequently reported mechanism of Allee effects in animals. Evolving more effective mate search may alleviate Allee effects, but may depend on density regimes a population experiences. In particular, high-density populations may evolve mechanisms that induce Allee effects which become detrimental when populations are reduced and maintained at a low density. We develop an individual-based, eco-genetic model to study how mating systems and fitness trade-offs interact with changes in population density to drive evolution of the rate at which males or females search for mates. Finite mate search rate triggers Allee effects in our model and we explore how these Allee effects respond to such evolution. We allow a population to adapt to several population density regimes and examine whether high-density populations are likely to reverse adaptations attained at low densities. We find density-dependent selection in most of scenarios, leading to search rates that result in lower Allee thresholds in populations kept at lower densities. This mainly occurs when fecundity costs are imposed on mate search, and provides an explanation for why Allee effects are often observed in anthropogenically rare species. Optimizing selection, where the attained trait value minimizes the Allee threshold independent of population density, depended on the trade-off between search and survival, combined with monogamy when females were searching. Other scenarios led to runaway selection on the mate search rate, including evolutionary suicide. Trade-offs involved in mate search may thus be crucial to determining how density influences the evolution of Allee effects. Previous studies did not examine evolution of a trait related to the strength of Allee effects under density variation. We emphasize the crucial role that mating systems, fitness trade-offs and the evolving sex have in determining the density threshold for population persistence, in particular since evolution need not always take the Allee threshold to its minimum value. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Cityscape genetics: structural vs. functional connectivity of an urban lizard population.

PubMed

Beninde, Joscha; Feldmeier, Stephan; Werner, Maike; Peroverde, Daniel; Schulte, Ulrich; Hochkirch, Axel; Veith, Michael

2016-10-01

Functional connectivity is essential for the long-term persistence of populations. However, many studies assess connectivity with a focus on structural connectivity only. Cityscapes, namely urban landscapes, are particularly dynamic and include numerous potential anthropogenic barriers to animal movements, such as roads, traffic or buildings. To assess and compare structural connectivity of habitats and functional connectivity of gene flow of an urban lizard, we here combined species distribution models (SDMs) with an individual-based landscape genetic optimization procedure. The most important environmental factors of the SDMs are structural diversity and substrate type, with high and medium levels of structural diversity as well as open and rocky/gravel substrates contributing most to structural connectivity. By contrast, water cover was the best model of all environmental factors following landscape genetic optimization. The river is thus a major barrier to gene flow, while of the typical anthropogenic factors only buildings showed an effect. Nonetheless, using SDMs as a basis for landscape genetic optimization provided the highest ranked model for functional connectivity. Optimizing SDMs in this way can provide a sound basis for models of gene flow of the cityscape, and elsewhere, while presence-only and presence-absence modelling approaches showed differences in performance. Additionally, interpretation of results based on SDM factor importance can be misleading, dictating more thorough analyses following optimization of SDMs. Such approaches can be adopted for management strategies, for example aiming to connect native common wall lizard populations or disconnect them from non-native introduced populations, which are currently spreading in many cities in Central Europe. © 2016 John Wiley & Sons Ltd.

Nurse Scheduling by Cooperative GA with Effective Mutation Operator

NASA Astrophysics Data System (ADS)

Ohki, Makoto

In this paper, we propose an effective mutation operators for Cooperative Genetic Algorithm (CGA) to be applied to a practical Nurse Scheduling Problem (NSP). The nurse scheduling is a very difficult task, because NSP is a complex combinatorial optimizing problem for which many requirements must be considered. In real hospitals, the schedule changes frequently. The changes of the shift schedule yields various problems, for example, a fall in the nursing level. We describe a technique of the reoptimization of the nurse schedule in response to a change. The conventional CGA is superior in ability for local search by means of its crossover operator, but often stagnates at the unfavorable situation because it is inferior to ability for global search. When the optimization stagnates for long generation cycle, a searching point, population in this case, would be caught in a wide local minimum area. To escape such local minimum area, small change in a population should be required. Based on such consideration, we propose a mutation operator activated depending on the optimization speed. When the optimization stagnates, in other words, when the optimization speed decreases, the mutation yields small changes in the population. Then the population is able to escape from a local minimum area by means of the mutation. However, this mutation operator requires two well-defined parameters. This means that user have to consider the value of these parameters carefully. To solve this problem, we propose a periodic mutation operator which has only one parameter to define itself. This simplified mutation operator is effective over a wide range of the parameter value.

Improvement in shelf life of minimally processed cilantro leaves through integration of kinetin pretreatment and packaging interventions: Studies on microbial population dynamics, biochemical characteristics and flavour retention.

PubMed

Ranjitha, K; Shivashankara, K S; Sudhakar Rao, D V; Oberoi, Harinder Singh; Roy, T K; Bharathamma, H

2017-04-15

Effect of integrating optimized combination of pretreatment with packaging on shelf life of minimally processed cilantro leaves (MPCL) was appraised through analysis of their sensory attributes, biochemical characteristics, microbial population and flavour profile during storage. Minimally pretreated cilantro leaves pretreated with 50ppm kinetin and packed in 25μ polypropylene bags showed a shelf life of 21days. Optimized combination helped in efficiently maintaining sensory parameters, flavour profile, and retention of antioxidants in MPCL until 21days. Studies conducted on the effect of optimized combination on microbial population and flavour profile revealed that among different microorganisms, pectinolysers had a significant effect on spoilage of MPCL and their population of ⩽3.59logcfu/g was found to be acceptable. Principal component analysis of headspace volatiles revealed that (E)-2-undecenal, (E)-2-hexadecenal, (E)-2-tetradecenal & (E)-2-tetradecen-1-ol in stored samples clustered with fresh samples and therefore, could be considered as freshness indicators for MPCL. Copyright © 2016 Elsevier Ltd. All rights reserved.

Transitions in optimal adaptive strategies for populations in fluctuating environments

NASA Astrophysics Data System (ADS)

Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.

2017-09-01

Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.

Establishing a Wild, Ex Situ Population of a Critically Endangered Shade-Tolerant Rainforest Conifer: A Translocation Experiment

PubMed Central

Zimmer, Heidi C.; Offord, Catherine A.; Auld, Tony D.; Baker, Patrick J.

2016-01-01

Translocation can reduce extinction risk by increasing population size and geographic range, and is increasingly being used in the management of rare and threatened plant species. A critical determinant of successful plant establishment is light environment. Wollemia nobilis (Wollemi pine) is a critically endangered conifer, with a wild population of 83 mature trees and a highly restricted distribution of less than 10 km2. We used under-planting to establish a population of W. nobilis in a new rainforest site. Because its optimal establishment conditions were unknown, we conducted an experimental translocation, planting in a range of different light conditions from deeply shaded to high light gaps. Two years after the experimental translocation, 85% of plants had survived. There were two distinct responses: very high survival (94%) but very low growth, and lower survival (69%) and higher growth, associated with initial plant condition. Overall survival of translocated W. nobilis was strongly increased in planting sites with higher light, in contrast to previous studies demonstrating long-term survival of wild W. nobilis juveniles in deep shade. Translocation by under-planting may be useful in establishing new populations of shade-tolerant plant species, not least by utilizing the range of light conditions that occur in forest understories. PMID:27403527

Establishing a Wild, Ex Situ Population of a Critically Endangered Shade-Tolerant Rainforest Conifer: A Translocation Experiment.

PubMed

Zimmer, Heidi C; Offord, Catherine A; Auld, Tony D; Baker, Patrick J

2016-01-01

Translocation can reduce extinction risk by increasing population size and geographic range, and is increasingly being used in the management of rare and threatened plant species. A critical determinant of successful plant establishment is light environment. Wollemia nobilis (Wollemi pine) is a critically endangered conifer, with a wild population of 83 mature trees and a highly restricted distribution of less than 10 km2. We used under-planting to establish a population of W. nobilis in a new rainforest site. Because its optimal establishment conditions were unknown, we conducted an experimental translocation, planting in a range of different light conditions from deeply shaded to high light gaps. Two years after the experimental translocation, 85% of plants had survived. There were two distinct responses: very high survival (94%) but very low growth, and lower survival (69%) and higher growth, associated with initial plant condition. Overall survival of translocated W. nobilis was strongly increased in planting sites with higher light, in contrast to previous studies demonstrating long-term survival of wild W. nobilis juveniles in deep shade. Translocation by under-planting may be useful in establishing new populations of shade-tolerant plant species, not least by utilizing the range of light conditions that occur in forest understories.

[Frailty in Germany: status and perspectives : Results from a workshop of the German Society for Epidemiology].

PubMed

Fuchs, Judith; Scheidt-Nave, Christa; Gaertner, Beate; Dapp, Ulrike; von Renteln-Kruse, Wolfgang; Saum, Kai-Uwe; Thorand, Barbara; Strobl, Ralf; Grill, Eva

2016-12-01

A standardized, valid and comparable operationalization and assessment of frailty in population-based studies is essential in order to describe the prevalence and determinants of frailty in the population. After an introduction to the subject the main goal of a workshop at the 9th annual meeting of the German Society for Epidemiology (DGEpi) was to present approaches and results from four different studies in Germany. The following four population-based studies were used to describe frailty in Germany: the German health interview and examination survey for adults (DEGS1), the epidemiological study on the chances of prevention, early recognition and optimized treatment of chronic diseases in the older population (ESTHER), the cooperative health research in the region Augsburg (KORA Age) study and the longitudinal urban cohort ageing study (LUCAS) in Hamburg. The four studies consistently showed that frailty is widespread in older and oldest-old persons in Germany. It is obvious that frailty represents a relevant concept in Germany even if there is currently no uniform basis for operationalization. Concepts and instruments for the collation of frailty should be included in future population-based studies in order to make a better assessment of older people's health situation and to describe the unused potential for prevention in an aging society.

The effect of travel loss on evolutionarily stable distributions of populations in space.

PubMed

Deangelis, Donald L; Wolkowicz, Gail S K; Lou, Yuan; Jiang, Yuexin; Novak, Mark; Svanbäck, Richard; Araújo, Márcio S; Jo, Youngseung; Cleary, Erin A

2011-07-01

A key assumption of the ideal free distribution (IFD) is that there are no costs in moving between habitat patches. However, because many populations exhibit more or less continuous population movement between patches and traveling cost is a frequent factor, it is important to determine the effects of costs on expected population movement patterns and spatial distributions. We consider a food chain (tritrophic or bitrophic) in which one species moves between patches, with energy cost or mortality risk in movement. In the two-patch case, assuming forced movement in one direction, an evolutionarily stable strategy requires bidirectional movement, even if costs during movement are high. In the N-patch case, assuming that at least one patch is linked bidirectionally to all other patches, optimal movement rates can lead to source-sink dynamics where patches with negative growth rates are maintained by other patches with positive growth rates. As well, dispersal between patches is not balanced (even in the two-patch case), leading to a deviation from the IFD. Our results indicate that cost-associated forced movement can have important consequences for spatial metapopulation dynamics. Relevance to marine reserve design and the study of stream communities subject to drift is discussed.

Subjective well-being among young people in five Eastern European countries.

PubMed

Lim, M S C; Cappa, C; Patton, G C

2017-01-01

Subjective well-being incorporates elements of life satisfaction, happiness and optimism. It is increasingly relevant in the assessment of population health and economic development. There are strong continuities in well-being from youth into later life. Despite its significance, few global surveys capture subjective well-being. This paper describes patterns of well-being among young people in five Eastern European countries [Belarus, Bosnia and Herzegovina (BiH), the Former Yugoslav Republic of Macedonia, Serbia and Ukraine] and investigates association between demographic factors and well-being. Nationally representative household surveys, including large Roma population samples, were conducted as part of UNICEF's Multiple Indicator Cluster Survey programme. Young people aged 15-24 years ( N  = 11 944) indicated their satisfaction with life, happiness and expectations about the future. Multilevel logistic regressions were conducted to determine the impact of individual-level predictors while accounting for country- and cluster-level variability. Around 40% of young people considered themselves very happy or very satisfied with their life overall. Three quarters reported optimism. Yet well-being varied greatly between countries, with youth in BiH and Ukraine reporting lowest levels of well-being. Current marriage, increasing wealth, higher education, rural residence and not having children were associated with greater well-being. Patterns of well-being in youth vary substantially between countries and are only partly accounted for by standard demographic characteristics. Despite higher rates of adolescent marriage and childbearing, and lower levels of educational attainment and employment, Roma youth had similar levels of well-being to the general population.

Optimization of the strength of the efavirenz/lamivudine/abacavir fixed-dose combination for paediatric patients.

PubMed

Bouazza, Naïm; Cressey, Tim R; Foissac, Frantz; Bienczak, Andrzej; Denti, Paolo; McIlleron, Helen; Burger, David; Penazzato, Martina; Lallemant, Marc; Capparelli, Edmund V; Treluyer, Jean-Marc; Urien, Saïk

2017-02-01

Child-friendly, low-cost, solid, oral fixed-dose combinations (FDCs) of efavirenz with lamivudine and abacavir are urgently needed to improve clinical management and drug adherence for children. Data were pooled from several clinical trials and therapeutic drug monitoring datasets from different countries. The number of children/observations was 505/3667 for efavirenz. Population pharmacokinetic analyses were performed using a non-linear mixed-effects approach. For abacavir and lamivudine, data from 187 and 920 subjects were available (population pharmacokinetic models previously published). Efavirenz/lamivudine/abacavir FDC strength options assessed were (I) 150/75/150, (II) 120/60/120 and (III) 200/100/200 mg. Monte Carlo simulations of the different FDC strengths were performed to determine the optimal dose within each of the WHO weight bands based on drug efficacy/safety targets. The probability of being within the target efavirenz concentration range 12 h post-dose (1-4 mg/L) varied between 56% and 60%, regardless of FDC option. Option I provided a best possible balance between efavirenz treatment failure and toxicity risks. For abacavir and lamivudine, simulations showed that for option I >75% of subjects were above the efficacy target. According to simulations, a paediatric efavirenz/lamivudine/abacavir fixed-dose formulation of 150 mg efavirenz, 75 mg lamivudine and 150 mg abacavir provided the most effective and safe concentrations across WHO weight bands, with the flexibility of dosage required across the paediatric population. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The association between achieving low-density lipoprotein cholesterol (LDL-C) goal and statin treatment in an employee population.

PubMed

Burton, Wayne N; Chen, Chin-Yu; Schultz, Alyssa B; Edington, Dee W

2010-02-01

Statin medications are recommended for patients who have not achieved low-density lipoprotein cholesterol (LDL-C) goals through lifestyle modifications. The objective of this retrospective observational study was to examine statin medication usage patterns and the relationship with LDL-C goal levels (according to Adult Treatment Panel III guidelines) among a cohort of employees of a major financial services corporation. From 1995 to 2004, a total of 1607 executives participated in a periodic health examination program. An index date was assigned for each study participant (date of their exam) and statin medication usage was determined from the pharmacy claims database for 365 days before the index date. Patients were identified as adherent to statins if the medication possession ratio was > or =80%. In all, 150 (9.3%) executives filled at least 1 statin prescription in the 365 days prior to their exam. A total of 102 statin users (68%) were adherent to statin medication. Among all executives who received statin treatment, 70% (odds ratio [OR] = 2.30, 95% confidence interval [CI] = 1.82, 2.90) achieved near-optimal (<130 mg/dL) and 30% (OR = 1.78, 95% CI = 1.15, 2.76) achieved optimal (<100 mg/dL) LDL-C goals, which is significantly higher than the rates among statin nonusers (55% and 21%). Adherent statin users were more likely to achieve recommended near-optimal LDL-C goals compared to statin nonusers (overall P = 0.002; adherent: OR = 2.75, 95% CI = 1.662, 4.550), while nonadherent statin users were more likely to achieve the optimal goal compared to statin nonusers (OR = 2.223; CI = 1.145, 4.313). Statin usage was associated with improvements in LDL-C goal attainment among executives who participated in a periodic health examination. Appropriate statin medication adherence should be encouraged in working populations in order to achieve LDL-C goals.

Short-term vs. long-term heart rate variability in ischemic cardiomyopathy risk stratification.

PubMed

Voss, Andreas; Schroeder, Rico; Vallverdú, Montserrat; Schulz, Steffen; Cygankiewicz, Iwona; Vázquez, Rafael; Bayés de Luna, Antoni; Caminal, Pere

2013-01-01

In industrialized countries with aging populations, heart failure affects 0.3-2% of the general population. The investigation of 24 h-ECG recordings revealed the potential of nonlinear indices of heart rate variability (HRV) for enhanced risk stratification in patients with ischemic heart failure (IHF). However, long-term analyses are time-consuming, expensive, and delay the initial diagnosis. The objective of this study was to investigate whether 30 min short-term HRV analysis is sufficient for comparable risk stratification in IHF in comparison to 24 h-HRV analysis. From 256 IHF patients [221 at low risk (IHFLR) and 35 at high risk (IHFHR)] (a) 24 h beat-to-beat time series (b) the first 30 min segment (c) the 30 min most stationary day segment and (d) the 30 min most stationary night segment were investigated. We calculated linear (time and frequency domain) and nonlinear HRV analysis indices. Optimal parameter sets for risk stratification in IHF were determined for 24 h and for each 30 min segment by applying discriminant analysis on significant clinical and non-clinical indices. Long- and short-term HRV indices from frequency domain and particularly from nonlinear dynamics revealed high univariate significances (p < 0.01) discriminating between IHFLR and IHFHR. For multivariate risk stratification, optimal mixed parameter sets consisting of 5 indices (clinical and nonlinear) achieved 80.4% AUC (area under the curve of receiver operating characteristics) from 24 h HRV analysis, 84.3% AUC from first 30 min, 82.2 % AUC from daytime 30 min and 81.7% AUC from nighttime 30 min. The optimal parameter set obtained from the first 30 min showed nearly the same classification power when compared to the optimal 24 h-parameter set. As results from stationary daytime and nighttime, 30 min segments indicate that short-term analyses of 30 min may provide at least a comparable risk stratification power in IHF in comparison to a 24 h analysis period.

Optimal Cut-Offs of Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) to Identify Dysglycemia and Type 2 Diabetes Mellitus: A 15-Year Prospective Study in Chinese

PubMed Central

Lee, C. H.; Shih, A. Z. L.; Woo, Y. C.; Fong, C. H. Y.; Leung, O. Y.; Janus, E.; Cheung, B. M. Y.; Lam, K. S. L.

2016-01-01

Background The optimal reference range of homeostasis model assessment of insulin resistance (HOMA-IR) in normal Chinese population has not been clearly defined. Here we address this issue using the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS), a prospective population-based cohort study with long-term follow-up. Material & Methods In this study, normal glucose tolerance (NGT), impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM) were defined according to the 1998 World Health Organization criteria. Dysglycemia referred to IFG, IGT or T2DM. This study comprised two parts. Part one was a cross-sectional study involving 2,649 Hong Kong Chinese subjects, aged 25–74 years, at baseline CRISPS-1 (1995–1996). The optimal HOMA-IR cut-offs for dysglycemia and T2DM were determined by the receiver-operating characteristic (ROC) curve. Part two was a prospective study involving 872 subjects who had persistent NGT at CRISPS-4 (2010–2012) after 15 years of follow-up. Results At baseline, the optimal HOMA-IR cut-offs to identify dysglyceia and T2DM were 1.37 (AUC = 0.735; 95% confidence interval [CI] = 0.713–0.758; Sensitivity [Se] = 65.6%, Specificity [Sp] = 71.3%] and 1.97 (AUC = 0.807; 95% CI = 0.777–0.886; Se = 65.5%, Sp = 82.9%) respectively. These cut-offs, derived from the cross-sectional study at baseline, corresponded closely to the 75th (1.44) and 90th (2.03) percentiles, respectively, of the HOMA-IR reference range derived from the prospective study of subjects with persistent NGT. Conclusions HOMA-IR cut-offs, of 1.4 and 2.0, which discriminated dysglycemia and T2DM respectively from NGT in Southern Chinese, can be usefully employed as references in clinical research involving the assessment of insulin resistance. PMID:27658115

Optimal Cut-Offs of Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) to Identify Dysglycemia and Type 2 Diabetes Mellitus: A 15-Year Prospective Study in Chinese.

PubMed

Lee, C H; Shih, A Z L; Woo, Y C; Fong, C H Y; Leung, O Y; Janus, E; Cheung, B M Y; Lam, K S L

The optimal reference range of homeostasis model assessment of insulin resistance (HOMA-IR) in normal Chinese population has not been clearly defined. Here we address this issue using the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS), a prospective population-based cohort study with long-term follow-up. In this study, normal glucose tolerance (NGT), impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM) were defined according to the 1998 World Health Organization criteria. Dysglycemia referred to IFG, IGT or T2DM. This study comprised two parts. Part one was a cross-sectional study involving 2,649 Hong Kong Chinese subjects, aged 25-74 years, at baseline CRISPS-1 (1995-1996). The optimal HOMA-IR cut-offs for dysglycemia and T2DM were determined by the receiver-operating characteristic (ROC) curve. Part two was a prospective study involving 872 subjects who had persistent NGT at CRISPS-4 (2010-2012) after 15 years of follow-up. At baseline, the optimal HOMA-IR cut-offs to identify dysglyceia and T2DM were 1.37 (AUC = 0.735; 95% confidence interval [CI] = 0.713-0.758; Sensitivity [Se] = 65.6%, Specificity [Sp] = 71.3%] and 1.97 (AUC = 0.807; 95% CI = 0.777-0.886; Se = 65.5%, Sp = 82.9%) respectively. These cut-offs, derived from the cross-sectional study at baseline, corresponded closely to the 75th (1.44) and 90th (2.03) percentiles, respectively, of the HOMA-IR reference range derived from the prospective study of subjects with persistent NGT. HOMA-IR cut-offs, of 1.4 and 2.0, which discriminated dysglycemia and T2DM respectively from NGT in Southern Chinese, can be usefully employed as references in clinical research involving the assessment of insulin resistance.

Optimized management of heart failure patients aged 80 years or more improves outcomes versus usual care: The HF80 randomized trial.

PubMed

Vorilhon, Charles; Jean, Frédéric; Mulliez, Aurélien; Clerfond, Guillaume; Pereira, Bruno; Sapin, Vincent; Souteyrand, Géraud; Citron, Bernard; Motreff, Pascal; Lusson, Jean-René; Eschalier, Romain

2016-12-01

The prevalence and incidence of heart failure (HF) in elderly patients are increasing worldwide. Management of HF with reduced ejection fraction (HF-REF) in patients aged 80 years or more follows international guidelines, despite the lack of a dedicated study in this frail population. To determine whether optimized management of HF-REF in patients aged 80 years or more can improve quality of life at 6 months. Patients aged 80 years or more hospitalized for acute HF-REF were randomized prospectively into an optimized group or a control group (usual care). All patients benefitted from the same in-hospital management. Optimized group patients were also managed at 3, 6 and 9 weeks, and 3, 6, 9 and 12 months after initial hospitalization, to optimize HF-REF treatment. The primary endpoint was quality of life at 6 months. The trial was stopped prematurely, according to prespecified rules and an independent data monitoring board, after 34 patients were included (n=17 in each group). There was no difference in quality of life at baseline and at 6 months between the two groups (P=0.14 and 0.64, respectively), although a significant improvement was observed between baseline and 6 months in the optimized group compared with the control group: -20.2±25.2 (P=0.01) versus -9.9±19.0 (P=0.19). Mortality at 12 months was lower in the optimized group (17.7% vs 47.1%; P=0.03). There was no increase in acute renal failure, hyperkalaemia or falls in the optimized group (P=0.49, 1 and 1, respectively). Optimizing the management of HF-REF in patients aged 80 years or more, according to the modalities of the HF80 study, seems to be both effective and safe. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

COPS: Large-scale nonlinearly constrained optimization problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bondarenko, A.S.; Bortz, D.M.; More, J.J.

2000-02-10

The authors have started the development of COPS, a collection of large-scale nonlinearly Constrained Optimization Problems. The primary purpose of this collection is to provide difficult test cases for optimization software. Problems in the current version of the collection come from fluid dynamics, population dynamics, optimal design, and optimal control. For each problem they provide a short description of the problem, notes on the formulation of the problem, and results of computational experiments with general optimization solvers. They currently have results for DONLP2, LANCELOT, MINOS, SNOPT, and LOQO.

Monitoring Cell Proliferation by Dye Dilution: Considerations for Probe Selection

PubMed Central

Tario, Joseph D.; Conway, Alexis N.; Muirhead, Katharine A.; Wallace, Paul K.

2018-01-01

In the third edition of this series, we described protocols for labeling cell populations with tracking dyes, and addressed issues to be considered when combining two different tracking dyes with other phenotypic and viability probes for the assessment of cytotoxic effector activity and regulatory T cell functions. We summarized key characteristics of and differences between general protein and membrane labeling dyes, discussed determination of optimal staining concentrations, and provided detailed labeling protocols for both dye types. Examples of the advantages of two color cell tracking were provided in the form of protocols for: (a) independent enumeration of viable effector and target cells in a direct cytotoxicity assay; and (b) an in vitro suppression assay for simultaneous proliferation monitoring of effector and regulatory T cells. The number of commercially available fluorescent cell tracking dyes has expanded significantly since the last edition, with new suppliers and/or new spectral properties being added at least annually. In this fourth edition, we describe evaluations to be performed by the supplier and/or user when characterizing a new cell tracking dye and by the user when selecting one for use in multicolor proliferation monitoring. These include methods for: Assessment of the dye’s spectral profile on the laboratory’s flow cytometer(s) to optimize compatibility with other employed fluorochromes and minimize compensation problems;Evaluating the effect of labeling on cell growth rate;Testing the fidelity with which dye dilution reports cell division;Determining the maximum number of generations to be included when using dye dilution profiles to estimate fold population expansion or frequency of responder cells; andVerifying that relevant cell functions (e.g., effector activity) remain unaltered by tracking dye labeling. PMID:29071683

Young patients with diverticular disease: a preliminary quality of life study.

PubMed

Koo, Vincent; Strange, John; Lam, Ching Yin; Epanomeritakis, Manos

2007-08-01

Diverticular disease is more apparent in the younger population under 50 years however, its management remains controversial. We report a preliminary quality of life (QoL) assessment which may be useful when determining the optimal management strategy. A retrospective review of clinical records was carried out from April 1999 to 2004, to identify all patients diagnosed with diverticular disease and its complications, confirmed either by radiology and/or histology evidence. The younger patients were classified according to their management: surgical or conservative. Information on demographic, investigations, treatment, follow-up and recurrent episodes was recorded, and the health-related SF-36 QoL questionnaire was administered. A total of 47 patients had confirmed diverticular disease. Forty-one patients were managed conservatively and six underwent surgery. Ten (24%) from the conservative group and one (17%) from the surgical group were re-admitted for recurrence of symptoms. About 80% (33 conservative and five surgical) responded to the QoL questionnaire. There was an overall negative impact on all QoL domains (conservative vs surgical): general health (54.1 vs 39.0), physical functioning (72.7 vs 56.0), social functioning (63.3 vs 67.0), physical role limitation (50.0 vs 45.0), emotional role limitation (58.6 vs 26.7), bodily pain (56.9 vs 48.5), vitality (45.0 vs 43.0), mental health (64.5 vs 57.6), PCS (44.5 vs 40.8), MCS (42.6 vs 38.8); and these domain scores did not differ significantly. Although there was a negative impact on the quality of life, the majority of patients can be treated adequately by conservative management. We highlighted the need to consider the QoL aspect when determining the optimal management of the disease in the younger population.

Physiological Trade-Offs Along a Fast-Slow Lifestyle Continuum in Fishes: What Do They Tell Us about Resistance and Resilience to Hypoxia?

PubMed Central

Stoffels, Rick J.

2015-01-01

It has recently been suggested that general rules of change in ecological communities might be found through the development of functional relationships between species traits and performance. The physiological, behavioural and life-history traits of fishes are often organised along a fast-slow lifestyle continuum (FSLC). With respect to resistance (capacity for population to resist change) and resilience (capacity for population to recover from change) to environmental hypoxia, the literature suggests that traits enhancing resilience may come at the expense of traits promoting resistance to hypoxia; a trade-off may exist. Here I test whether three fishes occupying different positions along the FSLC trade-off resistance and resilience to environmental hypoxia. Static respirometry experiments were used to determine resistance, as measured by critical oxygen tension (Pcrit), and capacity for (RC) and magnitude of metabolic reduction (RM). Swimming respirometry experiments were used to determine aspects of resilience: critical (U crit) and optimal swimming speed (U opt), and optimal cost of transport (COTopt). Results pertaining to metabolic reduction suggest a resistance gradient across species described by the inequality Melanotaenia fluviatilis (fast lifestyle) < Hypseleotris sp. (intermediate lifestyle) < Mogurnda adspersa (slow lifestyle). The Ucrit and COTopt data suggest a resilience gradient described by the reverse inequality, and so the experiments generally indicate that three fishes occupying different positions on the FSLC trade-off resistance and resilience to hypoxia. However, the scope of inferences that can be drawn from an individual study is narrow, and so steps towards general, trait-based rules of fish community change along environmental gradients are discussed. PMID:26070078

Estimating carrying capacity in a newly colonized sand fly Lutzomyia serrana (Diptera: Psychodidae).

PubMed

Santamaría, Erika; Munstermann, Leonard E; Ferro, Cristina

2002-02-01

The phlebotomine sand fly Lutzomyia serrana (Damasceno & Arouck) was mass-reared tinder conditions of varying densities in an effort to improve colony production efficiency. To do this, the experimental carrying capacity of a standard rearing chamber was determined, i.e., the optimum population size in relation to density (individuals per unit of space). Rearing chambers of 100 cm3 were populated with 1-50 L. serrana engorged females and an equal number of males. Laboratory conditions were maintained at 23-26 degrees C and 85-95% RH. The following parameters were recorded for each experimental chamber (three replicates): (1) female mortality without oviposition, (2) number of eggs oviposited and (3) number of adults emerging from the egg cohort. Female mortality began to increase substantially in the 26-female chamber, from 5.7% to 15% and finally reaching 60.2% in the 46-50 female chambers. In the chambers containing 1-20 females, egg number and realized adult progeny increased linearly to reach an asymptote. In the 20-50 female chambers, the number of eggs ranged from 420 to 699, and adult production from 306 to 432. The optimum carrying capacity for the 100-cm3 chambers was 22 +/- 2 females. Beyond this number, auto-regulation was initiated, i.e., female mortality without oviposition increased as the number of females per chamber increased. Total number of eggs and adult production was similar in all chambers containing 20-50 females. In conclusion, for optimizing production of mass reared sand flies, determination of the carrying capacity is essential to optimize use of insectary resources, to avoid loss of valuable potentially ovipositing females, and to increase overall production efficiency.

First report on simplified diagnostic criteria for pre-hypertension and hypertension in a national sample of adolescents from the Middle East and North Africa: the CASPIAN-III study.

PubMed

Kelishadi, Roya; Heshmat, Ramin; Ardalan, Gelayol; Qorbani, Mostafa; Taslimi, Mahnaz; Poursafa, Parinaz; Keramatian, Kasra; Taheri, Majzoubeh; Motlagh, Mohammad-Esmaeil

2014-01-01

This study aimed to simplify the diagnostic criteria of pre-hypertension (pre-HTN) and hypertension (HTN) in the pediatric age group, and to determine the accuracy of these simple indexes in a nationally-representative sample of Iranian children and adolescents. The diagnostic accuracy of the indexes of systolic blood pressure-to-height ratio (SBPHR) and diastolic BPHR (DBPHR) to define pre-HTN and HTN was determined by the area under the curve of the receiver operator characteristic curves. The study population consisted of 5,738 Iranian students (2,875 females) with mean (SD) age of 14.7 (2.4) years. The prevalences of pre-HTN and HTN were 6.9% and 5.6%. The optimal thresholds for defining pre-HTN were 0.73 in males and 0.71 in females for SBPHR, and 0.47 in males and 0.45 in females for DBPHR, respectively. The corresponding figures for HTN were 0.73, 0.71, 0.48, and 0.46, respectively. In both genders, the accuracies of SBPHR and DBPHR in diagnosing pre-HTN and HTN were approximately 80%. BPHR is a valid, simple, inexpensive, and accurate tool to diagnose pre-HTN and HTN in adolescents. The optimal thresholds of SBPHR and DBPHR were consistent with the corresponding figures in other populations of children and adolescents with different racial and ethnic backgrounds. Thus, it is suggested that the use of these indexes can be generalized in programs aiming to screen elevated blood pressure in the pediatric age group. Copyright © 2013 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Health in Adapted Youth Sports Study (HAYS): health effects of sports participation in children and adolescents with a chronic disease or physical disability.

PubMed

Lankhorst, Kristel; van der Ende-Kastelijn, Karin; de Groot, Janke; Zwinkels, Maremka; Verschuren, Olaf; Backx, Frank; Visser-Meily, Anne; Takken, Tim

2015-01-01

In typically developing children, participation in sports has been proven to be positively correlated to both physical and psychosocial health outcomes. In children and adolescents with a physical disability or chronic disease participation in both recreational and competitive sports is often reduced, while for this population an active lifestyle may be even more important in reaching optimal levels of physical and psychosocial health. Therefore, the aim of the Health in Adapted Youth Sports (HAYS) Study is to determine both negative and positive effects of sports on children and adolescents with a chronic disease or physical disability. In this cross-sectional study differences will be compared in regards to physical and psychosocial health, cognitive functioning, school performance, daily physical activity and injuries between children and adolescents with a chronic disease or physical disability who participate in sports and those who do not. Children and adolescents, both ambulatory and wheelchair dependent, in the age of 10-19 years with a physical disability or chronic disease will be included. "Sports" is defined as participation in an organized sport at least two times a week for a duration of 3 months or more prior to the assessment. Parametric and non-parametric statistics will be used to determine the differences between the two groups. This study provides insight in the effects of sports participation in relation to health, psychosocial functioning, physical activity and school performance in children and adolescents (10-19 years) with a chronic disease or physical disability. Results will guide healthcare professionals working with these children to better guide this population in reaching optimal levels of health and physical activity levels.

Injury, disability and access to care in Rwanda: results of a nationwide cross-sectional population study.

PubMed

Petroze, Robin T; Joharifard, Shahrzad; Groen, Reinou S; Niyonkuru, Francine; Ntaganda, Edmond; Kushner, Adam L; Guterbock, Thomas M; Kyamanywa, Patrick; Calland, J Forrest

2015-01-01

Disparities in access to quality injury care are a growing concern worldwide, with over 90 % of global injury-related morbidity and mortality occurring in low-income countries. We describe the use of a survey tool that evaluates the prevalence of surgical conditions at the population level, with a focus on the burden of traumatic injuries, subsequent disabilities, and barriers to injury care in Rwanda. The Surgeons OverSeas Assessment of Surgical Need (SOSAS) tool is a cross-sectional, cluster-based population survey designed to measure conditions that may necessitate surgical consultation or intervention. Questions are structured anatomically and designed around a representative spectrum of surgical conditions. Households in Rwanda were sampled using two-stage cluster sampling, and interviews were conducted over a one-month period in 52 villages nationwide, with representation of all 30 administrative districts. Injury-related results were descriptively analyzed and population-weighted by age and gender. A total of 1,627 households (3,175 individuals) were sampled; 1,185 lifetime injury-related surgical conditions were reported, with 38 % resulting in some form of perceived disability. Of the population, 27.4 % had ever had a serious injury-related condition, with 2.8 % having an injury-related condition at the time of interview. Over 30 % of household deaths in the previous year may have been surgically treatable, but only 4 % were injury-related. Determining accurate injury and disability burden is crucial to health system planning in low-income countries. SOSAS is a useful survey for determining injury epidemiology at the community level, which can in turn help to plan prevention efforts and optimize provision of care.

Balancing selection maintains polymorphisms at neurogenetic loci in field experiments

PubMed Central

Lonn, Eija; Mappes, Tapio; Mokkonen, Mikael; Sims, Angela M.; Watts, Phillip C.

2017-01-01

Most variation in behavior has a genetic basis, but the processes determining the level of diversity at behavioral loci are largely unknown for natural populations. Expression of arginine vasopressin receptor 1a (Avpr1a) and oxytocin receptor (Oxtr) in specific regions of the brain regulates diverse social and reproductive behaviors in mammals, including humans. That these genes have important fitness consequences and that natural populations contain extensive diversity at these loci implies the action of balancing selection. In Myodes glareolus, Avpr1a and Oxtr each contain a polymorphic microsatellite locus located in their 5′ regulatory region (the regulatory region-associated microsatellite, RRAM) that likely regulates gene expression. To test the hypothesis that balancing selection maintains diversity at behavioral loci, we released artificially bred females and males with different RRAM allele lengths into field enclosures that differed in population density. The length of Avpr1a and Oxtr RRAMs was associated with reproductive success, but population density and the sex interacted to determine the optimal genotype. In general, longer Avpr1a RRAMs were more beneficial for males, and shorter RRAMs were more beneficial for females; the opposite was true for Oxtr RRAMs. Moreover, Avpr1a RRAM allele length is correlated with the reproductive success of the sexes during different phases of reproduction; for males, RRAM length correlated with the numbers of newborn offspring, but for females selection was evident on the number of weaned offspring. This report of density-dependence and sexual antagonism acting on loci within the arginine vasopressin–oxytocin pathway explains how genetic diversity at Avpr1a and Oxtr could be maintained in natural populations. PMID:28325880

Trait-based Modeling of Larval Dispersal in the Gulf of Maine

NASA Astrophysics Data System (ADS)

Jones, B.; Richardson, D.; Follows, M. J.; Hill, C. N.; Solow, A.; Ji, R.

2016-02-01

Population connectivity of marine species is the inter-generational movement of individuals among geographically separated subpopulations and is a crucial determinant of population dynamics, community structure, and optimal management strategies. For many marine species, population connectivity is largely determined by the dispersal patterns that emerge from a pelagic larval phase. These dispersal patterns are a result of interactions between the physical environment, adult spawning strategy, and larval ecology. Using a generalized trait-based model that represents the adult spawning strategy as a distribution of larval releases in time and space and the larval trait space with the pelagic larval duration, vertical swimming behavior, and settlement habitat preferences, we simulate dispersal patterns in the Gulf of Maine and surrounding regions. We implement this model as an individual-based simulation that tracks Lagrangian particles on a graphics processing unit as they move through hourly archived output from the Finite-Volume Community Ocean Model. The particles are released between the Hudson Canyon and Nova Scotia and the release distributions are determined using a novel method that minimizes the number of simulations required to achieve a predetermined level of precision for the connectivity matrices. The simulated larvae have a variable pelagic larval duration and exhibit multiple forms of dynamic depth-keeping behavior. We describe how these traits influence the dispersal trajectories and connectivity patterns among regions in the northwest Atlantic. Our description includes the probability of successful recruitment, patchiness of larval distributions, and the variability of these properties in time and space under a variety of larval dispersal strategies.

Seasonal reproduction leads to population collapse and an Allee effect in a stage-structured consumer-resource biomass model when mortality rate increases

PubMed Central

de Roos, André M.

2017-01-01

Many populations collapse suddenly when reaching low densities even if they have abundant food conditions, a phenomenon known as an Allee effect. Such collapses can have disastrous consequences, for example, for loss of biodiversity. In this paper, we formulate a stage-structured consumer-resource biomass model in which adults only reproduce at the beginning of each growing season, and investigate the effect of an increasing stage-independent background mortality rate of the consumer. As the main difference with previously studied continuous-time models, seasonal reproduction can result in an Allee effect and consumer population collapses at high consumer mortality rate. However, unlike the mechanisms reported in the literature, in our model the Allee effect results from the time difference between the maturation of juveniles and the reproduction of adults. The timing of maturation plays a crucial role because it not only determines the body size of the individuals at maturation but also influences the duration of the period during which adults can invest in reproductive energy, which together determine the reproductive output at the end of the season. We suggest that there exists an optimal timing of maturation and that consumer persistence is promoted if individuals mature later in the season at a larger body size, rather than maturing early, despite high food availability supporting rapid growth. PMID:29088273

Fetal growth curves for an ethnically diverse military population: the American Institute of Ultrasound in Medicine-accredited platform experience.

PubMed

Elliott, Dawn; Patience, Troy; Boyd, Emily; Hume, Roderick F; Calhoun, Byron C; Napolitano, Peter G; Apodaca, Christina C

2006-06-01

To determine which fetal growth curve provided the best estimates of fetal weight for a cohort of ethnically diverse patients at sea level. The study consisted of a population of 1,729 fetuses examined at sea level between January 1, 1997, and June 30, 2000, at 18 weeks, 28 weeks, and term. Gestational age (GA) based on menstrual dates was confirmed or adjusted by crown-rump length or early second-trimester biometry. Fetal weight was estimated by using biparietal diameter, head circumference, abdominal circumference, and femur length. Our fetal growth curves were analyzed with fourth-order polynomial regression analysis, applying four previously defined formulae for fetal growth. Fetal growth curves for estimated fetal weight demonstrated the expected parabolic shape, which varied according to the formulae used. Our curve best fit the following equation: estimated fetal weight = 4.522 - 0.22 x GA age + 0.25 x GA(2) - 0.001 x GA(3) + 5.248 x 10(-6) x GA(4) (R2 = 0.976). SD increased in concordance with GA. Madigan Army Medical Center serves a racially mixed, culturally diverse, military community with unrestricted access to prenatal care. Determination of the optimal population-appropriate growth curve at the correct GA assists clinicians in identifying fetuses at risk for growth restriction or macrosomia and therefore at risk for increased perinatal morbidity and death.

Two additional principles for determining which species to monitor.

PubMed

Wilson, Howard B; Rhodes, Jonathan R; Possingham, Hugh P

2015-11-01

Monitoring to detect population declines is widespread, but also costly. There is, consequently, a need to optimize monitoring to maximize cost-effectiveness. Here we develop a quantitative decision analysis framework for how to optimally allocate resources for monitoring among species. By keeping the framework simple, we analytically establish two new principles about which species are optimal to monitor for detecting declines: (1) those that lie on the boundary between species being allocated resources for conservation action and species that are not and (2) those with the greatest uncertainty in whether they are declining. These two principles are in addition to other factors that are also important in monitoring decisions, such as complementarity. We demonstrate the efficacy of these principles when other factors are not present, and show how the two principles can be combined. This analysis demonstrates that the most cost-effective species to monitor are ones where the information gained from monitoring is most likely to change the allocation of funds for action, not necessarily the most vulnerable or endangered. We suggest these results are general and apply to all ecological monitoring, not just of biological species: monitoring and information are only valuable when they are likely to change how people act.

Optimization of the Water Volume in the Buckets of Pico Hydro Overshot Waterwheel by Analytical Method

NASA Astrophysics Data System (ADS)

Budiarso; Adanta, Dendy; Warjito; Siswantara, A. I.; Saputra, Pradhana; Dianofitra, Reza

2018-03-01

Rapid economic and population growth in Indonesia lead to increased energy consumption, including electricity needs. Pico hydro is considered as the right solution because the cost of investment and operational cost are fairly low. Additionally, Indonesia has many remote areas with high hydro-energy potential. The overshot waterwheel is one of technology that is suitable to be applied in remote areas due to ease of operation and maintenance. This study attempts to optimize bucket dimensions with the available conditions. In addition, the optimization also has a good impact on the amount of generated power because all available energy is utilized maximally. Analytical method is used to evaluate the volume of water contained in bucket overshot waterwheel. In general, there are two stages performed. First, calculation of the volume of water contained in each active bucket is done. If the amount total of water contained is less than the available discharge in active bucket, recalculation at the width of the wheel is done. Second, calculation of the torque of each active bucket is done to determine the power output. As the result, the mechanical power generated from the waterwheel is 305 Watts with the efficiency value of 28%.

Controlling measles using supplemental immunization activities: A mathematical model to inform optimal policy

PubMed Central

Verguet, Stéphane; Johri, Mira; Morris, Shaun K.; Gauvreau, Cindy L.; Jha, Prabhat; Jit, Mark

2015-01-01

Background The Measles & Rubella Initiative, a broad consortium of global health agencies, has provided support to measles-burdened countries, focusing on sustaining high coverage of routine immunization of children and supplementing it with a second dose opportunity for measles vaccine through supplemental immunization activities (SIAs). We estimate optimal scheduling of SIAs in countries with the highest measles burden. Methods We develop an age-stratified dynamic compartmental model of measles transmission. We explore the frequency of SIAs in order to achieve measles control in selected countries and two Indian states with high measles burden. Specifically, we compute the maximum allowable time period between two consecutive SIAs to achieve measles control. Results Our analysis indicates that a single SIA will not control measles transmission in any of the countries with high measles burden. However, regular SIAs at high coverage levels are a viable strategy to prevent measles outbreaks. The periodicity of SIAs differs between countries and even within a single country, and is determined by population demographics and existing routine immunization coverage. Conclusions Our analysis can guide country policymakers deciding on the optimal scheduling of SIA campaigns and the best combination of routine and SIA vaccination to control measles. PMID:25541214

Applications of physiologically based pharmacokinetic modeling for the optimization of anti-infective therapies.

PubMed

Moss, Darren Michael; Marzolini, Catia; Rajoli, Rajith K R; Siccardi, Marco

2015-01-01

The pharmacokinetic properties of anti-infective drugs are a determinant part of treatment success. Pathogen replication is inhibited if adequate drug levels are achieved in target sites, whereas excessive drug concentrations linked to toxicity are to be avoided. Anti-infective distribution can be predicted by integrating in vitro drug properties and mathematical descriptions of human anatomy in physiologically based pharmacokinetic models. This method reduces the need for animal and human studies and is used increasingly in drug development and simulation of clinical scenario such as, for instance, drug-drug interactions, dose optimization, novel formulations and pharmacokinetics in special populations. We have assessed the relevance of physiologically based pharmacokinetic modeling in the anti-infective research field, giving an overview of mechanisms involved in model design and have suggested strategies for future applications of physiologically based pharmacokinetic models. Physiologically based pharmacokinetic modeling provides a powerful tool in anti-infective optimization, and there is now no doubt that both industry and regulatory bodies have recognized the importance of this technology. It should be acknowledged, however, that major challenges remain to be addressed and that information detailing disease group physiology and anti-infective pharmacodynamics is required if a personalized medicine approach is to be achieved.

Modeling uncertainty in producing natural gas from tight sands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chermak, J.M.; Dahl, C.A.; Patrick, R.H

1995-12-31

Since accurate geologic, petroleum engineering, and economic information are essential ingredients in making profitable production decisions for natural gas, we combine these ingredients in a dynamic framework to model natural gas reservoir production decisions. We begin with the certainty case before proceeding to consider how uncertainty might be incorporated in the decision process. Our production model uses dynamic optimal control to combine economic information with geological constraints to develop optimal production decisions. To incorporate uncertainty into the model, we develop probability distributions on geologic properties for the population of tight gas sand wells and perform a Monte Carlo study tomore » select a sample of wells. Geological production factors, completion factors, and financial information are combined into the hybrid economic-petroleum reservoir engineering model to determine the optimal production profile, initial gas stock, and net present value (NPV) for an individual well. To model the probability of the production abandonment decision, the NPV data is converted to a binary dependent variable. A logit model is used to model this decision as a function of the above geological and economic data to give probability relationships. Additional ways to incorporate uncertainty into the decision process include confidence intervals and utility theory.« less

Economic thermoregulatory response explains mismatch between thermal physiology and behaviour in newts.

PubMed

Gvoždík, Lumír; Kristín, Peter

2017-03-15

Temperature is an important factor determining distribution and abundance of organisms. Predicting the impact of warming climate on ectotherm populations requires information about species' thermal requirements, i.e. their so-called 'thermal niche'. The characterization of thermal niche remains a complicated task. We compared the applicability of two indirect approaches, based on reaction norm (aerobic scope curve) and optimality (preferred body temperature) concepts, for indirect estimation of thermal niche while using newts, Ichthyosaura alpestris , as a study system. If the two approaches are linked, then digesting newts should keep their body temperatures close to values maximizing aerobic scope for digestion. After feeding, newts maintained their body temperatures within a narrower range than did hungry individuals. The range of preferred body temperatures was well below the temperature maximizing aerobic scope for digestion. Optimal temperatures for factorial aerobic scope fell within the preferred body temperature range of digesting individuals. We conclude that digesting newts prefer body temperatures that are optimal for the maximum aerobic performance but relative to the maintenance costs. What might be termed the 'economic' thermoregulatory response explains the mismatch between thermal physiology and behaviour in this system. © 2017. Published by The Company of Biologists Ltd.

Efficient dynamic optimization of logic programs

NASA Technical Reports Server (NTRS)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

Climatic niche and flowering and fruiting phenology of an epiphytic plant.

PubMed

Barve, Narayani; Martin, Craig E; Peterson, A Townsend

2015-09-10

Species have geographic distributions constrained by combinations of abiotic factors, biotic factors and dispersal-related factors. Abiotic requirements vary across the life stages for a species; for plant species, a particularly important life stage is when the plant flowers and develops seeds. A previous year-long experiment showed that ambient temperature of 5-35 °C, relative humidity of >50 % and ≤15 consecutive rainless days are crucial abiotic conditions for Spanish moss (Tillandsia usneoides L.). Here, we explore whether these optimal physiological intervals relate to the timing of the flowering and fruiting periods of Spanish moss across its range. As Spanish moss has a broad geographic range, we examined herbarium specimens to detect and characterize flowering/fruiting periods for the species across the Americas; we used high-temporal-resolution climatic data to assess the availability of optimal conditions for Spanish moss populations during each population's flowering period. We explored how long populations experience suboptimal conditions and found that most populations experience suboptimal conditions in at least one environmental dimension. Flowering and fruiting periods of Spanish moss populations are either being optimized for one or a few parameters or may be adjusted such that all parameters are suboptimal. Spanish moss populations appear to be constrained most closely by minimum temperature during this period. Published by Oxford University Press on behalf of the Annals of Botany Company.

Low thrust spacecraft transfers optimization method with the stepwise control structure in the Earth-Moon system in terms of the L1-L2 transfer

NASA Astrophysics Data System (ADS)

Fain, M. K.; Starinova, O. L.

2016-04-01

The paper outlines the method for determination of the locally optimal stepwise control structure in the problem of the low thrust spacecraft transfer optimization in the Earth-Moon system, including the L1-L2 transfer. The total flight time as an optimization criterion is considered. The optimal control programs were obtained by using the Pontryagin's maximum principle. As a result of optimization, optimal control programs, corresponding trajectories, and minimal total flight times were determined.

An assessment of staffing needs at a HIV clinic in a Western Kenya using the WHO workload indicators of staffing need WISN, 2011.

PubMed

Burmen, B; Owuor, N; Mitei, P

2017-01-26

An optimal number of health workers, who are appropriately allocated across different occupations and geographical regions, are required to ensure population coverage of health interventions. Health worker shortages in HIV care provision are highest in areas that are worst hit by the HIV epidemic. Kenya is listed among countries that experience health worker shortages (<2.5 health workers per 1000 population) and have a high HIV burden (HIV prevalence 5.6 with 15.2% in Nyanza province). We set out to determine the optimum number of clinicians required to provide quality consultancy HIV care services at the Jaramogi Oginga Odinga Teaching and Referral Hospital, JOOTRH, HIV Clinic, the premier HIV clinic in Nyanza province with a cumulative client enrolment of PLHIV of over 20,000 persons. The World Health's Organization's Workload Indicators of Staffing Needs (WISN) was used to compute the staffing needs and sufficiency of staffing needs at the JOOTRH HIV clinic in Kisumu, Kenya, between January and December 2011. All people living with HIV (PLHIV) who received HIV care services at the HIV clinic at JOOTRH and all the clinicians attending to them were included in this analysis. The actual staffing was divided by the optimal staff requirement to give ratios of staffing excesses or shortages. A ratio of 1.0 indicated optimal staffing, less than 1.0 indicated suboptimal staffing, and more than 1 indicated supra optimal staffing. The HIV clinic is served by 56 staff of various cadres. Clinicians (doctors and clinical officers) comprise approximately one fifth of this population (n = 12). All clinicians (excluding the clinic manager, who is engaged in administrative duties and supervisory roles that consumes approximately one third of his time) provide full-time consultancy services. To operate at maximum efficiency, the clinic therefore requires 19 clinicians. The clinic therefore operates with only 60% of its staffing requirements. Our assessment revealed a severe shortage of clinicians providing consultation services at the HIV clinic. Human resources managers should oversee the rational planning, training, retention, and management of human resources for health using the WISN which is an objective and reliable means of estimating staffing needs.

An optimized computational method for determining the beta dose distribution using a multiple-element thermoluminescent dosimeter system.

PubMed

Shen, L; Levine, S H; Catchen, G L

1987-07-01

This paper describes an optimization method for determining the beta dose distribution in tissue, and it describes the associated testing and verification. The method uses electron transport theory and optimization techniques to analyze the responses of a three-element thermoluminescent dosimeter (TLD) system. Specifically, the method determines the effective beta energy distribution incident on the dosimeter system, and thus the system performs as a beta spectrometer. Electron transport theory provides the mathematical model for performing the optimization calculation. In this calculation, parameters are determined that produce calculated doses for each of the chip/absorber components in the three-element TLD system. The resulting optimized parameters describe an effective incident beta distribution. This method can be used to determine the beta dose specifically at 7 mg X cm-2 or at any depth of interest. The doses at 7 mg X cm-2 in tissue determined by this method are compared to those experimentally determined using an extrapolation chamber. For a great variety of pure beta sources having different incident beta energy distributions, good agreement is found. The results are also compared to those produced by a commonly used empirical algorithm. Although the optimization method produces somewhat better results, the advantage of the optimization method is that its performance is not sensitive to the specific method of calibration.

The Functional Movement Screen and Injury Risk: Association and Predictive Value in Active Men.

PubMed

Bushman, Timothy T; Grier, Tyson L; Canham-Chervak, Michelle; Anderson, Morgan K; North, William J; Jones, Bruce H

2016-02-01

The Functional Movement Screen (FMS) is a series of 7 tests used to assess the injury risk in active populations. To determine the association of the FMS with the injury risk, assess predictive values, and identify optimal cut points using 3 injury types. Cohort study; Level of evidence, 2. Physically active male soldiers aged 18 to 57 years (N = 2476) completed the FMS. Demographic and fitness data were collected by survey. Medical record data for overuse injuries, traumatic injuries, and any injury 6 months after the FMS assessment were obtained. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated along with the receiver operating characteristic (ROC) to determine the area under the curve (AUC) and identify optimal cut points for the risk assessment. Risks, risk ratios (RRs), odds ratios (ORs), and 95% CIs were calculated to assess injury risks. Soldiers who scored ≤14 were at a greater risk for injuries compared with those who scored >14 using the composite score for overuse injuries (RR, 1.84; 95% CI, 1.63-2.09), traumatic injuries (RR, 1.26; 95% CI, 1.03-1.54), and any injury (RR, 1.60; 95% CI, 1.45-1.77). When controlling for other known injury risk factors, multivariate logistic regression analysis identified poor FMS performance (OR [score ≤14/19-21], 2.00; 95% CI, 1.42-2.81) as an independent risk factor for injuries. A cut point of ≤14 registered low measures of predictive value for all 3 injury types (sensitivity, 28%-37%; PPV, 19%-52%; AUC, 54%-61%). Shifting the injury risk cut point of ≤14 to the optimal cut points indicated by the ROC did not appreciably improve sensitivity or the PPV. Although poor FMS performance was associated with a higher risk of injuries, it displayed low sensitivity, PPV, and AUC. On the basis of these findings, the use of the FMS to screen for the injury risk is not recommended in this population because of the low predictive value and misclassification of the injury risk. © 2015 The Author(s).

Laser pulses for coherent xuv Raman excitation

NASA Astrophysics Data System (ADS)

Greenman, Loren; Koch, Christiane P.; Whaley, K. Birgitta

2015-07-01

We combine multichannel electronic structure theory with quantum optimal control to derive femtosecond-time-scale Raman pulse sequences that coherently populate a valence excited state. For a neon atom, Raman target populations of up to 13% are obtained. Superpositions of the ground and valence Raman states with a controllable relative phase are found to be reachable with up to 4.5% population and arbitrary phase control facilitated by the pump pulse carrier-envelope phase. Analysis of the optimized pulse structure reveals a sequential mechanism in which the valence excitation is reached via a fast (femtosecond) population transfer through an intermediate resonance state in the continuum rather than avoiding intermediate-state population with simultaneous or counterintuitive (stimulated Raman adiabatic passage) pulse sequences. Our results open a route to coupling valence excitations and core-hole excitations in molecules and aggregates that locally address specific atoms and represent an initial step towards realization of multidimensional spectroscopy in the xuv and x-ray regimes.

Particle Swarm Optimization Toolbox

NASA Technical Reports Server (NTRS)

Grant, Michael J.

2010-01-01

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

Two-step optimization of pressure and recovery of reverse osmosis desalination process.

PubMed

Liang, Shuang; Liu, Cui; Song, Lianfa

2009-05-01

Driving pressure and recovery are two primary design variables of a reverse osmosis process that largely determine the total cost of seawater and brackish water desalination. A two-step optimization procedure was developed in this paper to determine the values of driving pressure and recovery that minimize the total cost of RO desalination. It was demonstrated that the optimal net driving pressure is solely determined by the electricity price and the membrane price index, which is a lumped parameter to collectively reflect membrane price, resistance, and service time. On the other hand, the optimal recovery is determined by the electricity price, initial osmotic pressure, and costs for pretreatment of raw water and handling of retentate. Concise equations were derived for the optimal net driving pressure and recovery. The dependences of the optimal net driving pressure and recovery on the electricity price, membrane price, and costs for raw water pretreatment and retentate handling were discussed.

Multi-objective route planning for dangerous goods using compromise programming

NASA Astrophysics Data System (ADS)

Li, Rongrong; Leung, Yee

2011-09-01

The transportation of dangerous goods (DG) can significantly affect the human and natural environment if accidents occur during the transportation process. Hong Kong is a large city with high population density and narrow streets. Due to the land constraints, vehicles carrying DG inevitably have to pass through densely populated areas or their vicinities. Therefore, safe DG transportation is of paramount importance. There is thus an urgent need to review and improve the way trucks carrying DG are being routed on the road networks. Routing of such vehicles should consider not only the operating cost, but also the safety of travelers in the network, the population potentially exposed, and the possible damage inflicted to the surrounding properties and facilities in the event of a DG incident. This research develops a novel methodology for the determination of optimal routes for DG transportation under conflicting objectives by means of the compromise programming approach. With the support of geographical information system (GIS), a case study is carried out for the transportation of DG in the road network of Hong Kong. The experimental results confirm the effectiveness of the proposed approach.

Analysis of Prey-Predator Three Species Fishery Model with Harvesting Including Prey Refuge and Migration

NASA Astrophysics Data System (ADS)

Roy, Sankar Kumar; Roy, Banani

In this article, a prey-predator system with Holling type II functional response for the predator population including prey refuge region has been analyzed. Also a harvesting effort has been considered for the predator population. The density-dependent mortality rate for the prey, predator and super predator has been considered. The equilibria of the proposed system have been determined. Local and global stabilities for the system have been discussed. We have used the analytic approach to derive the global asymptotic stabilities of the system. The maximal predator per capita consumption rate has been considered as a bifurcation parameter to evaluate Hopf bifurcation in the neighborhood of interior equilibrium point. Also, we have used fishing effort to harvest predator population of the system as a control to develop a dynamic framework to investigate the optimal utilization of the resource, sustainability properties of the stock and the resource rent is earned from the resource. Finally, we have presented some numerical simulations to verify the analytic results and the system has been analyzed through graphical illustrations.

Evolutionary game theory using agent-based methods.

PubMed

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Strategies and trajectories of coral reef fish larvae optimizing self-recruitment.

PubMed

Irisson, Jean-Olivier; LeVan, Anselme; De Lara, Michel; Planes, Serge

2004-03-21

Like many marine organisms, most coral reef fishes have a dispersive larval phase. The fate of this phase is of great concern for their ecology as it may determine population demography and connectivity. As direct study of the larval phase is difficult, we tackle the question of dispersion from an opposite point of view and study self-recruitment. In this paper, we propose a mathematical model of the pelagic phase, parameterized by a limited number of factors (currents, predator and prey distributions, energy budgets) and which focuses on the behavioral response of the larvae to these factors. We evaluate optimal behavioral strategies of the larvae (i.e. strategies that maximize the probability of return to the natal reef) and examine the trajectories of dispersal that they induce. Mathematically, larval behavior is described by a controlled Markov process. A strategy induces a sequence, indexed by time steps, of "decisions" (e.g. looking for food, swimming in a given direction). Biological, physical and topographic constraints are captured through the transition probabilities and the sets of possible decisions. Optimal strategies are found by means of the so-called stochastic dynamic programming equation. A computer program is developed and optimal decisions and trajectories are numerically derived. We conclude that this technique can be considered as a good tool to represent plausible larval behaviors and that it has great potential in terms of theoretical investigations and also for field applications.

Unification theory of optimal life histories and linear demographic models in internal stochasticity.

PubMed

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of "Stochastic Control Theory" in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path-integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models.

Unification Theory of Optimal Life Histories and Linear Demographic Models in Internal Stochasticity

PubMed Central

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of “Stochastic Control Theory” in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path–integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models. PMID:24945258

Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping

NASA Astrophysics Data System (ADS)

Balakrishnan, D.; Quan, C.; Tay, C. J.

2013-06-01

The phase unwrapping is the final and trickiest step in any phase retrieval technique. Phase unwrapping by artificial intelligence methods (optimization algorithms) such as hybrid genetic algorithm, reverse simulated annealing, particle swarm optimization, minimum cost matching showed better results than conventional phase unwrapping methods. In this paper, Ensemble of hybrid genetic algorithm with parallel populations is proposed to solve the branch-cut phase unwrapping problem. In a single populated hybrid genetic algorithm, the selection, cross-over and mutation operators are applied to obtain new population in every generation. The parameters and choice of operators will affect the performance of the hybrid genetic algorithm. The ensemble of hybrid genetic algorithm will facilitate to have different parameters set and different choice of operators simultaneously. Each population will use different set of parameters and the offspring of each population will compete against the offspring of all other populations, which use different set of parameters. The effectiveness of proposed algorithm is demonstrated by phase unwrapping examples and advantages of the proposed method are discussed.

Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies

USGS Publications Warehouse

Rizzo, Austin A.; Brown, Donald J.; Welsh, Stuart A.; Thompson, Patricia A.

2017-01-01

Population monitoring is an essential component of endangered species recovery programs. The federally endangered Diamond Darter Crystallaria cincotta is in need of an effective monitoring design to improve our understanding of its distribution and track population trends. Because of their small size, cryptic coloration, and nocturnal behavior, along with limitations associated with current sampling methods, individuals are difficult to detect at known occupied sites. Therefore, research is needed to determine if survey efforts can be improved by increasing probability of individual detection. The primary objective of this study was to determine if there are seasonal and diel patterns in Diamond Darter detectability during population surveys. In addition to temporal factors, we also assessed five habitat variables that might influence individual detection. We used N-mixture models to estimate site abundances and relationships between covariates and individual detectability and ranked models using Akaike's information criteria. During 2015 three known occupied sites were sampled 15 times each between May and Oct. The best supported model included water temperature as a quadratic function influencing individual detectability, with temperatures around 22 C resulting in the highest detection probability. Detection probability when surveying at the optimal temperature was approximately 6% and 7.5% greater than when surveying at 16 C and 29 C, respectively. Time of Night and day of year were not strong predictors of Diamond Darter detectability. The results of this study will allow researchers and agencies to maximize detection probability when surveying populations, resulting in greater monitoring efficiency and likely more precise abundance estimates.

Review of fall risk assessment in geriatric populations using inertial sensors

PubMed Central

2013-01-01

Background Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Methods Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Results Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Conclusions Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls. PMID:23927446

Do Optimal Prognostic Thresholds in Continuous Physiological Variables Really Exist? Analysis of Origin of Apparent Thresholds, with Systematic Review for Peak Oxygen Consumption, Ejection Fraction and BNP

PubMed Central

Leong, Tora; Rehman, Michaela B.; Pastormerlo, Luigi Emilio; Harrell, Frank E.; Coats, Andrew J. S.; Francis, Darrel P.

2014-01-01

Background Clinicians are sometimes advised to make decisions using thresholds in measured variables, derived from prognostic studies. Objectives We studied why there are conflicting apparently-optimal prognostic thresholds, for example in exercise peak oxygen uptake (pVO2), ejection fraction (EF), and Brain Natriuretic Peptide (BNP) in heart failure (HF). Data Sources and Eligibility Criteria Studies testing pVO2, EF or BNP prognostic thresholds in heart failure, published between 1990 and 2010, listed on Pubmed. Methods First, we examined studies testing pVO2, EF or BNP prognostic thresholds. Second, we created repeated simulations of 1500 patients to identify whether an apparently-optimal prognostic threshold indicates step change in risk. Results 33 studies (8946 patients) tested a pVO2 threshold. 18 found it prognostically significant: the actual reported threshold ranged widely (10–18 ml/kg/min) but was overwhelmingly controlled by the individual study population's mean pVO2 (r = 0.86, p<0.00001). In contrast, the 15 negative publications were testing thresholds 199% further from their means (p = 0.0001). Likewise, of 35 EF studies (10220 patients), the thresholds in the 22 positive reports were strongly determined by study means (r = 0.90, p<0.0001). Similarly, in the 19 positives of 20 BNP studies (9725 patients): r = 0.86 (p<0.0001). Second, survival simulations always discovered a “most significant” threshold, even when there was definitely no step change in mortality. With linear increase in risk, the apparently-optimal threshold was always near the sample mean (r = 0.99, p<0.001). Limitations This study cannot report the best threshold for any of these variables; instead it explains how common clinical research procedures routinely produce false thresholds. Key Findings First, shifting (and/or disappearance) of an apparently-optimal prognostic threshold is strongly determined by studies' average pVO2, EF or BNP. Second, apparently-optimal thresholds always appear, even with no step in prognosis. Conclusions Emphatic therapeutic guidance based on thresholds from observational studies may be ill-founded. We should not assume that optimal thresholds, or any thresholds, exist. PMID:24475020

Energetics of growth and reproduction in a high-tidal population of the clam Ruditapes decussatus from Urdaibai Estuary (Basque Country, N. Spain)

NASA Astrophysics Data System (ADS)

Urrutia, M. B.; Ibarrola, I.; Iglesias, J. I. P.; Navarro, E.

1999-08-01

Energetics of growth and reproduction were studied in a high-tidal population of the clam Ruditapes decussatus living in the Mundaka Estuary in the Biosphere Reserve of Urdaibai (Basque Country, North Spain). The study included an analysis of growth rings on the shells to establish the growth curve as well as seasonal patterns of growth and body condition, and estimates of the breeding cycle including quantification of the reproductive output and reproductive effort. The simultaneous determination of the seasonal course of metabolism allowed estimates of assimilation, growth efficiency and reproductive costs. Growth rates were consistently lower in this population than in other populations from similar latitudes, and this effect is interpreted in terms of nutritional restrictions caused by the high tidal position of the population. Assimilation rapidly increased from March to July, as a consequence of optimal nutritional conditions and increasing water temperatures. Somatic growth (spring) and gonadal development (early summer) both took place during this period. Negative growth was restricted to the winter and late summer and was associated with poor nutritional conditions (winter) and high rates of metabolic expenditure induced by high temperatures (late summer). Net growth efficiencies (ranging from 27% in 1-y-old to 6% in 7-y-old individuals) ranked among the lowest recorded for populations of marine bivalves. Reduced reproductive-effort values were consistent with the poor growing conditions that appeared to characterise this population of clams.

Citizen Science: Participatory Monitoring of Water Resources Management in Mustang District, Nepal

NASA Astrophysics Data System (ADS)

Regmi, S.; Bhusal, J.; Gurung, P.; Ochoa-Tocachi, B. F.; Buytaert, W.

2016-12-01

Abstract The Mustang region of the Himalayas has unique geographical and climatic features. This region is characterized by a cold-arid climate with total annual precipitation of less than 300mm. Agriculture and livestock grazing lands are the major ecosystem services, which support directly the livelihoods of local populations yet, are strongly determined by low water availability. As a result, optimizing water resources management is paramount to support local development, but this is severely complicated by the lack of information about water availability. This problem is further aggravated by increasing pressure on the social, physical and climatic environments. In order to support the management of scarce water in irrigation and domestic uses, stream flow and precipitation monitoring networks were established using a participatory approach under the principle of citizen science. Data collection, and the following interpretation and application of the co-generated knowledge relies on local users, whereas the establishment of the system, knowledge co-generation, and development of application tools particularly is part of a collaboration of members of the general public with professional scientists. We show how the resulting data enable local users to quantify the water balance in the area and reduce the uncertainty associated to data-scarcity, which leads to the generation of useable information about water availability for irrigation, livestock grazing, and domestic demand. We contrast the current scenario of water use, under different conditions of natural variability and environmental change, with an optimized water management strategy generated and agreed with local users. This approach contributes to an optimal use of water, to an improvement in ecosystem services supporting to livelihood development and economic progress of local populations. Key words: ecosystem services, climate change, water balance, knowledge generation, irrigation

[Emergency care in the autonomous regions of Spain. Improvement in pre-hospital emergency care and welfare coordination. SESPAS Report 2012].

PubMed

Miguel García, Félix; Fernández Quintana, Ana Isabel; Díaz Prats, Amadeo

2012-03-01

The present article describes the general organization of pre-hospital emergency care in the autonomous regions and provides data on activity corresponding to 2010, drawn from the information available in the Primary Care Information System of the Ministry of Health, Social Policy and Equality. Emergency care is provided through various organizational structures covering 24-hour periods. Family medicine attended 17.8 million emergency consultations and nursing attended 10.2 million (year 2010, 14 autonomous communities, 79.7% of the National Health System population). Emergency department utilization ranged between 0.11 and 0.83 urgent family physician consultations per inhabitant/year and between 0.05 and 0.57 nursing consultations per inhabitant/year. Any reform in the management of pre-hospital emergency care will involve organizational changes and aims to produce measurable improvements in healthcare coordination. In the new organizational designs, most of the responsibility lies with human resources in order to achieve the new goals for the future aims to be presented in an operational teamwork structure. Undoubtedly, the main challenge is to achieve optimal coordination with other welfare levels, including the police, social services, nursing homes, etc. If optimal care of the population needs to count on the efforts of all these groups, mobility, individual differences, consistent achievement of high standards, and -most of all- the use of these services by citizens will determine the final result. The results can be quantified in various ways, but evaluation should concentrate on the resources used, the degree of satisfaction among all the parties involved and optimal management of demand, which will help to disseminate the need for a rational resource use. Copyright © 2011 SESPAS. Published by Elsevier Espana. All rights reserved.

Selecting optimal second-generation antihistamines for allergic rhinitis and urticaria in Asia.

PubMed

Recto, Marysia Tiongco; Gabriel, Ma Teresita; Kulthanan, Kanokvalai; Tantilipikorn, Pongsakorn; Aw, Derrick Chen-Wee; Lee, Tak Hong; Chwen, Ch'ng Chin; Mutusamy, Somasundran; Hao, Nguyen Trong; Quang, Vo Thanh; Canonica, Giorgio Walter

2017-01-01

Allergic diseases are on the rise in many parts of the world, including the Asia-Pacific (APAC) region. Second-generation antihistamines are the first-line treatment option in the management of allergic rhinitis and urticaria. International guidelines describe the management of these conditions; however, clinicians perceive the additional need to tailor treatment according to patient profiles. This study serves as a consensus of experts from several countries in APAC (Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam), which aims to describe the unmet needs, practical considerations, challenges, and key decision factors when determining optimal second-generation antihistamines for patients with allergic rhinitis and/or urticaria. Specialists from allergology, dermatology, and otorhinolaryngology were surveyed on practical considerations and key decision points when treating patients with allergic rhinitis and/or urticaria. Clinicians felt the need for additional tools for diagnosis of these diseases and a single drug with all preferred features of an antihistamine. Challenges in treatment include lack of clinician and patient awareness and compliance, financial constraints, and treatment for special patient populations such as those with concomitant disease. Selection of optimal second-generation antihistamines depends on many factors, particularly drug safety and efficacy, impact on psychomotor abilities, and sedation. Country-specific considerations include drug availability and cost-effectiveness. Survey results reveal bilastine as a preferred choice due to its high efficacy and safety, suitability for special patient populations, and the lack of sedative effects. Compliance to the international guidelines is present among allergists, dermatologists and otorhinolaryngologists; however, this is lower amongst general practitioners (GPs). To increase awareness, allergy education programs targeted at GPs and patients may be beneficial. Updates to the existing international guidelines are suggested in APAC to reflect appropriate management for different patient profiles and varying symptoms of allergic rhinitis and urticaria.

Long-Term Preservation of Left Ventricular Systolic Function in Patients With Refractory Angina Pectoris and Inducible Myocardial Ischemia on Optimal Medical Therapy.

PubMed

Slavich, Massimo; Maranta, Francesco; Fumero, Andrea; Godino, Cosmo; Giannini, Francesco; Oppizzi, Michele; Colombo, Antonio; Fragasso, Gabriele; Margonato, Alberto

2016-05-15

Refractory angina pectoris (RAP) represents a clinical condition characterized by frequent episodes of chest pain despite therapy optimization. According to myocardial stunning and myocardial hibernation definitions, RAP should represent the ideal condition for systolic dysfunction development. We aim to investigate the evolution of left ventricular (LV) function in patients with RAP. A retrospective study which encompasses 144 patients with RAP referred to our institution from 1999 to December 2014 was performed. Of them, 88 met the inclusion criteria, and LV function was assessed by echocardiography. All of them had persistent angina episodes on top of optimal medical therapy and evidence of significant inducible myocardial ischemia and no further revascularization options. Nitrates consumption rate, time of angina duration, and the number of angina attacks were evaluated. In the whole population, ejection fraction (EF) was 44% ± 2. EF was significantly lower in patients with previous myocardial infarction (41% ± 1.5 vs 51% ± 1.8, p <0.0001). The duration time and the number of angina attacks did not correlate with EF in the whole population and in patients without previous myocardial infarction. In patients with previous myocardial infarction, the number of anginal attacks did not correlate with EF, but EF appeared higher in patients with angina duration >5 years (<5 years EF 37% ± 1 [n = 26]; >5 years 44% ± 2 [n = 44]; p 0.02). Long-term LV function in patients with RAP is generally preserved. A previous history of myocardial infarction is the only determinant in the development of systolic dysfunction. In conclusion, frequent angina attacks and a long-term history of angina are not apparently associated to worse LV function. Copyright © 2016 Elsevier Inc. All rights reserved.

Evolutionary speed of species invasions.

PubMed

García-Ramos, Gisela; Rodríguez, Diego

2002-04-01

Successful invasion may depend of the capacity of a species to adjust genetically to a spatially varying environment. This research modeled a species invasion by examining the interaction between a quantitative genetic trait and population density. It assumed: (I) a quantitative genetic trait describes the adaptation of an individual to its local ecological conditions; (2) populations far from the local optimum grow more slowly than those near the optimum; and (3) the evolution of a trait depends on local population density, because differences in local population densities cause asymmetrical gene flow. This genetics-density interaction determined the propagation speed of populations. Numerical simulations showed that populations spread by advancing as two synchronic traveling waves, one for population density and one for trait adaptation. The form of the density wave was a step front that advances homogenizing populations at their carrying capacity; the adaptation wave was a curve with finite slope that homogenizes populations at full adaptation. The largest speed of population expansion, for a dimensionless analysis, corresponded to an almost homogeneous spatial environment when this model approached an ecological description such as the Fisher-Skellam's model. A large genetic response also favored faster speeds. Evolutionary speeds, in a natural scale, showed a wide range of rates that were also slower compared to models that only consider demographics. This evolutionary speed increased with high heritability, strong stabilizing selection, and high intrinsic growth rate. It decreased for steeper environmental gradients. Also indicated was an optimal dispersal rate over which evolutionary speed declined. This is expected because dispersal moves individuals further, but homogenizes populations genetically, making them maladapted. The evolutionary speed was compared to observed data. Furthermore, a moderate increase in the speed of expansion was predicted for ecological changes related to global warming.

Optimizing human activity patterns using global sensitivity analysis.

PubMed

Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M

2014-12-01

Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.

Optimizing human activity patterns using global sensitivity analysis

PubMed Central

Hickmann, Kyle S.; Mniszewski, Susan M.; Del Valle, Sara Y.; Hyman, James M.

2014-01-01

Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule’s regularity for a population. We show how to tune an activity’s regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations. PMID:25580080

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding

NASA Astrophysics Data System (ADS)

Susemihl, Alex; Meir, Ron; Opper, Manfred

2013-03-01

Neurons in the nervous system convey information to higher brain regions by the generation of spike trains. An important question in the field of computational neuroscience is how these sensory neurons encode environmental information in a way which may be simply analyzed by subsequent systems. Many aspects of the form and function of the nervous system have been understood using the concepts of optimal population coding. Most studies, however, have neglected the aspect of temporal coding. Here we address this shortcoming through a filtering theory of inhomogeneous Poisson processes. We derive exact relations for the minimal mean squared error of the optimal Bayesian filter and, by optimizing the encoder, obtain optimal codes for populations of neurons. We also show that a class of non-Markovian, smooth stimuli are amenable to the same treatment, and provide results for the filtering and prediction error which hold for a general class of stochastic processes. This sets a sound mathematical framework for a population coding theory that takes temporal aspects into account. It also formalizes a number of studies which discussed temporal aspects of coding using time-window paradigms, by stating them in terms of correlation times and firing rates. We propose that this kind of analysis allows for a systematic study of temporal coding and will bring further insights into the nature of the neural code.

Characterizing the Survey Strategy and Initial Orbit Determination Abilities of the NASA MCAT Telescope for Geosynchronous Orbital Debris Environmental Studies

NASA Astrophysics Data System (ADS)

Frith, J.; Barker, E.; Cowardin, H.; Buckalew, B.; Anz-Meador, P.; Lederer, S.

The National Aeronautics and Space Administration (NASA) Orbital Debris Program Office (ODPO) recently commissioned the Meter Class Autonomous Telescope (MCAT) on Ascension Island with the primary goal of obtaining population statistics of the geosynchronous (GEO) orbital debris environment. To help facilitate this, studies have been conducted using MCAT’s known and projected capabilities to estimate the accuracy and timeliness in which it can survey the GEO environment, including collected weather data and the proposed observational data collection cadence. To optimize observing cadences and probability of detection, on-going work using a simulated GEO debris population sampled at various cadences are run through the Constrained Admissible Region Multi Hypotheses Filter (CAR-MHF). The orbits computed from the results are then compared to the simulated data to assess MCAT’s ability to determine accurately the orbits of debris at various sample rates. The goal of this work is to discriminate GEO and near-GEO objects from GEO transfer orbit objects that can appear as GEO objects in the environmental models due to the short arc observation and an assumed circular orbit. The specific methods and results are presented here.

Calculation of high-rise construction limitations for non-resident housing fund in megacities

NASA Astrophysics Data System (ADS)

Iliashenko, Oksana; Krasnov, Sergey; Sergeev, Sergey

2018-03-01

The paper is devoted to topical issues of urban planning in terms of high-rise construction of a non-resident housing stock in relation to megacities. We consider this issue taking into account the limitations of natural, communal and social resources. The problem is especially acute for the overwhelming majority of the state capitals, as well as cities with historical heritage that are of great interest due to the rapid development of tourism and the high mobility of the population in the world. The growth of the population of many states capitals led to the use of high-rise buildings as a non-resident housing stock. However, there are a number of restrictions on the high-rise construction of non-resident housing stock in megacities. The authors formalize the problem of determining the optimal ratio of the volume of urban buildings belonging to the high-rise buildings types and intended for non-residents to a common housing fund. We conduct economic calculations to determine the quantitative indicators. It can be used as the basis for administrative measures aimed at limiting the people flow arriving with the intention of temporarily deploying in megacities.

Cellular therapies for heart disease: unveiling the ethical and public policy challenges.

PubMed

Raval, Amish N; Kamp, Timothy J; Hogle, Linda F

2008-10-01

Cellular therapies have emerged as a potential revolutionary treatment for cardiovascular disease. Promising preclinical results have resulted in a flurry of basic research activity and spawned multiple clinical trials worldwide. However, the optimal cell type and delivery mode have not been determined for target patient populations. Nor have the mechanisms of benefit for the range of cellular interventions been clearly defined. Experiences to date have unveiled a myriad of ethical and public policy challenges which will affect the way researchers and clinicians make decisions for both basic and clinical research. Stem cells derived from embryos are at the forefront of the ethical and political debate, raising issues of which derivation methods are morally and socially permissible to pursue, as much as which are technically feasible. Adult stem cells are less controversial; however, important challenges exist in determining study design, cell processing, delivery mode, and target patient population. Pathways to successful commercialization and hence broad accessibility of cellular therapies for heart disease are only beginning to be explored. Comprehensive, multi-disciplinary and collaborative networks involving basic researchers, clinicians, regulatory officials and policymakers are required to share information, develop research, regulatory and policy standards and enable rational and ethical cell-based treatment approaches.

Selecting at-risk populations for sexually transmitted disease/HIV intervention studies.

PubMed

Wu, Zunyou; Rotheram-Borus, Mary Jane; Detels, Roger; Li, Li; Guan, Jihui; Liang, Guojun; Yap, Lorraine

2007-12-01

This paper describes one option to select populations for randomized, controlled trials (RCT). We used a popular opinion leader intervention in Fuzhou, China, to: (1) identify population selection criteria; (2) systematically examine the suitability of potential target populations and settings; (3) briefly evaluate risk and stability in the population; and (4) evaluate regional and organizational support among administrators and government officials. After comparing migrant villagers, truck drivers, factory workers, construction workers, and market employees in five regions of China, market employees in Fuzhou were identified as the optimal target population. Markets were the optimal sites for several reasons: (1) the population demonstrated a sufficient base rate of sexually transmitted diseases; (2) the population was stable over time; (3) a sufficient number of sites of manageable sizes were available; (4) stable networks existed; (5) local gatekeepers/stakeholders supported the intervention; (6) there was organizational capacity in the local health department to mount the intervention; (7) the demographic profile was similar across potential sites; and (8) the sites were sufficiently distanced to minimize contamination. Evaluating intervention efficacy in an RCT requires a time-consuming and rigorous process that systematically and routinely documents selection criteria, evaluates multiple populations, sites, and organizations for their appropriateness.

Constrained minimization problems for the reproduction number in meta-population models.

PubMed

Poghotanyan, Gayane; Feng, Zhilan; Glasser, John W; Hill, Andrew N

2018-02-14

The basic reproduction number ([Formula: see text]) can be considerably higher in an SIR model with heterogeneous mixing compared to that from a corresponding model with homogeneous mixing. For example, in the case of measles, mumps and rubella in San Diego, CA, Glasser et al. (Lancet Infect Dis 16(5):599-605, 2016. https://doi.org/10.1016/S1473-3099(16)00004-9 ), reported an increase of 70% in [Formula: see text] when heterogeneity was accounted for. Meta-population models with simple heterogeneous mixing functions, e.g., proportionate mixing, have been employed to identify optimal vaccination strategies using an approach based on the gradient of the effective reproduction number ([Formula: see text]), which consists of partial derivatives of [Formula: see text] with respect to the proportions immune [Formula: see text] in sub-groups i (Feng et al. in J Theor Biol 386:177-187, 2015.  https://doi.org/10.1016/j.jtbi.2015.09.006 ; Math Biosci 287:93-104, 2017.  https://doi.org/10.1016/j.mbs.2016.09.013 ). These papers consider cases in which an optimal vaccination strategy exists. However, in general, the optimal solution identified using the gradient may not be feasible for some parameter values (i.e., vaccination coverages outside the unit interval). In this paper, we derive the analytic conditions under which the optimal solution is feasible. Explicit expressions for the optimal solutions in the case of [Formula: see text] sub-populations are obtained, and the bounds for optimal solutions are derived for [Formula: see text] sub-populations. This is done for general mixing functions and examples of proportionate and preferential mixing are presented. Of special significance is the result that for general mixing schemes, both [Formula: see text] and [Formula: see text] are bounded below and above by their corresponding expressions when mixing is proportionate and isolated, respectively.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

PubMed

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018 Institute of Physics and Engineering in Medicine.

Bioeconomic analysis supports the endangered species act.

PubMed

Salau, Kehinde R; Fenichel, Eli P

2015-10-01

The United States Endangered Species Act (ESA) was enacted to protect and restore declining fish, wildlife, and plant populations. The ESA mandates endangered species protection irrespective of costs. This translates to the restriction of activities that harm endangered populations. We discuss criticisms of the ESA in the context of public land management and examine under what circumstance banning non-conservation activity on multiple use federal lands can be socially optimal. We develop a bioeconomic model to frame the species management problem under the ESA and identify scenarios where ESA-imposed regulations emerge as optimal strategies. Results suggest that banning harmful activities is a preferred strategy when valued endangered species are in decline or exposed to poor habitat quality. However, it is not optimal to sustain such a strategy in perpetuity. An optimal plan involves a switch to land-use practices characteristic of habitat conservation plans.

A Danger-Theory-Based Immune Network Optimization Algorithm

PubMed Central

Li, Tao; Xiao, Xin; Shi, Yuanquan

2013-01-01

Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853

An opinion formation based binary optimization approach for feature selection

NASA Astrophysics Data System (ADS)

Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

2018-02-01

This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

Optimal control of a rabies epidemic model with a birth pulse.

PubMed

Clayton, Tim; Duke-Sylvester, Scott; Gross, Louis J; Lenhart, Suzanne; Real, Leslie A

2010-01-01

A system of ordinary differential equations describes the population dynamics of a rabies epidemic in raccoons. The model accounts for the dynamics of a vaccine, including loss of vaccine due to animal consumption and loss from factors other than racoon uptake. A control method to reduce the spread of disease is introduced through temporal distribution of vaccine packets. This work incorporates the effect of the seasonal birth pulse in the racoon population and the attendant increase in new-borns which are susceptible to the diseases, analysing the impact of the timing and length of this pulse on the optimal distribution of vaccine packets. The optimization criterion is to minimize the number of infected raccoons while minimizing the cost of distributing the vaccine. Using an optimal control setting, numerical results illustrate strategies for distributing the vaccine depending on the timing of the infection outbreak with respect to the birth pulse.

World Population: U.N. on the Move but Grounds for Optimism Are Scant

ERIC Educational Resources Information Center

Holden, Constance

1974-01-01

Discusses current trends and problems relating to world population, and focuses on action being taken by the United Nations. This year (1974) has been designated World Population Year, and will be highlighted by a conference in Bucharest in which all 130 member governments will meet to confront the issue of population control. (JR)

Mean Field Games for Stochastic Growth with Relative Utility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Minyi, E-mail: mhuang@math.carleton.ca; Nguyen, Son Luu, E-mail: sonluu.nguyen@upr.edu

This paper considers continuous time stochastic growth-consumption optimization in a mean field game setting. The individual capital stock evolution is determined by a Cobb–Douglas production function, consumption and stochastic depreciation. The individual utility functional combines an own utility and a relative utility with respect to the population. The use of the relative utility reflects human psychology, leading to a natural pattern of mean field interaction. The fixed point equation of the mean field game is derived with the aid of some ordinary differential equations. Due to the relative utility interaction, our performance analysis depends on some ratio based approximation errormore » estimate.« less

Life quality and living standards in big cities under conditions of high-rise construction development

NASA Astrophysics Data System (ADS)

Avdeeva, Elena; Averina, Tatiana; Kochetova, Larisa

2018-03-01

Modern urbanization processes occurring on a global scale inevitably lead to an increase in population density in large cities. People assess the state of life quality and living standards of megalopolises under conditions of high-rise construction development ambiguously. Using SWOT analysis, the authors distinguished positive and negative aspects of high-rise construction, highlighted threats to its development and its opportunities. The article considers the model of development of the city's industry and infrastructure, which enables determining the optimal volume of production by sectors and branches of city economy in order to increase its innovative, production and economic potential and business activity.

How to allocate limited healthcare resources: Lessons from the introduction of antiretroviral therapy in rural Mozambique

PubMed Central

Dodson, Zan M.; Agadjanian, Victor; Driessen, Julia

2016-01-01

Proper allocation of limited healthcare resources is a challenging task for policymakers in developing countries. Allocation of and access to these resources typically varies based on how need is defined, thus determining how individuals access and acquire healthcare. Using the introduction of antiretroviral therapy in southern Mozambique as an example, we examine alternative definitions of need for rural populations and how they might impact the allocation of this vital health service. Our results show that how need is defined matters when allocating limited healthcare resources and the use of need-based metrics can help ensure more optimal distribution of services. PMID:28596630

A general equilibrium model of guest-worker migration: the source-country perspective.

PubMed

Djajic, S; Milbourne, R

1988-11-01

"This paper examines the problem of guest-worker migration from an economy populated by identical, utility-maximizing individuals with finite working lives. The decision to migrate, the rate of saving while abroad, as well as the length of a migrant's stay in the foreign country, are all viewed as part of a solution to an intertemporal optimization problem. In addition to studying the microeconomic aspects of temporary migration, the paper analyses the determinants of the equilibrium flow of migrants, the corresponding domestic wage, and the level of welfare enjoyed by a typical worker. Effects of an emigration tax are also investigated." excerpt

Determination of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls in human serum using programmable-temperature vaporization gas chromatography with high-resolution mass spectrometry.

PubMed

Zhang, Lei; Zhong, Yuxin; Liu, Xin; Bao, Yan; Zhao, Yunfeng; Wu, Yongning; Cai, Zongwei; Li, Jingguang

2017-09-01

The determination of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls in blood from a non-occupational population is essential for the investigation of adverse health effects from these pollutants. In this study, a sensitive method based on programmable-temperature vaporization with large-volume injection coupled with gas chromatography with high-resolution mass spectrometry was developed to determine these pollutants in 1-2 mL of human serum samples. Various key parameters of programmable-temperature vaporization injector, including vent temperature, vent time, vent flow, transfer temperature and transfer time were optimized by factorial design. The accuracy and precision as well as applicability were assessed by determining polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls in calibration standard solutions, standard reference materials and real human serum samples from non-occupational population. The method detection limits of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls were 1.5-9.0 and 0.005-0.02 ng/kg wet weight, respectively. By comparing with typically splitless injection, the application of programmable-temperature vaporization injector could effectively lead to higher detectable rate of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls in 1-2 mL of human serum samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design and optimization of a self-deploying PV tent array

NASA Astrophysics Data System (ADS)

Colozza, Anthony J.

A study was performed to design a self-deploying tent shaped PV (photovoltaic) array and optimize the design for maximum specific power. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces it would be subjected to. Through this analysis the component weights were determined. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power for a given PV blanket. This optimization was performed for both Lunar and Martian environmental conditions. The performance specifications for the array at both locations and with various PV blankets were determined.

Strain gage based determination of mixed mode SIFs

NASA Astrophysics Data System (ADS)

Murthy, K. S. R. K.; Sarangi, H.; Chakraborty, D.

2018-05-01

Accurate determination of mixed mode stress intensity factors (SIFs) is essential in understanding and analysis of mixed mode fracture of engineering components. Only a few strain gage determination of mixed mode SIFs are reported in literatures and those also do not provide any prescription for radial locations of strain gages to ensure accuracy of measurement. The present investigation experimentally demonstrates the efficacy of a proposed methodology for the accurate determination of mixed mode I/II SIFs using strain gages. The proposed approach is based on the modified Dally and Berger's mixed mode technique. Using the proposed methodology appropriate gage locations (optimal locations) for a given configuration have also been suggested ensuring accurate determination of mixed mode SIFs. Experiments have been conducted by locating the gages at optimal and non-optimal locations to study the efficacy of the proposed approach. The experimental results from the present investigation show that highly accurate SIFs (0.064%) can be determined using the proposed approach if the gages are located at the suggested optimal locations. On the other hand, results also show the very high errors (212.22%) in measured SIFs possible if the gages are located at non-optimal locations. The present work thus clearly substantiates the importance of knowing the optimal locations of the strain gages apriori in accurate determination of SIFs.

Traditional foods and 25(OH)D concentrations in a subarctic First Nations community.

PubMed

Mansuri, Sudaba; Badawi, Alaa; Kayaniyil, Sheena; Cole, David E; Harris, Stewart B; Mamakeesick, Mary; Wolever, Thomas; Gittelsohn, Joel; Maguire, Jonathon L; Connelly, Philip W; Zinman, Bernard; Hanley, Anthony J

2016-01-01

Sub-optimal vitamin D status is common worldwide and the condition may be associated with increased risk for various chronic diseases. In particular, low vitamin D status is highly prevalent in indigenous communities in Canada, although limited data are available on the determinants of serum 25-hydroxyvitamin D (25(OH)D) concentrations in this population. The relationship between traditional food consumption and vitamin D status has not been well documented. To investigate the determinants of serum 25(OH)D status in a First Nations community in Ontario, Canada, with a focus on the role of traditional food consumption and activities. A cross-sectional analysis was conducted within the Sandy Lake Health and Diabetes Project (2003-2005). A total of 445 participants (>12 years of age) were assessed for serum 25(OH)D status, anthropometric and lifestyle variables, including traditional and non-traditional dietary practices and activities. Diet patterns were identified using factor analysis, and multivariate linear regression analysis was used to analyse the determinants of 25(OH)D concentrations. Mean serum 25(OH)D concentrations were 22.1 nmol/L (16.9, 29.9 nmol/L) in men and 20.5 nmol/L (16.0, 27.3 nmol/L) in women. Multivariate determinants of higher serum 25(OH)D included higher consumption of traditional and healthier market foods, higher wild fish consumption, male gender, spring/summer season of blood collection and more frequent physical activity. Significant negative determinants included hours of TV/day, higher BMI and higher consumption of unhealthy market foods. Traditional food consumption contributed independently to higher 25(OH)D concentrations in a First Nations community with a high prevalence of sub-optimal vitamin D status.

N-terminal pro-B-type Natriuretic Peptides' Prognostic Utility Is Overestimated in Meta-analyses Using Study-specific Optimal Diagnostic Thresholds.

PubMed

Potgieter, Danielle; Simmers, Dale; Ryan, Lisa; Biccard, Bruce M; Lurati-Buse, Giovanna A; Cardinale, Daniela M; Chong, Carol P W; Cnotliwy, Miloslaw; Farzi, Sylvia I; Jankovic, Radmilo J; Lim, Wen Kwang; Mahla, Elisabeth; Manikandan, Ramaswamy; Oscarsson, Anna; Phy, Michael P; Rajagopalan, Sriram; Van Gaal, William J; Waliszek, Marek; Rodseth, Reitze N

2015-08-01

N-terminal fragment B-type natriuretic peptide (NT-proBNP) prognostic utility is commonly determined post hoc by identifying a single optimal discrimination threshold tailored to the individual study population. The authors aimed to determine how using these study-specific post hoc thresholds impacts meta-analysis results. The authors conducted a systematic review of studies reporting the ability of preoperative NT-proBNP measurements to predict the composite outcome of all-cause mortality and nonfatal myocardial infarction at 30 days after noncardiac surgery. Individual patient-level data NT-proBNP thresholds were determined using two different methodologies. First, a single combined NT-proBNP threshold was determined for the entire cohort of patients, and a meta-analysis conducted using this single threshold. Second, study-specific thresholds were determined for each individual study, with meta-analysis being conducted using these study-specific thresholds. The authors obtained individual patient data from 14 studies (n = 2,196). Using a single NT-proBNP cohort threshold, the odds ratio (OR) associated with an increased NT-proBNP measurement was 3.43 (95% CI, 2.08 to 5.64). Using individual study-specific thresholds, the OR associated with an increased NT-proBNP measurement was 6.45 (95% CI, 3.98 to 10.46). In smaller studies (<100 patients) a single cohort threshold was associated with an OR of 5.4 (95% CI, 2.27 to 12.84) as compared with an OR of 14.38 (95% CI, 6.08 to 34.01) for study-specific thresholds. Post hoc identification of study-specific prognostic biomarker thresholds artificially maximizes biomarker predictive power, resulting in an amplification or overestimation during meta-analysis of these results. This effect is accentuated in small studies.

Study and Optimization of CPT Resonance Parameters in 87 Rb/Ar/Ne Microcells Aimed for Application in Metrology

NASA Astrophysics Data System (ADS)

Masian, Y.; Sivak, A.; Sevostianov, D.; Vassiliev, V.; Velichansky, V.

The paper shows the presents results of studies of small-size rubidium cells with argon and neon buffer gases, produced by a patent pended technique of laser welding [Fishman et al. (2014)]. Cells were designed for miniature frequency standard. Temperature dependence of the frequency of the coherent population trapping (CPT) resonance was measured and used to optimize the ratio of partial pressures of buffer gases. The influence of duration and regime of annealing on the CPT-resonance frequency drift was investigated. The parameters of the FM modulation of laser current for two cases which correspond to the highest amplitude of CPT resonance and to the smallest light shifts of the resonance frequency were determined. The temperature dependences of the CPT resonance frequency were found to be surprisingly different in the two cases. A non-linear dependence of CPT resonance frequency on the temperature of the cell with the two extremes was revealed for one of these cases.

Lower hybrid accessibility in a large, hot reversed field pinch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dziubek, R.A.; Harvey, R.W.; Hokin, S.A.

1995-11-01

Accessibility and damping of the slow wave in a reversed field pinch (RFP) plasma is investigated theoretically, using projected Reversed Field Experiment (RFX) plasma parameters. By numerically solving the hot plasma dispersion relation, regions of propagation are found and the possibility of mode conversion is analyzed. If the parallel index of refraction of the wave is chosen judiciously at the edge of the plasma, the slow wave is accessible to a target region located just inside the reversal surface without mode conversion. Landau damping is also optimized in this region. A representative fast electron population is then added in ordermore » to determine its effect on accessibility and damping. The presence of these electrons, whose parameters were estimated by extrapolation of Madison Symmetric Torus (MST) data, does not affect the accessibility of the wave. However, the initial phase velocity of the wave needs to be increased somewhat in order to maintain optimal damping in the target zone.« less

Developmental contexts and sporting success: birth date and birthplace effects in national hockey league draftees 2000-2005.

PubMed

Baker, Joseph; Logan, A Jane

2007-08-01

To examine relative age and birth place effects in hockey players drafted to play in the National Hockey League (NHL) between 2000 and 2005 and determine whether these factors influenced when players were chosen in the draft. 1013 North American draftees were evaluated from the official NHL website, which provided birthplace, date of birth and selection order in the draft. Population size was collected from Canadian and American census information. Athletes were divided into four quartiles on the basis of selection date to define age cohorts in hockey. Data between the Canadian and American players were also compared to see if the optimal city sizes differed between the two nations. Relative age and birthplace effects were found, although the optimal city size found was dissimilar to that found in previous studies. Further, there were inconsistencies between the Canadian and American data. Contextual factors such as relative age and size of birthplace have a significant effect on likelihood of being selected in the NHL draft.

Maximising functional recovery following hip fracture in frail seniors.

PubMed

Beaupre, Lauren A; Binder, Ellen F; Cameron, Ian D; Jones, C Allyson; Orwig, Denise; Sherrington, Cathie; Magaziner, Jay

2013-12-01

This review discusses factors affecting recovery following hip fracture in frail older people as well as interventions associated with improved functional recovery. Prefracture function, cognitive status, co-morbidities, depression, nutrition and social support impact recovery and may interact to affect post-fracture outcome. There is mounting evidence that exercise is beneficial following hip fracture with higher-intensity/duration programmes showing more promising outcomes. Pharmacologic management for osteoporosis has benefits in preventing further fractures, and interest is growing in pharmacologic treatments for post-fracture loss of muscle mass and strength. A growing body of evidence suggests that sub-populations - those with cognitive impairment, residing in nursing homes or males - also benefit from rehabilitation after hip fracture. Optimal post-fracture care may entail the use of multiple interventions; however, more work is needed to determine optimal exercise components, duration and intensity as well as exploring the impact of multimodal interventions that combine exercise, pharmacology, nutrition and other interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Two distinct DNA sequences recognized by transcription factors represent enthalpy and entropy optima

PubMed Central

Yin, Yimeng; Das, Pratyush K; Jolma, Arttu; Zhu, Fangjie; Popov, Alexander; Xu, You; Nilsson, Lennart

2018-01-01

Most transcription factors (TFs) can bind to a population of sequences closely related to a single optimal site. However, some TFs can bind to two distinct sequences that represent two local optima in the Gibbs free energy of binding (ΔG). To determine the molecular mechanism behind this effect, we solved the structures of human HOXB13 and CDX2 bound to their two optimal DNA sequences, CAATAAA and TCGTAAA. Thermodynamic analyses by isothermal titration calorimetry revealed that both sites were bound with similar ΔG. However, the interaction with the CAA sequence was driven by change in enthalpy (ΔH), whereas the TCG site was bound with similar affinity due to smaller loss of entropy (ΔS). This thermodynamic mechanism that leads to at least two local optima likely affects many macromolecular interactions, as ΔG depends on two partially independent variables ΔH and ΔS according to the central equation of thermodynamics, ΔG = ΔH - TΔS. PMID:29638214

Influence of Sequential vs. Simultaneous Dual-Task Exercise Training on Cognitive Function in Older Adults

PubMed Central

Tait, Jamie L.; Duckham, Rachel L.; Milte, Catherine M.; Main, Luana C.; Daly, Robin M.

2017-01-01

Emerging research indicates that exercise combined with cognitive training may improve cognitive function in older adults. Typically these programs have incorporated sequential training, where exercise and cognitive training are undertaken separately. However, simultaneous or dual-task training, where cognitive and/or motor training are performed simultaneously with exercise, may offer greater benefits. This review summary provides an overview of the effects of combined simultaneous vs. sequential training on cognitive function in older adults. Based on the available evidence, there are inconsistent findings with regard to the cognitive benefits of sequential training in comparison to cognitive or exercise training alone. In contrast, simultaneous training interventions, particularly multimodal exercise programs in combination with secondary tasks regulated by sensory cues, have significantly improved cognition in both healthy older and clinical populations. However, further research is needed to determine the optimal characteristics of a successful simultaneous training program for optimizing cognitive function in older people. PMID:29163146

Maximising functional recovery following hip fracture in frail seniors

PubMed Central

Beaupre, Lauren A.; Binder, Ellen F.; Cameron, Ian D.; Jones, C. Allyson; Orwig, Denise; Sherrington, Cathie; Magaziner, Jay

2015-01-01

This review discusses factors affecting recovery following hip fracture in frail older people as well as interventions associated with improved functional recovery. Prefracture function, cognitive status, co-morbidities, depression, nutrition and social support impact recovery and may interact to affect post-fracture outcome. There is mounting evidence that exercise is beneficial following hip fracture with higher-intensity/duration programmes showing more promising outcomes. Pharmacologic management for osteoporosis has benefits in preventing further fractures, and interest is growing in pharmacologic treatments for post-fracture loss of muscle mass and strength. A growing body of evidence suggests that sub-populations – those with cognitive impairment, residing in nursing homes or males – also benefit from rehabilitation after hip fracture. Optimal post-fracture care may entail the use of multiple interventions; however, more work is needed to determine optimal exercise components, duration and intensity as well as exploring the impact of multimodal interventions that combine exercise, pharmacology, nutrition and other interventions. PMID:24836335

Managing the Cayo Santiago rhesus macaque population: The role of density.

PubMed

Hernandez-Pacheco, Raisa; Delgado, Diana L; Rawlins, Richard G; Kessler, Matthew J; Ruiz-Lambides, Angelina V; Maldonado, Elizabeth; Sabat, Alberto M

2016-01-01

Cayo Santiago is the oldest continuously operating free-ranging rhesus monkey colony in the world. Population control of this colony has historically been carried out by periodic live capture and removal of animals. However, the effect of such a strategy on the size, growth rate, age structure, and sex ratio of the population has not been analyzed. This study reviews past removal data and uses a population projection model to simulate the effects of different removal schemes based on Cayo Santiago demographic data from 2000-2012. The model incorporates negative density-dependence in female fertility, as well as male and female survival rates, to determine the population-level effects of selective removal by age and sex. Modeling revealed that removal of sexually immature individuals has negligible effects on the population dynamics explaining why with an initial population of 1309 in 2000 and annual removals of immature monkeys a mean annual population growth rate of 12% and a final population size of ∼1,435 individuals by 2012 (∼0.009 animal/m(2) ) was observed. With no removals, the population is expected to exhibit dampened oscillations until reaching equilibrium at ∼1,690 individuals (∼0.0111 animal/m(2) ) in 2,100. In contrast, removal of adult females (≥4 yrs) would significantly reduce the population size, but would also promote an increase in population growth rate due to density feedback. A maximum annual production of 275 births is expected when 550 adult females are present in the population. Sensitivity analyses showed that removing females, in contrast to controlling their fertility through invasive treatments would contribute the most to changes in population growth rate. Given the density compensation on fertility, stabilizing the population would require removing ∼80% of the current population of adult females. This study highlights the importance of addressing the population-level density effects, as well as sensitivity analyses, to optimize management strategies. © 2016 Wiley Periodicals, Inc.

Validation of morphing wing methodologies on an unmanned aerial system and a wind tunnel technology demonstrator

NASA Astrophysics Data System (ADS)

Gabor, Oliviu Sugar

To increase the aerodynamic efficiency of aircraft, in order to reduce the fuel consumption, a novel morphing wing concept has been developed. It consists in replacing a part of the wing upper and lower surfaces with a flexible skin whose shape can be modified using an actuation system placed inside the wing structure. Numerical studies in two and three dimensions were performed in order to determine the gains the morphing system achieves for the case of an Unmanned Aerial System and for a morphing technology demonstrator based on the wing tip of a transport aircraft. To obtain the optimal wing skin shapes in function of the flight condition, different global optimization algorithms were implemented, such as the Genetic Algorithm and the Artificial Bee Colony Algorithm. To reduce calculation times, a hybrid method was created by coupling the population-based algorithm with a fast, gradient-based local search method. Validations were performed with commercial state-of-the-art optimization tools and demonstrated the efficiency of the proposed methods. For accurately determining the aerodynamic characteristics of the morphing wing, two new methods were developed, a nonlinear lifting line method and a nonlinear vortex lattice method. Both use strip analysis of the span-wise wing section to account for the airfoil shape modifications induced by the flexible skin, and can provide accurate results for the wing drag coefficient. The methods do not require the generation of a complex mesh around the wing and are suitable for coupling with optimization algorithms due to the computational time several orders of magnitude smaller than traditional three-dimensional Computational Fluid Dynamics methods. Two-dimensional and three-dimensional optimizations of the Unmanned Aerial System wing equipped with the morphing skin were performed, with the objective of improving its performances for an extended range of flight conditions. The chordwise positions of the internal actuators, the spanwise number of actuation stations as well as the displacement limits were established. The performance improvements obtained and the limitations of the morphing wing concept were studied. To verify the optimization results, high-fidelity Computational Fluid Dynamics simulations were also performed, giving very accurate indications of the obtained gains. For the morphing model based on an aircraft wing tip, the skin shapes were optimized in order to control laminar flow on the upper surface. An automated structured mesh generation procedure was developed and implemented. To accurately capture the shape of the skin, a precision scanning procedure was done and its results were included in the numerical model. High-fidelity simulations were performed to determine the upper surface transition region and the numerical results were validated using experimental wind tunnel data.

Using genetic algorithms to optimise current and future health planning--the example of ambulance locations.

PubMed

Sasaki, Satoshi; Comber, Alexis J; Suzuki, Hiroshi; Brunsdon, Chris

2010-01-28

Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations. Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared. The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.

Optimizing Distribution of Pandemic Influenza Antiviral Drugs

PubMed Central

Huang, Hsin-Chan; Morton, David P.; Johnson, Gregory P.; Gutfraind, Alexander; Galvani, Alison P.; Clements, Bruce; Meyers, Lauren A.

2015-01-01

We provide a data-driven method for optimizing pharmacy-based distribution of antiviral drugs during an influenza pandemic in terms of overall access for a target population and apply it to the state of Texas, USA. We found that during the 2009 influenza pandemic, the Texas Department of State Health Services achieved an estimated statewide access of 88% (proportion of population willing to travel to the nearest dispensing point). However, access reached only 34.5% of US postal code (ZIP code) areas containing <1,000 underinsured persons. Optimized distribution networks increased expected access to 91% overall and 60% in hard-to-reach regions, and 2 or 3 major pharmacy chains achieved near maximal coverage in well-populated areas. Independent pharmacies were essential for reaching ZIP code areas containing <1,000 underinsured persons. This model was developed during a collaboration between academic researchers and public health officials and is available as a decision support tool for Texas Department of State Health Services at a Web-based interface. PMID:25625858

Incidence, outcomes, and risk factors for retreatment after wavefront-optimized ablations with PRK and LASIK.

PubMed

Randleman, J Bradley; White, Alfred J; Lynn, Michael J; Hu, Michelle H; Stulting, R Doyle

2009-03-01

To analyze and compare retreatment rates after wavefront-optimized photorefractive keratectomy (PRK) and LASIK and determine risk factors for retreatment. A retrospective chart review was performed to identify patients undergoing PRK or LASIK with the wavefront-optimized WaveLight platform from January 2005 through December 2006 targeted for a piano outcome and to determine the rate and risk factors for retreatment surgery in this population. Eight hundred fifty-five eyes were analyzed, including 70 (8.2%) eyes with hyperopic refractions and 785 (91.8%) eyes with myopic refractions. After initial treatment, 72% of eyes were 20/20 or better and 99.5% were 20/40 or better. To improve uncorrected visual acuity, 54 (6.3%) eyes had retreatments performed. No significant differences in retreatment rates were noted based on age (P = .15), sex (P = .8), eye (P = .3), PRK versus LASIK (P = 1.0), room temperature (P = .1) or humidity (P = .9), and no correlation between retreatment rate and month or season of primary surgery (P = .4). There was no correlation between degree of myopia and retreatment rate. Eyes were significantly more likely to undergo retreatment if they were hyperopic (12.8% vs 6.0%, P = .006) or had astigmatism > or = 1.00 diopter (D) (9.1% vs 5.3%, P = .04). Retreatment rate was 6.3% with the WaveLight ALLEGRETTO WAVE excimer laser. This rate was not influenced by age, sex, corneal characteristics, or environmental factors. Eyes with hyperopic refractions or astigmatism > or = 1.00 D were more likely to undergo retreatment.

Optimal cutoff of the triglyceride to high-density lipoprotein cholesterol  ratio to detect cardiovascular risk factors among Han adults in Xinjiang.

PubMed

Li, Hua-Yin; Chen, Bang-Dang; Ma, Yi-Tong; Yang, Yi-Ning; Ma, Xiang; Liu, Fen; Fu, Zhen-Yan; Xie, Xiang; Li, Xiao-Mei; Pan, Shuo; He, Chun-Hui; Zheng, Ying-Ying; Wu, Yun; Tao, Jing; Dong, Chun-Lan; Wu, Ting-Ting

2016-09-01

To determine whether TG/HDL-C ratio, which has been shown to be an indicator of the metabolic syndrome (MetS) and insulin resistance (IR), can predict cardiovascular risk factors in the Chinese Han population in Xinjiang. The cardiovascular risk survey (CRS) was conducted from October 2007 to March 2010. A total of 14,618 representative participants were selected using a four-stage stratified sampling method. A total of 5757 Han participants were included in the study. The present statistical analysis was restricted to the 5595 Han subjects who had complete anthropometric data. The sensitivity, specificity, and distance on the receiver operating characteristic (ROC) curve in each TG/HDL level were calculated. The shortest distance in the ROC curves was used to determine the optimal cutoff of the TG/HDL-C ratio for detecting cardiovascular risk factors. The prevalence of hypertension, hypercholesterolemia, and hypertriglyceridemia was higher with higher TG/HDL-C ratio for both men and women. The TG/HDL-C ratio was positively associated with systolic blood pressure, diastolic blood pressure, and serum concentrations of total cholesterol. The optimal TG/HDL-C ratio cutoffs for predicting hypertension, dyslipidemia, diabetes, and ≥2 of these risk factors for Han adults in Xinjiang were 1.3, 1.3, 1.4, and 1.4 in men and 0.9, 1.0, 1.0, and 1.1 in women, respectively. The evaluation of TG/HDL-C ratio should be considered for one of cardiovascular risk factor predictors among Han adults in Xinjiang.

Fuel management optimization using genetic algorithms and expert knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1996-09-01

The CIGARO fuel management optimization code based on genetic algorithms is described and tested. The test problem optimized the core lifetime for a pressurized water reactor with a penalty function constraint on the peak normalized power. A bit-string genotype encoded the loading patterns, and genotype bias was reduced with additional bits. Expert knowledge about fuel management was incorporated into the genetic algorithm. Regional crossover exchanged physically adjacent fuel assemblies and improved the optimization slightly. Biasing the initial population toward a known priority table significantly improved the optimization.

Resolving the multiple sequence alignment problem using biogeography-based optimization with multiple populations.

PubMed

Zemali, El-Amine; Boukra, Abdelmadjid

2015-08-01

The multiple sequence alignment (MSA) is one of the most challenging problems in bioinformatics, it involves discovering similarity between a set of protein or DNA sequences. This paper introduces a new method for the MSA problem called biogeography-based optimization with multiple populations (BBOMP). It is based on a recent metaheuristic inspired from the mathematics of biogeography named biogeography-based optimization (BBO). To improve the exploration ability of BBO, we have introduced a new concept allowing better exploration of the search space. It consists of manipulating multiple populations having each one its own parameters. These parameters are used to build up progressive alignments allowing more diversity. At each iteration, the best found solution is injected in each population. Moreover, to improve solution quality, six operators are defined. These operators are selected with a dynamic probability which changes according to the operators efficiency. In order to test proposed approach performance, we have considered a set of datasets from Balibase 2.0 and compared it with many recent algorithms such as GAPAM, MSA-GA, QEAMSA and RBT-GA. The results show that the proposed approach achieves better average score than the previously cited methods.