11,777 research outputs found
Dynamic Energy Budget (DEB) parameters for ensis directus
No full textIn this report a Dynamic Energy Budget (DEB) model for razor clams (Ensis directus) is presented. A DEB model is a generic model describing growth and development of individual organisms as a function of environmental conditions. The DEB model for Ensis directus is based on the standard DEB model. The species specific primary DEB parameters are estimated with the Add_my_pet procedure, using literature data and the results of laboratory experiments with Ensis directus. The performance of the model is demonstrated by theoretical model experiments with varying environmental conditions. In following projects, the model will be used to predict and quantify the effects of sand mining on the shellfish community in the Dutch coastal zone. For this purpose the functional response of the model should be adapted so that the combined effect of changing phytoplankton and suspended sediment concentration on the uptake rate can be simulated
Complete mitochondrial genomes and bacterial metagenomic data from two species of parasitic avian nasal-mites (Rhinonyssidae: Mesostigmata)
No full textNational Science Foundation NSF DEB-1239788, DEB-1342604, DEB-185581
A Tutorial on Evolutionary Multi-Objective Optimization (EMO)
No full textMany real-world search and optimization problems are naturally posed
as non-linear programming problems having multiple objectives.
Due to lack of suitable solution techniques, such problems are
artificially converted into a single-objective problem and solved.
The difficulty arises because such problems give rise to a set
of Pareto-optimal solutions, instead of a single optimum solution.
It then becomes important to find not just one Pareto-optimal
solution but as many of them as possible. Classical methods are
not quite efficient in solving these problems because they require
repetitive applications to find multiple Pareto-optimal solutions
and in some occasions repetitive applications do not guarantee
finding distinct Pareto-optimal solutions. The population approach
of evolutionary algorithms (EAs) allows an efficient way to find
multiple Pareto-optimal solutions simultaneously in a single
simulation run.
In this tutorial, we discussed the following aspects related to
EMO:
1. The basic differences in principle of EMO with classical methods.
2. A gentle introduction to evolutionary algorithms with simple
examples. A simple method of handling constraints was also
discussed.
3. The concept of domination and methods of finding non-dominated
solutions in a population of solutions were discussed.
4. A brief history of the development of EMO is highlighted.
5. A number of main EMO methods (NSGA-II, SPEA and PAES) were
discussed.
6. The advantage of EMO methodologies was discussed by presenting
a number of case studies. They clearly showed the advantage of
finding a number of Pareto-optimal solutions simultaneously.
7. Three advantages of using an EMO methodology were stressed:
(i) For a better decision making (in terms of choosing a
compromised solution) in the presence of multiple solutions
(ii) For finding important relationships among decision variables
(useful in design optimization). Some case studies from engineering
demonstrated the importance of such studies.
(iii) For solving other optimization problems efficiently. For
example, in solving genetic programming problems, the so-called
`bloating problem of increased program size can be solved by using
a second objective of minimizing the size of the programs.
8. A number of salient research topics were highlighted. Some of
them are as follows:
(i) Development of scalable test problems
(ii) Development of computationally fast EMO methods
(iii) Performance metrics for evaluating EMO methods
(iv) Interactive EMO methodologies
(v) Robust multi-objective optimization procedures
(vi) Finding knee or other important solutions including partial
Pareto-optimal set
(vii) Multi-objective scheduling and other optimization problems.
It was clear from the discussions that
evolutionary search methods offers an alternate means of solving
multi-objective optimization problems compared to classical
approaches. This is why multi-objective optimization using EAs is
getting a growing attention in the recent years.
The motivated readers may explore
current research issues and other important studies from various
texts (Coello et al, 2003; Deb, 2001), conference proceedings
(EMO-01 and EMO-03 Proceedings) and numerous research papers
(http://www.lania.mx/~ccoello/EMOO/).
References:
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C. A. C. Coello, D. A. VanVeldhuizen, and G. Lamont.
Evolutionary Algorithms for Solving Multi-Objective Problems.
Boston, MA: Kluwer Academic Publishers, 2002.
K.Deb. Multi-objective optimization using evolutionary algorithms.
Chichester, UK: Wiley, 2001.
C. Fonseca, P. Fleming, E. Zitzler, K. Deb, and L. Thiele, editors.
Proceedings of the Second Evolutionary Multi-Criterion
Optimization (EMO-03) Conference
(Lecture Notes in Computer Science (LNCS) 2632).
Heidelberg: Springer, 2003.
E. Zitzler, K. Deb, L. Thiele, C. A. C. Coello, and D. Corne,
editors. Proceedings of the First Evolutionary Multi-Criterion
Optimization (EMO-01) Conference
(Lecture Notes in Computer Science (LNCS) 1993).
Heidelberg: Springer, 2001
Are primary care physicians, public and private sector specialists substitutes or complements? Evidence from a simultaneous equations model for count data
No full textIn this paper, we examine the relationships between health care visits to general practitioners, public and private sector specialists using data from Italy, which has a mixed public-private health care system. We develop a simultaneous equations model that allows for the discreteness of measures of utilization and estimate this model using maximum simulated likelihood. Once common unobserved heterogeneity is properly accounted for, general practitioners, public and private specialists are found to be substitute sources of medical care. In contrast, a naive model finds they are complement
TACE-DEB vs. SBRT for hepatocellular carcinoma
No full textAbstract: Purpose To compare transarterial chemoembolization delivered with drug eluting beads (TACE-DEB) with stereotactioc body radiation therapy (SBRT) in patients with hepatocellular carcinoma (HCC) in a multicenter randomized trial. Materials and Methods Patients were included if they were eligible for TACE. They could also be recruited if they required treatment prior to liver transplantation. A maximum of four TACE-DEB procedures and ablation after incomplete TACE-DEB were both allowed. SBRT was delivered in six fractions of 8-9Gy. Primary end point was time to progression (TTP). Secondary endpoints were local control (LC), overall survival (OS), response rate (RR), toxicity, and quality of life (QoL). The calculated sample size was 100 patients. Results Between May 2015 and April 2020, 30 patients were randomized to the study. Due to slow accrual the trial was closed prematurely. Two patients in the SBRT arm were considered ineligible leaving 16 patients in the TACE-DEB arm and 12 in the SBRT arm. Median follow-up was 28.1 months. Median TTP was 12 months for TACE-DEB and 19 months for SBRT (p=0.15). Median LC was 12 months for TACE-DEB and >40 months (not reached) for SBRT (p=0.075). Median OS was 36.8 months for TACE-DEB and 44.1 months for SBRT (p=0.36). A post-hoc analysis showed 100% for SBRT 1- and 2-year LC, and 54.4% and 43.6% for TACE-DEB (p=0.019). Both treatments resulted in RR>80%. Three episodes of possibly related toxicity grade 653 were observed after TACE-DEB. No episodes were observed after SBRT. QoL remained stable after both treatment arms. Conclusions In this trial, TTP after TACE-DEB was not significantly improved by SBRT, while SBRT showed higher local antitumoral activity than TACE-DEB, without detrimental effects on OS, toxicity and QoL. To overcome poor accrual in randomized trials that include SBRT, and to generate evidence for including SBRT in treatment guidelines, international cooperation is needed
DEB parameters and values.
No full text<p>Values were taken from Saraiva (2011a) and adapted to allow different food proxies.</p><p>DEB parameters and values.</p
Domain structure of DEB-1.
No full textThe domain structure of DEB-1 and human vinculin is shown. The deb-1(gk329549) allele harbors the D908V mutation in the tail domain. Identical and similar residues are highlighted in red and yellow shading, respectively. (PDF)</p
Synchrony Matters More than Species Richness in Plant Community Stability at a Global Scale
No full textThe stability of ecological communities is critical for the stable provisioning of ecosystem services, such as food and forage production, carbon sequestration, and soil fertility. Greater biodiversity is expected to enhance stability across years by decreasing synchrony among species, but the drivers of stability in nature remain poorly resolved. Our analysis of time series from 79 datasets across the world showed that stability was associated more strongly with the degree of synchrony among dominant species than with species richness. The relatively weak influence of species richness is consistent with theory predicting that the effect of richness on stability weakens when synchrony is higher than expected under random fluctuations, which was the case in most communities. Land management, nutrient addition, and climate change treatments had relatively weak and varying effects on stability, modifying how species richness, synchrony, and stability interact. Our results demonstrate the prevalence of biotic drivers on ecosystem stability, with the potential for environmental drivers to alter the intricate relationship among richness, synchrony, and stability.National Science Foundation DEB-8114302, DEB8811884, DEB-9411972, DEB-0080382, DEB-0620652, DEB-1234162, DEB0618210National Science Foundation Research Coordination Network DEB-1042132Institute on the Environment DG-0001-13Agency of the Czech Republic GACR16-15012SCzech Academy of Sciences RVO 67985939Comunidad Autónoma de Madrid 2017-T2/AMB-5406Biotechnology and Biological Sciences Research Council BBS/E/C/000J030
Homozygous knockout mutants are sensitive to DEB treatment.
No full text(A) Embryos obtained from inbreeding heterozygous knockouts of fancd1 (hg45; 0.9 μg/mL DEB), fancd2 (hg47; 0.9 μg/mL DEB), fanci (hg54; 0.65 μg/mL DEB), fancj (hg56 and hg57; 0.6 μg/mL DEB), fancn (hg62; 0.8 μg/mL DEB), fancp (hg66; 0.9 μg/mL DEB) and fanct (hg70; 0.8 μg/mL DEB) were treated at indicated DEB concentrations between 4–72 hpf. Treated embryos were classified based on severity of morphological changes observed into three phenotypic groups: normal (WT appearance), moderate (slight body curvature and minor edema) and severe (emaciated appearance, severe body curvature and large edema). An example image of DEB treated embryo (72 hpf) for each group is shown on the left. Distribution of each phenotypic group for a given genotype are displayed as stacked bar chart. The segments in bar show percent of embryos in each morphological group: normal (white), moderate (light blue), severe (dark blue). The number in each segment depicts the number of embryos for a given phenotypic group. (B) Maternal WT fanca transcript rescues embryos from DEB hypersensitivity. Embryos obtained from indicated fanca_hg41 breeding were treated with DEB (0.8 μg/mL). Representative images show untreated and DEB treated embryos. (C) Embryos generated from inbreeding of homozygous knockouts of fancb (hg42; 0.8 μg/mL DEB), fanco (hg65; 0.8 μg/mL DEB) and fancq (hg69; 0.5 μg/mL DEB) were treated at indicated DEB concentrations. Representative images show untreated and DEB treated embryos.</p
Model process of DEB-IBM.
No full textThe set-up process of the model (steps 1-3), followed by the daily process (i.e. at each time-step) of the DEB-IBM for southern elephant seals (steps 4-7). Headings of steps 4-7 follow the headings of the sub-models as described in the ODD (Overview, Design concepts and Details) in section Sub-models in Model description.</p
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