This paper proposes a novel algorithm for solving combinatorial optimization problems using genetic algorithms (GA) with self-adaptive mutation. We selected the N-Queens problem (8 ≤ ≤ 32) as our benchmarking test suite, as they are highly multi-modal with huge numbers of global optima. Optimal static mutation probabilities for the traditional GA approach are determined for each to use as a best-case scenario benchmark in our conducted comparative analysis. Despite an unfair advantage with traditional GA using optimized fixed mutation probabilities, in large problem sizes (where > 15) multi-objective analysis showed the self-adaptive approach yielded a 65% to 584% improvement in the number of distinct solutions generated; the self-adaptive approach also produced the first distinct solution faster than traditional GA with a 1.90% to 70.0% speed improvement. Self-adaptive mutation control is valuable because it adjusts the mutation rate based on the problem characteristics and search process stages accordingly. This is not achievable with an optimal constant mutation probability which remains unchanged during the search process.
We investigate theoretically and experimentally the temperature-dependent linear optical properties of the clean c(4×2) reconstructed Si(100) surface for a wide range of temperatures. We combine two theoretical formalisms: the first one incorporates the contribution of temperature-dependent atomic motion to the surface optical response and, the second uses a dielectric function layer-by-layer separation method. Using these formalisms, we model temperature-dependent reflectance anisotropy (RA) of this surface for the first time: finite temperature ab-initio Car-Parrinello Molecular Dynamics (CPMD) at different temperatures up to 1000 K provide temperature-dependent atomic structural inputs for optical calculations and subsequent average of dielectric functions. Experimentally, one-domain c(4x2) Si(100) surface was prepared and characterised by Reflectance Anisotropy Spectroscopy (RAS) in a temperature range between 300 K and 800 K. Good agreement between experiment and theory is demonstrated, including a temperature-induced red shift of both the surface and bulk optical peaks. Theoretical results indicate that the temperature-induced modification of the optical response is substantially more pronounced for the surface than for the bulk.
During myocardial ischemia/reperfusion (I/R), the generation of reactive oxygen species (ROS) contributes to post‐reperfusion cardiac injury and contractile dysfunction. Activation of protein kinase C epsilon (PKC ɛ) during I/R has been shown to increase ROS release, in part, by its stimulation of increased uncoupled endothelial nitric oxide synthase activity. We hypothesize that using a cell permeable PKC ɛ peptide inhibitor (PKC ɛ‐) (N‐myr‐EAVSLKPT, MW=1054 g/mol, 10μM or 20μM) will improve post‐reperfused cardiac function and attenuate infarct size compared to untreated controls in isolated perfused rat hearts subjected to I(30 min)/R(90 min). Male Sprague‐Dawley rats (275–325 g) were anesthetized with sodium pentobarbital (60 mg/kg) and anticoagulated with heparin 1000 units IP. PKC ɛ‐was dissolved in Krebs' buffer and infused during the first 10 min of reperfusion. PKC ɛ‐treated hearts exhibited significant improvement in post‐reperfused cardiac function at 90 min in the maximal rate of left ventricular developed pressure (+dP/dtmax): 56±5%; n=6 (10μM) and 46±3%; n=4 (20μM) compared to untreated controls (n=6) which only recovered to 32±5% of baseline values for +dP/dtmax respectively (p<0.05). Furthermore, PKC ɛ‐treated hearts showed significant reduction in infarct size of 27±2% (10μM) and 28 ±2% (20μM) compared to untreated control I/R hearts, 40±3% (p<0.05). The results suggest that PKC ɛ‐is effective in improving cardiac function and reducing infarct size and is a putative treatment that could aid in clinical myocardial infarction/organ transplantation patient recovery.Support or Funding InformationThis study was supported by the Center for Chronic Disorders of Aging, the Division of Research and the Department of Bio‐Medical Sciences at Philadelphia College of Osteopathic Medicine.
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