A promising approach using Fibonacci sequence-based optimization algorithms and advanced computing.

In this paper, the feasibility of Structural Health Monitoring (SHM) employing a novel Fibonacy Sequence (FS)-based Optimization Algorithms (OAs) and up-to-date computing techniques is investigated for a large-scale railway bridge. During recent decades, numerous metaheuristic intelligent OAs have been proposed and immediately gained a lot of momentum. However, the major concern is how to employ OAs to deal with real-world problems, especially the SHM of large-scale structures. In addition to the requirement of high accuracy, a high computational cost is putting up a major barrier to the real application of OAs. Therefore, this article aims at addressing these two aforementioned issues. First, we propose employing the optimal ability of the golden ratio formulated by the well-known FS to remedy the shortcomings and improve the accuracy of OAs, specifically, a recently proposed new algorithm, namely Salp Swarm Algorithm (SSA). On the other hand, to deal with the high computational cost problems of OAs, we propose employing an up-to-date computing technique, termed superscalar processor to conduct a series of iterations in parallel. Moreover, in this work, the vectorization technique is also applied to reduce the size of the data. The obtained results show that the proposed approach is highly potential to apply for SHM of real large-scale structures.

Damage assessment in structures using artificial neural network working and a hybrid stochastic optimization.

Artificial neural network (ANN) has been commonly used to deal with many problems. However, since this algorithm applies backpropagation algorithms based on gradient descent (GD) technique to look for the best solution, the network may face major risks of being entrapped in local minima. To overcome those drawbacks of ANN, in this work, we propose a novel ANN working parallel with metaheuristic algorithms (MAs) to train the network. The core idea is that first, (1) GD is applied to increase the convergence speed. (2) If the network is stuck in local minima, the capacity of the global search technique of MAs is employed. (3) After escaping from local minima, the GD technique is applied again. This process is applied until the target is achieved. Additionally, to increase the efficiency of the global search capacity, a hybrid of particle swarm optimization and genetic algorithm (PSOGA) is employed. The effectiveness of ANNPSOGA is assessed using both numerical models and measurement. The results demonstrate that ANNPSOGA provides higher accuracy than traditional ANN, PSO, and other hybrid ANNs (even a higher level of noise is employed) and also considerably decreases calculational cost compared with PSO.

Pterocarpus marsupium extract extends replicative lifespan in budding yeast.

As the molecular mechanisms of biological aging become better understood, there is growing interest in identifying interventions that target those mechanisms to promote extended health and longevity. The budding yeast Saccharomyces cerevisiae has served as a premier model organism for identifying genetic and molecular factors that modulate cellular aging and is a powerful system in which to evaluate candidate longevity interventions. Here we screened a collection of natural products and natural product mixtures for effects on the growth rate, mTOR-mediated growth inhibition, and replicative lifespan. No mTOR inhibitory activity was detected, but several of the treatments affected growth rate and lifespan. The strongest lifespan shortening effects were observed for green tea extract and berberine. The most robust lifespan extension was detected from an extract of Pterocarpus marsupium and another mixture containing Pterocarpus marsupium extract. These findings illustrate the utility of the yeast system for longevity intervention discovery and identify Pterocarpus marsupium extract as a potentially fruitful longevity intervention for testing in higher eukaryotes.

Defining the impact of mutation accumulation on replicative lifespan in yeast using cancer-associated mutator phenotypes.

Mutations accumulate within somatic cells and have been proposed to contribute to aging. It is unclear what level of mutation burden may be required to consistently reduce cellular lifespan. Human cancers driven by a mutator phenotype represent an intriguing model to test this hypothesis, since they carry the highest mutation burdens of any human cell. However, it remains technically challenging to measure the replicative lifespan of individual mammalian cells. Here, we modeled the consequences of cancer-related mutator phenotypes on lifespan using yeast defective for mismatch repair (MMR) and/or leading strand (Polε) or lagging strand (Polδ) DNA polymerase proofreading. Only haploid mutator cells with significant lifetime mutation accumulation (MA) exhibited shorter lifespans. Diploid strains, derived by mating haploids of various genotypes, carried variable numbers of fixed mutations and a range of mutator phenotypes. Some diploid strains with fewer than two mutations per megabase displayed a 25% decrease in lifespan, suggesting that moderate numbers of random heterozygous mutations can increase mortality rate. As mutation rates and burdens climbed, lifespan steadily eroded. Strong diploid mutator phenotypes produced a form of genetic anticipation with regard to aging, where the longer a lineage persisted, the shorter lived cells became. Using MA lines, we established a relationship between mutation burden and lifespan, as well as population doubling time. Our observations define a threshold of random mutation burden that consistently decreases cellular longevity in diploid yeast cells. Many human cancers carry comparable mutation burdens, suggesting that while cancers appear immortal, individual cancer cells may suffer diminished lifespan due to accrued mutation burden.

Model Updating for Nam O Bridge Using Particle Swarm Optimization Algorithm and Genetic Algorithm.

Vibration-based structural health monitoring (SHM) for long-span bridges has become a dominant research topic in recent years. The Nam O Railway Bridge is a large-scale steel truss bridge located on the unique main rail track from the north to the south of Vietnam. An extensive vibration measurement campaign and model updating are extremely necessary to build a reliable model for health condition assessment and operational safety management of the bridge. The experimental measurements are carried out under ambient vibrations using piezoelectric sensors, and a finite element (FE) model is created in MATLAB to represent the physical behavior of the structure. By model updating, the discrepancies between the experimental and the numerical results are minimized. For the success of the model updating, the efficiency of the optimization algorithm is essential. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are employed to update the unknown model parameters. The result shows that PSO not only provides a better accuracy between the numerical model and measurements, but also reduces the computational cost compared to GA. This study focuses on the stiffness conditions of typical joints of truss structures. According to the results, the assumption of semi-rigid joints (using rotational springs) can most accurately represent the dynamic characteristics of the truss bridge considered.

Impact of Dengue Vaccination on Serological Diagnosis: Insights From Phase III Dengue Vaccine Efficacy Trials.

Background: We previously reported that vaccination with the tetravalent dengue vaccine (CYD-TDV; Dengvaxia) may bias the diagnosis of dengue based on immunoglobulin M (IgM) and immunoglobulin G (IgG) assessments. Methods: We undertook a post hoc pooled analysis of febrile episodes that occurred during the active surveillance phase (the 25 months after the first study injection) of 2 pivotal phase III, placebo-controlled CYD-TDV efficacy studies that involved ≥31000 children aged 2-16 years across 10 countries in Asia and Latin America. Virologically confirmed dengue (VCD) episode was defined with a positive test for dengue nonstructural protein 1 antigen or dengue polymerase chain reaction. Probable dengue episode was serologically defined as (1) IgM-positive acute- or convalescent-phase sample, or (2) IgG-positive acute-phase sample and ≥4-fold IgG increase between acute- and convalescent-phase samples. Results: There were 1284 VCD episodes (575 and 709 in the CYD-TDV and placebo groups, respectively) and 17673 other febrile episodes (11668 and 6005, respectively). Compared with VCD, the sensitivity and specificity of probable dengue definition were 93.1% and 77.2%, respectively. Overall positive and negative predictive values were 22.9% and 99.5%, respectively, reflecting the much lower probability of correctly confirming probable dengue in a population including a vaccinated cohort. Vaccination-induced bias toward false-positive diagnosis was more pronounced among individuals seronegative at baseline. Conclusions: Caution will be required when interpreting IgM and IgG data obtained during routine surveillance in those vaccinated with CYD-TDV. There is an urgent need for new practical, dengue-specific diagnostic algorithms now that CYD-TDV is approved in a number of dengue-endemic countries. Clinical Trials Registration: NCT01373281 and NCT01374516.

In vitro evaluation of color change in maxillofacial elastomer through the use of an ultraviolet light absorber and a hindered amine light stabilizer.

STATEMENT OF PROBLEM: External prostheses composed of silicone elastomers exhibit an unwanted color change over time. PURPOSE: This study evaluated color stability when an ultraviolet light absorber and hindered amine light stabilizer were mixed in the maxillofacial elastomer containing either organic or inorganic pigments. MATERIAL AND METHODS: The materials used were an RTV silicone elastomer, 1 natural inorganic dry-earth pigment (burnt sienna) and 2 synthesized organic pigments (hansa yellow and alizarin red), ultraviolet light absorber (UVA) and hindered amine light stabilizer (HALS). Specimens (n=160) were fabricated in a custom mold and randomly assigned and exposed to weathering sites in Miami and Phoenix for approximately 3 months. Eight test groups (2 of each 4 material types with or without additives) of 10 specimens each were assigned to each site. L*, a*, b* readings were obtained before and after weathering from a spectrocolorimeter. Nonpigmented elastomers served as the control. Three-factor ANOVA was conducted to examine interaction effects between weathering sites, specimen type, and the presence of additive (alpha=.05). Overall color change (Delta E) and change in color coordinates (Delta L*, Delta a*, Delta b*) of specimen groups with and without additive were analyzed with independent sample t tests. RESULTS: In specimen groups with the additives (UVA and HALS), color change decreased significantly (P<.05) in burnt sienna and hansa yellow in Phoenix and in the control and hansa yellow in Miami. Additives did not affect color change in the alizarin red group. CONCLUSION: UVA and HALS were shown to be effective in retarding color change in some circumstances.