Time-dependent reliability methodologies with saddlepoint approximation

Engineers always encounter time-dependent uncertainties that ubiquitously exist, such as the random deterioration of material properties and time-variant loads. Therefore the reliability of engineering systems becomes time-dependent. It is crucial to predict the time-dependent reliability in the design stage, given possible catastrophic consequences of a failure. Although extensive research has been conducted on reliability analysis, estimating the reliability accurately and efficiently is still challenging. The objective of this work is to develop accurate and efficient reliability methodologies for engineering design. The basic idea is the integration of traditional reliability methods with saddlepoint approximation (SPA), which can accurately approximate the tail distribution of a random variable. Four methods are proposed in this work. The first three methods deal with time-independent reliability while the last one estimates the time-dependent reliability. The first method combines SPA with first-order approximation and achieves higher accuracy over the traditional first-order reliability method when bimodal distributions are involved. The second method further improves the accuracy of reliability estimation by integrating SPA with the second-order approximation. The third method extends the second method into the reliability-based design for higher accuracy, and the high efficiency is maintained by an efficient algorithm for searching for an equivalent reliability index. The fourth method uses sequential efficient global optimization to convert a time-dependent problem into a time-independent counterpart. Then the second method is utilized to estimate the time-independent reliability after the conversion. The accuracy and effectiveness of the above methods are demonstrated by both numerical examples and engineering applications --Abstract, page iv

Prediction of autogenous shrinkage in fly ash blended cement systems

Autogenous shrinkage is the unrestrained volume change of cementitious materials occurring at con-stant temperature without any change in mass. It occurs as a consequence of self-desiccation (de-crease of internal relative humidity) and increasing capillary pressure in the pore fluid. In concrete elements hardening in sealed conditions, autogenous shrinkage is critical for crack development, in particular in high performance concrete with low water to cement ratio. Being able to predict autog-enous shrinkage can provide insights for the long-term deformation of different concrete mixtures, create a useful database for simulations and ultimately minimize the cracking risks. The main objective of this thesis is to predict the autogenous shrinkage of fly-ash-blended cement systems by using a quantitative multi-physics approach. In order to reach this goal, a systematic ex-perimental study of autogenous deformation, self-desiccation, microstructure evolution, elastic properties and basic creep of different cementitious systems was first carried out. After having achieved a phenomenological understanding, supported by experimental data, analytical and numer-ical modeling of autogenous deformation is possible. In this study, a novel method based on the evolution of microstructure for predicting the self-desiccation was developed. In this method, 1H nuclear magnetic resonance and mercury intrusion porosimetry were combined to obtain the evolution of the microstructure. This prediction provides another possibility to predict capillary pressure and corresponding autogenous shrinkage of a simu-lated microstructure. Prediction of autogenous shrinkage, including poro-elastic and poro-visco-elastic response based on experimental quantities, was accomplished. In the prediction, the poro-elastic deformation of ce-mentitious materials was calculated based on poromechanics. The poro-visco-elastic response was studied with basic creep tests on hardening cementitious materials. Generalized Kelvin-Voigt chains were applied to predict the aging of creep. The prediction matched reasonably well with measured autogenous shrinkage. Autogenous shrinkage of cementitious materials was also numerically modeled with a microstructure simulation and a finite element method. This part of the work extended existing approaches based mainly on two programing platforms: µic platform and Automatic Mechanics for Integrated Exper-iments (AMIE) finite element framework. Average pore pressure load calculated from measured relative humidity, saturation degree and Biot coefficient was imposed into a 3-dimensional micro-structure computed with µic platform. Based on back-calculated elastic and visco-elastic behavior of C-S-H, an approach for simulating the autogenous shrinkage was demonstrated

Second Order Reliability Method for Time-Dependent Reliability Analysis Using Sequential Efficient Global Optimization

Reliability depends on time if the associated limit-state function includes time. A time-dependent reliability problem can be converted into a time-independent reliability problem by using the extreme value of the limit-state function. Then the first order reliability method can be used but it may produce a large error since the extreme limit-state function is usually highly nonlinear. This study proposes a new reliability method so that the second order reliability method can be applied to time-dependent reliability analysis for higher accuracy while maintaining high efficiency. The method employs sequential efficient global optimization to transform the time-dependent reliability analysis into the time-independent problem. The Hessian approximation and envelope theorem are used to obtain the second order information of the extreme limit-state function. Then the second order saddlepoint approximation is use to evaluate the reliability. The accuracy and efficiency of the proposed method are verified through numerical examples

Expression of fatty acid synthesis genes and fatty acid accumulation in haematococcus pluvialis under different stressors

<p>Abstract</p> <p>Background</p> <p>Biofuel has been the focus of intensive global research over the past few years. The development of 4^thgeneration biofuel production (algae-to-biofuels) based on metabolic engineering of algae is still in its infancy, one of the main barriers is our lacking of understanding of microalgal growth, metabolism and biofuel production. Although fatty acid (FA) biosynthesis pathway genes have been all cloned and biosynthesis pathway was built up in some higher plants, the molecular mechanism for its regulation in microalgae is far away from elucidation.</p> <p>Results</p> <p>We cloned main key genes for FA biosynthesis in <it>Haematococcus pluvialis</it>, a green microalga as a potential biodiesel feedstock, and investigated the correlations between their expression alternation and FA composition and content detected by GC-MS under different stress treatments, such as nitrogen depletion, salinity, high or low temperature. Our results showed that high temperature, high salinity, and nitrogen depletion treatments played significant roles in promoting microalgal FA synthesis, while FA qualities were not changed much. Correlation analysis showed that acyl carrier protein (ACP), 3-ketoacyl-ACP-synthase (KAS), and acyl-ACP thioesterase (FATA) gene expression had significant correlations with monounsaturated FA (MUFA) synthesis and polyunsaturated FA (PUFA) synthesis.</p> <p>Conclusions</p> <p>We proposed that ACP, KAS, and FATA in <it>H. pluvialis </it>may play an important role in FA synthesis and may be rate limiting genes, which probably could be modified for the further study of metabolic engineering to improve microalgal biofuel quality and production.</p

Characterization of long-chain acyl-CoA synthetases which stimulate secretion of fatty acids in green algae Chlamydomonas reinhardtii

Additional file 1. Complete list of primers used in this study

Transgenerational Epigenetic Inheritance Under Environmental Stress by Genome-Wide DNA Methylation Profiling in Cyanobacterium

Epigenetic modifications such as DNA methylation are well known as connected with many important biological processes. Rapid accumulating evidence shows environmental stress can generate particular defense epigenetic changes across generations in eukaryotes. This transgenerational epigenetic inheritance in animals and plants has gained interest over the last years. Cyanobacteria play very crucial role in the earth, and as the primary producer they can adapt to nearly all diverse environments. However, few knowledge about the genome wide epigenetic information such as methylome information in cyanobacteria, especially under any environment stress, was reported so far. In this study we profiled the genome-wide cytosine methylation from a model cyanobacterium Synechocystis sp. PCC 6803, and explored the possibility of transgenerational epigenetic process in this ancient single-celled prokaryote by comparing the DNA methylomes among normal nitrogen medium cultivation, nitrogen starvation for 72 h and nitrogen recovery for about 12 generations. Our results shows that DNA methylation patterns in nitrogen starvation and nitrogen recovery are much more similar with each other, significantly different from that of the normal nitrogen. This study reveals the difference in global DNA methylation pattern of cyanobacteria between normal and nutrient stress conditions and reports the evidence of transgenerational epigenetic process in cyanobacteria. The results of this study may contribute to a better understanding of epigenetic regulation in prokaryotic adaptation to and survive in the ever changing environment

Stable Expression of Antibiotic-Resistant Gene ble from Streptoalloteichus hindustanus in the Mitochondria of Chlamydomonas reinhardtii

The mitochondrial expression of exogenous antibiotic resistance genes has not been demonstrated successfully to date, which has limited the development of antibiotic resistance genes as selectable markers for mitochondrial site-directed transformation in Chlamydomonas reinhardtii. In this work, the plasmid pBSLPNCB was constructed by inserting the gene ble of Streptoalloteichus hindustanus (Sh ble), encoding a small (14-kilodalton) protective protein into the site between TERMINVREP-Left repeats and the cob gene in a fragment of mitochondrial DNA (mtDNA) of C. reinhardtii. The fusion DNA-construct, which contained TERMINVREP-Left, Sh ble, cob, and partial nd4 sequence, were introduced into the mitochondria of the respiratory deficient dum-1 mutant CC-2654 of C. reinhardtii by biolistic particle delivery system. A large number of transformants were obtained after eight weeks in the dark. Subsequent subculture of the transformants on the selection TAP media containing 3 ìg/mL Zeomycin for 12 months resulted in genetically modified transgenic algae MT-Bs. Sequencing and Southern analyses on the mitochondrial genome of the different MT-B lines revealed that Sh ble gene had been integrated into the mitochondrial genome of C. reinhardtii. Both Western blot, using the anti-BLE monoclonal antibody, and Zeomycin tolerance analysis confirmed the presence of BLE protein in the transgenic algal cells. It indicates that the Sh ble gene can be stably expressed in the mitochondria of C. reinhardtii

Taurohyocholic acid acts as a potential predictor of the efficacy of tyrosine kinase inhibitors combined with programmed cell death-1 inhibitors in hepatocellular carcinoma

Background and aims: Tyrosine kinase inhibitors (TKIs) combined with programmed cell death protein-1 (PD-1) have significantly improved survival in patients with unresectable hepatocellular carcinoma (uHCC), but effective biomarkers to predict treatment efficacy are lacking. Peripheral blood bile acids (BAs) are associated with tumor response to therapy, but their roles in HCC remain unclear.Methods: This retrospective study included HCC patients who received first-line TKIs combined with PD-1 inhibitors treatment (combination therapy) in our clinical center from November 2020 to June 2022. The aim of this study was to analyze the changes in plasma BA profiles before and after treatment in both the responding group (Res group) and the non-responding group (Non-Res group). We aimed to explore the potential role of BAs in predicting the response to combination therapy in HCC patients.Results: Fifty-six patients with HCC who underwent combination therapy were included in this study, with 28 designated as responders (Res group) and 28 as non-responders (Non-Res group). There were differences in plasma BA concentrations between the two groups before systemic therapy. Plasma taurohyocholic acid (THCA) levels in the Res group were significantly lower than those in the Non-Res group. Patients with low levels of THCA exhibited superior median progression-free survival (7.6 vs. 4.9 months, p = 0.027) and median overall survival (23.7 vs. 11.6 months, p = 0.006) compared to those of patients with high levels of THCA.Conclusion: Peripheral blood BA metabolism is significantly correlated with combination therapy response and survival in patients with HCC. Our findings emphasize the potential of plasma BAs as biomarkers for predicting combination therapy outcomes and offering novel therapeutic targets for modulating responses to systemic cancer therapy

Reliability Methods for Bimodal Distribution with First-Order Approximation

In traditional reliability problems, the distribution of a basic random variable is usually unimodal; in other words, the probability density of the basic random variable has only one peak. In real applications, some basic random variables may follow bimodal distributions with two peaks in their probability density. When binomial variables are involved, traditional reliability methods, such as the first-order second moment (FOSM) method and the first-order reliability method (FORM), will not be accurate. This study investigates the accuracy of using the saddlepoint approximation (SPA) for bimodal variables and then employs SPA-based reliability methods with first-order approximation to predict the reliability. A limit-state function is at first approximated with the first-order Taylor expansion so that it becomes a linear combination of the basic random variables, some of which are bimodally distributed. The SPA is then applied to estimate the reliability. Examples show that the SPA-based reliability methods are more accurate than FOSM and FORM