Lipid Production from a Louisiana Native Chlorella vulgaris/Leptolyngbya sp. Co-culture for Biofuel Applications

Over the last several decades, microalgae have garnered great interest for biofuel production mainly due to the high lipid productivity and minimum land competition with food crops. In this research, a Louisiana native Chlorella vulgaris/Leptolyngbya sp. co-culture was selected for lipid production. The goal of this work is to improve the lipid productivity and lipid composition of this co-culture via optimizing irradiance and nitrogen levels, lipid extraction method and modeling of pilot photobioreactor (HISTAR). Effects of irradiance and nitrate nitrogen levels on total lipid yield, neutral lipid portion, and fatty acid profile of non-aerated and aerated co-cultures were investigated in bench top scale experiments. The maximum lipid productivities were ~17 and 116 mg L-1d-1 for non-aerated and aerated cultures respectively. The optimal nitrogen level was 2.94 mM and the optimal irradiance was in the range of 400 and 800 ƒÝmol m-2 s-1. Neutral lipids comprised approximately 75% of total lipids for non-aerated culture and 89% for aerated cultures. The major fatty acid components were 16- and 18-carbon fatty acids, and ~35% are saturated fatty acids. The fatty acid profiles did not vary significantly with the irradiance and nitrate nitrogen levels. A method using silver nanofibers to enhance the lipid extraction efficiency was investigated. Silver nanoparticles were added to disrupt microalgal cell walls to improve the lipid extraction efficiency of Folch¡¦s method and microwave assisted lipid extraction. The results showed that 1000 £gg g-1 silver nanofibers had the most significant improvement in the efficiency of lipid extraction (~30% and 50% increase in efficiency for Folch¡¦s method and microwave assisted lipid extraction respectively). Microwave assisted lipid extraction was the optimal method, considering both fatty acid profile and lipid extraction efficiency. For the modeling of HISTAR system, Steele¡¦s model was used for impact of irradiance and Monod model was used for the effects of nitrogen. The final model was able to predict the trend of lipid percentage increase with limited nitrogen level. The results of the simulations indicated the limited nitrogen constrained the lipid productivity despite of a higher lipid percentage. The results matched the conclusions of the experiments in bench top scale

Review of \u3cem\u3eThe War on Kids: How American Juvenile Justice Lost Its Way.\u3c/em\u3e by Cara H. Drinan

Review of: Cara H. Drinan, The War on Kids: How American Juvenile Justice Lost Its Way. Oxford University Press (2018), 215 pages, $27.95 (hardcover)

Ministries of Catholic Sisters in the Diocese of Cleveland: Assessing Capacity and Opportunity in a Period of Transition

Catholic sisters have long played a vital role in addressing the needs of the poor, neglected, and vulnerable members of society. In northeast Ohio, sisters have been instrumental in the arenas of education, healthcare, social service, and advocacy. This research builds on research conducted in 2009 on the characteristics of the ministries of Catholic sisters. Using a survey approach, responses were collected from 358 Catholic Sisters in 12 religious orders, approximately 60 percent of the sisters living in the Diocese of Cleveland. The study explores sisters\u27 current ministries (work and service), the plans for their ministries to continue, and their perspectives on the future of ministry. The research highlights several avenues for strengthening the transition of ministry activities as the number of retired sisters continues to increase

A Bayesian Approach to Estimate the Size and Structure of the Broad-line Region in Active Galactic Nuclei Using Reverberation Mapping Data

This is the first paper in a series devoted to systematic study of the size and structure of the broad-line region (BLR) in active galactic nuclei (AGNs) using reverberation mapping (RM) data. We employ a recently developed Bayesian approach that statistically describes the variabibility as a damped random walk process and delineates the BLR structure using a flexible disk geometry that can account for a variety of shapes, including disks, rings, shells, and spheres. We allow for the possibility that the line emission may respond non-linearly to the continuum, and we detrend the light curves when there is clear evidence for secular variation. We use a Markov Chain Monte Carlo implementation based on Bayesian statistics to recover the parameters and uncertainties for the BLR model. The corresponding transfer function is obtained self-consistently. We tentatively constrain the virial factor used to estimate black hole masses; more accurate determinations will have to await velocity-resolved RM data. Application of our method to RM data with Hbeta monitoring for about 40 objects shows that the assumed BLR geometry can reproduce quite well the observed emission-line fluxes from the continuum light curves. We find that the Hbeta BLR sizes obtained from our method are on average ~20% larger than those derived from the traditional cross-correlation method. Nevertheless, we still find a tight BLR size-luminosity relation with a slope of alpha=0.55\pm0.03 and an intrinsic scatter of ~0.18 dex. In particular, we demonstrate that our approach yields appropriate BLR sizes for some objects (such as Mrk 142 and PG 2130+099) where traditional methods previously encountered difficulties.Comment: 17 pages, 10 figures, 2 tables; minor reversion to match the published versio

A New Approach to Constrain Black Hole Spins in Active Galaxies Using Optical Reverberation Mapping

A tight relation between the size of the broad-line region (BLR) and optical luminosity has been established in about 50 active galactic nuclei studied through reverberation mapping of the broad Hbeta emission line. The R_blr-L relation arises from simple photoionization considerations. Using a general relativistic model of an optically thick, geometrically thin accretion disk, we show that the ionizing luminosity jointly depends on black hole mass, accretion rate, and spin. The non-monotonic relation between the ionizing and optical luminosity gives rise to a complicated relation between the BLR size and the optical luminosity. We show that the reverberation lag of Hbeta to the varying continuum depends very sensitively to black hole spin. For retrograde spins, the disk is so cold that there is a deficit of ionizing photons in the BLR, resulting in shrinkage of the hydrogen ionization front with increasing optical luminosity, and hence shortened Hbeta lags. This effect is specially striking for luminous quasars undergoing retrograde accretion, manifesting in strong deviations from the canonical R_blr-L relation. This could lead to a method to estimate black hole spins of quasars and to study their cosmic evolution. At the same time, the small scatter of the observed R_blr-L relation for the current sample of reverberation-mapped active galaxies implies that the majority of these sources have rapidly spinning black holes.Comment: 6 pages, 5 figures, to appear in ApJ

Wavelet Shrinkage Based Image Denoising using Soft Computing

Noise reduction is an open problem and has received considerable attention in the literature for several decades. Over the last two decades, wavelet based methods have been applied to the problem of noise reduction and have been shown to outperform the traditional Wiener filter, Median filter, and modified Lee filter in terms of root mean squared error (MSE), peak signal noise ratio (PSNR) and other evaluation methods. In this research, two approaches for the development of high performance algorithms for de-noising are proposed, both based on soft computing tools, such as fuzzy logic, neural networks, and genetic algorithms. First, an improved additive noise reduction method for digital grey scale nature images, which uses an interval type-2 fuzzy logic system to shrink wavelet coefficients, is proposed. This method is an extension of a recently published approach for additive noise reduction using a type-1 fuzzy logic system based wavelet shrinkage. Unlike the type-1 fuzzy logic system based wavelet shrinkage method, the proposed approach employs a thresholding filter to adjust the wavelet coefficients according to the linguistic uncertainty in neighborhood values, inter-scale dependencies and intra-scale correlations of wavelet coefficients at different resolutions by exploiting the interval type-2 fuzzy set theory. Experimental results show that the proposed approach can efficiently and rapidly remove additive noise from digital grey scale images. Objective analysis and visual observations show that the proposed approach outperforms current fuzzy non-wavelet methods and fuzzy wavelet based methods, and is comparable with some recent but more complex wavelet methods, such as Hidden Markov Model based additive noise de-noising method. The main differences between the proposed approach and other wavelet shrinkage based approaches and the main improvements of the proposed approach are also illustrated in this thesis. Second, another improved method of additive noise reduction is also proposed. The method is based on fusing the results of different filters using a Fuzzy Neural Network (FNN). The proposed method combines the advantages of these filters and has outstanding ability of smoothing out additive noise while preserving details of an image (e.g. edges and lines) effectively. A Genetic Algorithm (GA) is applied to choose the optimal parameters of the FNN. The experimental results show that the proposed method is powerful for removing noise from natural images, and the MSE of this approach is less, and the PSNR of is higher, than that of any individual filters which are used for fusion. Finally, the two proposed approaches are compared with each other from different point of views, such as objective analysis in terms of mean squared error(MSE), peak signal to noise ratio (PSNR), image quality index (IQI) based on quality assessment of distorted images, and Information Theoretic Criterion (ITC) based on a human vision model, computational cost, universality, and human observation. The results show that the proposed FNN based algorithm optimized by GA has the best performance among all testing approaches. Important considerations for these proposed approaches and future work are discussed

Role of the porous structure of the bioceramic scaffolds in bone tissue engineering

The porous structure of biomaterials plays a critical role in improving the efficiency of biomaterials in tissue engineering. Here we fabricate successfully porous bioceramics with accurately controlled pore parameters, and investigate the effect of pore parameters on the mechanical property, the cell seeding proliferation and the vascularization of the scaffolds. This study shows that the porosity play an important role on the mechanical property of the scaffolds, which is affected not only by the macropores size, but also by the interconnections of the scaffolds. Larger pores are beneficial for cell growth in scaffolds. In contrast, the interconnections do not affect cell growth much. The interconnections appear to limit the number of blood vessels penatrating through adjacent pores, and both the pores size and interconnections can determine the size of blood vessels. The results may be referenced on the selective design of porous structure of biomaterials to meet the specificity of biological application