Publications by authors named "L Yeghiazarian"

Article Synopsis
  • Mitigating water contamination and enhancing sustainability necessitate the use of engaging geospatial tools that consider the likelihood and distribution of water quality issues.
  • The paper introduces the STREAMS tool, which utilizes reliability theory and integrates with ArcGIS to create maps that visualize the risk of contamination in watersheds.
  • Two case studies illustrate how STREAMS can evaluate and communicate the effectiveness of different water management strategies across various watershed settings.
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Blastocyst-derived stem cell lines were shown to self-organize into embryo-like structures in 3D cell culture environments. Here, we provide evidence that embryo-like structures can be generated solely based on transcription factor-mediated reprogramming of embryonic stem cells in a simple 3D co-culture system. Embryonic stem cells in these cultures self-organize into elongated, compartmentalized embryo-like structures reflecting aspects of the inner regions of the early post-implantation embryo.

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Microbial surface water contamination can disrupt critical ecosystem services such as recreation and drinking water supply. Prediction of water contamination and assessment of sustainability of water resources in the context of water quality are needed but are difficult to achieve - with challenges arising from the complexity of environmental systems, and stochastic variability of processes that drive contaminant fate and transport. In this paper we use reliability theory as a framework to address these issues.

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This work describes the novel use of a cell phone camera and the L*a*b method (color space defined by the International Commission on Illumination) to characterize the color change in different vapochromic platinum(II) complexes in order to get quantitative and more reliable data. In this study, we have developed a semi-automatic CCA software that digitally analyzes images (e.g.

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Effective load reduction strategies rely on an accurate Total Maximum Daily Load (TMDL) calculation, which quantifies contaminant loading from various sources. There is a wide range of methods to consider uncertainties in TMDLs: from simple, conservative assumptions regarding factors that contribute to the TMDL required margin of safety (MOS), to probability-based approaches such as Monte Carlo simulations, which explicitly quantifies TMDL uncertainty. In this paper the authors adapt the Load Resistance Factor Design (LRFD), a rigorous, reliability-based framework, to water quality assessment and the TMDL process.

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