We study the nonperturbative renormalization of the nucleon-nucleon (N N ) interaction at nextto-leading order (NLO) and next-to-next-to-leading order (NNLO) of chiral effective field theory. A systematic variation of the cutoff parameter is performed for values below the chiral symmetry breaking scale of about 1 GeV. The accuracy of the predictions is determined by calculating the χ 2 for the reproduction of the N N data for energy intervals below pion-production threshold. At NLO, N N data are described well up to about 100 MeV laboratory energy and, at NNLO, up to about 200 MeV-with, essentially, cutoff independence for cutoffs between about 450 and 850 MeV.

Optimal metabolic trade-offs between growth and productivity are key constraints in strain optimization by metabolic engineering; however, how cellular noise impacts these trade-offs and drives the emergence of subpopulations with distinct resource allocation strategies, remains largely unknown. Here, we introduce a single-cell strategy for quantifying the trade-offs between triacylglycerol production and growth in the oleaginous microorganism Yarrowia lipolytica. The strategy relies on high-throughput quantitative-phase imaging and, enabled by nanoscale secondary ion mass spectrometry analyses and dedicated image processing, allows us to image how resources are partitioned between growth and productivity. Enhanced precision over population-averaging biotechnologies and conventional microscopy demonstrates how cellular noise impacts growth and productivity differently. As such, subpopulations with distinct metabolic trade-offs emerge, with notable impacts on strain performance and robustness. By quantifying the self-degradation of cytosolic macromolecules under nutrient-limiting conditions, we discover the cell-to-cell heterogeneity in protein and fatty-acid recycling, unmasking a potential bet-hedging strategy under starvation.

The MgxZn1−xO alloy system is emerging as an environmentally friendly choice in ultraviolet lighting and sensor technologies. Knowledge of defects which impact their optical and material properties is a key issue for utilization of these alloys in various technologies. The impact of phase segregation, structural imperfections, and alloy inhomogeneities on the phonon dynamics and electronic states of MgxZn1−xO thin films were studied via selective resonant Raman scattering (SRRS) and Urbach analyses, respectively. A series of samples with Mg composition from 0–68% were grown using a sputtering technique, and the optical gaps were found to span a wide UV range of 3.2–5.8 eV. The extent of the inherent phase segregation was determined via SRRS using two UV-laser lines to achieve resonance with the differing optical gaps of the embedded cubic and wurtzite structural domains. The occurrence of Raman scattering from cubic structures is discussed in terms of relaxation of the selection rules due to symmetry breaking by atomic substitutions. The Raman linewidth and Urbach energy behavior indicate the phase segregation region occurs in the range of 47–66% Mg. Below the phase segregation, the longitudinal optical phonons are found to follow the model of one-mode behavior. The phonon decay model of Balkanski et al. indicates that the major contributor to Raman linewidth arises from the temperature-independent term attributed to structural defects and alloy inhomogeneity, while the contribution from anharmonic decay is relatively small. Moreover, a good correlation between Urbach energy and Raman linewidth was found, implying that the underlying crystal dynamics affecting the phonons also affect the electronic states. Furthermore, for alloys with low Mg composition structural defects are dominant in determining the alloy properties, while at higher compositions alloy inhomogeneity cannot be neglected.

High-throughput imaging with single-cell resolution has enabled remarkable discoveries in cell physiology and Systems Biology investigations. A common, and often the most challenging step in all such imaging implementations, is the ability to segment multiple images to regions that correspond to individual cells. Here, a robust segmentation strategy for microbial cells using Quantitative Phase Imaging is reported. The proposed method enables a greater than 99% yeast cell segmentation success rate, without any computationally-intensive, post-acquisition processing. We also detail how the method can be expanded to bacterial cell segmentation with 98% success rates with substantially reduced processing requirements in comparison to existing methods. We attribute this improved performance to the remarkably uniform background, elimination of cell-to-cell and intracellular optical artifacts, and enhanced signal-tobackground ratio-all innate properties of imaging in the optical-phase domain. V C 2017 International Society for Advancement of Cytometry

We expand upon our recent, fundamental report on solvent immersion imprint lithography (SIIL) and describe a semi-automated and high-performance procedure for prototyping polymer microfluidics and optofluidics. The SIIL procedure minimizes manual intervention through a cost-effective (∼$200) and easy-to-assemble apparatus. We analyze the procedure's performance specifically for Poly (methyl methacrylate) microsystems and report repeatable polymer imprinting, bonding, and 3D functionalization in less than 5 min, down to 8 μm resolutions and 1:1 aspect ratios. In comparison to commercial approaches, the modified SIIL procedure enables substantial cost reductions, a 100-fold reduction in imprinting force requirements, as well as a more than 10-fold increase in bonding strength. We attribute these advantages to the directed polymer dissolution that strictly localizes at the polymer-solvent interface, as uniquely offered by SIIL. The described procedure opens new desktop prototyping opportunities, particularly for non-expert users performing live-cell imaging, flow-through catalysis, and on-chip gas detection.