Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

Peer reviewedPublisher PD

Photoconductivity analyzed in the frequency domain - an introductory case study of strontium titanate

Strontium titanate (STO, SrTiO3) has been used for many applications in solid state electrochemistry and is considered a standard and model material. Its characteristics, and those of its derivatives such as STF (SrTi0.65Fe0.35O3-x), have been characterized by many groups on various aspects, such as electronic/ionic conductivity, oxygen exchange kinetics and the impact of doping. Recently, the interaction of light with STO/STF has been of increased interest. A persistent photoconductivity has been observed [1] and enhanced oxygen exchange kinetics have been detected, opening up new fields of application, such as a light-driven fuel cell [2]. The reasons behind these effects remain subject to discussion or even speculation as the relation to the relatively large bandgap and the photoresponse at long wavelengths remains unclear. What makes the analysis of these effects difficult is the interplay of many electrochemical and photoelectrochemical processes that contribute to the photoresponse including the electronic and ionic conductivity, the number and nature of charge carriers, charge traps, phonon related effects, and surface reactions. With electrochemical impedance spectroscopy (EIS), one can distinguish diverse processes on the basis of their time constants and how they evolve as a function of operating conditions, such as temperature, atmosphere (leading to stoichiometry changes) and illumination. However, the impact of light can only be characterized implicitly as a change in other processes that also prevail in the dark. Intensity modulated photocurrent/-voltage spectroscopy (IMPS/IMVS) have been shown to reveal valuable information about charge carrier dynamics for photoelectrodes and photovoltaic cells [3]. To the best of our knowledge, these techniques have never been applied to devices or materials that are not photoactive, or in other words, that do not show a photovoltage, such as a symmetrical model cells based on STO or STF. However, with the small signal light perturbation that is the key element of IMPS and IMVS, we can trigger the light effect directly and analyze the system response by its current and voltage signals. In this contribution, we will begin with a brief introduction into IMPS and IMVS and show how these techniques can be applied to model electrodes consisting of STO and STF. The results are compared to EIS under different illumination and we will show how to extract the relevant information about the photoresponse. By evaluating the activation energies of the different electrochemical and photoelectrochemical processes, we can attribute those to physical effects and clarify some of the previously unknown processes that lead to anomalies observed in STO/STF under illumination. The capacity of IMPS and IMVS have been underestimated so far and in this contribution, we will conclude with an outlook for their potential to other fields of application, such as ionic motion in perovskite solar cells that are thought to be responsible for their accelerated degradation under illumination. This work was supported by JSPS Core-to-Core Program, A. Advanced Research Networks: “Solid Oxide Interfaces for Faster Ion Transport”. References [1] M. C. Tarun et al., Phys. Rev. Lett. 111, 187403, 2013. [2] G. C. Bunauer, Adv. Funct. Mater. 26, 120, 2016. [3] D. Klotz et al., Phys. Chem. Chem. Phys. 18, 23438, 2016

Macropore flow at the field scale: predictive performance of empirical models and X-ray CT analyzed macropore characteristics

Predictions of macropore flow is important for maintaining both soil and water quality as it governs key related soil processes e.g. soil erosion and subsurface transport of pollutants. However, macropore flow currently cannot be reliably predicted at the field scale because of inherently large spatial variability. The aim of this study was to perform field scale characterization of macropore flow and investigate the predictive performance of (1) current empirical models for both water and air flow, and (2) X-ray CT derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 to 8.5 cm depth) in a 15 m × 15 m grid from an agricultural loamy field located in Silstrup, Denmark. All soil columns were scanned with an industrial CT scanner (129 μm resolution) and later used for measurements of saturated water permeability, air permeability and gas diffusivity at -30 and -100 cm matric potentials. Distribution maps for both water and air permeabilities and gas diffusivity reflected no spatial correlation irrespective of the soil texture and organic matter maps. Empirical predictive models for both water and air permeabilities showed poor performance as they were not able to realistically capture macropore flow because of poor correlations with soil texture and bulk density. The tested empirical model predicted well gas diffusivity at -100 cm matric potential, but relatively failed at -30 cm matric potential particularly for samples with biopore flow. Image segmentation output of the four employed methods was nearly the same, and matched well with measured air-filled porosity at -30 cm matric potential. Many of the CT derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also strongly correlated with saturated water permeability, air permeability, and gas diffusivity. The correlations between macropore network characteristics and macropore flow parameters were further improved on dividing soil samples into samples with biopore and matrix flow. Observed strong correlations between macropore network characteristics and macropore flow highlighted the need of further research on numerical simulations of macropore flow based on X-ray CT images. This could pave the way for the digital soil physics laboratory in the future

Food Insecurity as a Barrier to Sustained Antiretroviral Therapy Adherence in Uganda

Background: Food insecurity is emerging as an important barrier to antiretroviral (ARV) adherence in sub-Saharan Africa and elsewhere, but little is known about the mechanisms through which food insecurity leads to ARV non-adherence and treatment interruptions. Methodology: We conducted in-depth, open-ended interviews with 47 individuals (30 women, 17 men) living with HIV/AIDS recruited from AIDS treatment programs in Mbarara and Kampala, Uganda to understand how food insecurity interferes with ARV therapy regimens. Interviews were transcribed, coded for key themes, and analyzed using grounded theory. Findings: Food insecurity was common and an important barrier to accessing medical care and ARV adherence. Five mechanisms emerged for how food insecurity can contribute to ARV non-adherence and treatment interruptions or to postponing ARV initiation: 1) ARVs increased appetite and led to intolerable hunger in the absence of food; 2) Side effects of ARVs were exacerbated in the absence of food; 3) Participants believed they should skip doses or not start on ARVs at all if they could not afford the added nutritional burden; 4) Competing demands between costs of food and medical expenses led people either to default from treatment, or to give up food and wages to get medications; 5) While working for food for long days in the fields, participants sometimes forgot medication doses. Despite these obstacles, many participants still reported high ARV adherence and exceptional motivation to continue therapy. Conclusions: While reports from sub-Saharan Africa show excellent adherence to ARVs, concerns remain that these successes are not sustainable in the presence of widespread poverty and food insecurity. We provide further evidence on how food insecurity can compromise sustained ARV therapy in a resource-limited setting. Addressing food insecurity as part of emerging ARV treatment programs is critical for their long-term success

Transportation Costs Impede Sustained Adherence and Access to HAART in a Clinic Population in Southwestern Uganda: A Qualitative Study

The cost of transportation for monthly clinic visits has been identified as a potential barrier to antiretroviral (ARV) adherence in sub-Saharan Africa and elsewhere, although there is limited data on this issue. We conducted open-ended interviews with 41 individuals living with HIV/AIDS and attending a clinic in Mbarara, Uganda, to understand structural barriers to ARV adherence and clinical care. Almost all respondents cited the need to locate funds for the monthly clinic visit as a constant source of stress and anxiety, and lack of money for transportation was a key factor in cases of missed doses and missed medical appointments. Participants struggled with competing demands between transport costs and other necessities such as food, housing and school fees. Our findings suggest that transportation costs can compromise both ARV adherence and access to care. Interventions that address this barrier will be important to ensure the success of ARV programs in sub-Saharan Africa

Efficient algorithms for reconstructing gene content by co-evolution

<p>Abstract</p> <p>Background</p> <p>In a previous study we demonstrated that co-evolutionary information can be utilized for improving the accuracy of ancestral gene content reconstruction. To this end, we defined a new computational problem, the Ancestral Co-Evolutionary (ACE) problem, and developed algorithms for solving it.</p> <p>Results</p> <p>In the current paper we generalize our previous study in various ways. First, we describe new efficient computational approaches for solving the ACE problem. The new approaches are based on reductions to classical methods such as linear programming relaxation, quadratic programming, and min-cut. Second, we report new computational hardness results related to the ACE, including practical cases where it can be solved in polynomial time.</p> <p>Third, we generalize the ACE problem and demonstrate how our approach can be used for inferring parts of the genomes of <it>non-ancestral</it> organisms. To this end, we describe a heuristic for finding the portion of the genome ('dominant set’) that can be used to reconstruct the rest of the genome with the lowest error rate. This heuristic utilizes both evolutionary information and co-evolutionary information.</p> <p>We implemented these algorithms on a large input of the ACE problem (95 unicellular organisms, 4,873 protein families, and 10, 576 of co-evolutionary relations), demonstrating that some of these algorithms can outperform the algorithm used in our previous study. In addition, we show that based on our approach a ’dominant set’ cab be used reconstruct a major fraction of a genome (up to 79%) with relatively low error-rate (<it>e.g.</it> 0.11). We find that the ’dominant set’ tends to include metabolic and regulatory genes, with high evolutionary rate, and low protein abundance and number of protein-protein interactions.</p> <p>Conclusions</p> <p>The <it>ACE</it> problem can be efficiently extended for inferring the genomes of organisms that exist today. In addition, it may be solved in polynomial time in many practical cases. Metabolic and regulatory genes were found to be the most important groups of genes necessary for reconstructing gene content of an organism based on other related genomes.</p

Communications and Related Projects

Contains reports on three research projects.Office of Scientific Research and Development (OSRD) OEMsr-26

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell