Alpacas are one of four South American Camelid species living in the highlands of the Andes. Production of alpaca fiber contributes to the economy of the region and the livelihood of many rural ...families. Fiber quantity and quality are important and in need of a modern breeding program based on genomic selection to accelerate genetic gain. To achieve this is necessary to discover enough molecular markers, single nucleotide polymorphisms (SNPs) in particular, to provide genome coverage and facilitate genome wide association studies to fiber production characteristics. The aim of this study was to discover alpaca SNPs by genotyping forty alpaca DNA samples using the BovineHD Genotyping Beadchip. Data analysis was performed with GenomeStudio (Illumina) software. Because different filters and thresholds are reported in the literature we investigated the effects of no-call threshold (≥0.05, ≥0.15, and ≥0.25) and call frequency (≥0.9 and =1.0) in identifying positive SNPs. Average GC Scores, calculated as the average of the 10% and 50% GenCall scores for each SNP (≥0.70) and the GenTrain score ≥ 0.25 parameters were applied to all comparisons. SNPs with minor allele frequency (MAF) ≥ 0.05 or ≥ 0.01 were retained. Since detection of SNPs is based on the stable binding of oligonucleotide probes to the target DNA immediately adjacent to the variant nucleotide, all positive SNP flanking sequences showing perfect alignments between the bovine and alpaca genomes for the first 21 or 26 nucleotides flanking the variant nucleotide at either side were selected. Only SNPs localized in one scaffold were assumed unique. Unique SNPs identified in both reference genomes were kept and mapped on the Vicugna_pacos 2.0.2 genome. The effects of the no-call threshold ≥ 0.25, call frequency = 1 and average GC ≥ 0.7 were meaningful and identified 6756 SNPs of which 400 were unique and polymorphic (MAF ≥ 0.01). Assignment to alpaca chromosomes was possible for 292 SNPs. Likewise, 209 SNPs were localized in 202 alpaca gene loci and 29 of these share the same loci with the dromedary. Interestingly, 69 of 400 alpaca SNPs have 100% similarity with dromedary.
Experimental observations clearly show that dispersed-phase pore-scale flow effects of emulsion flow are responsible for drop entrapment at pore throats and this strongly depends on local capillary ...number. As a result, this dimensionless number is key to parametrize emulsion flooding for EOR purposes. In this work, we incorporate capillary number effects that influence two well-known oil recovery mechanisms observed in continuous emulsion flooding, namely a microscopic increased pore-level efficiency, and a macroscopic mobility control or flood conformance. These mechanisms can be advantageously exploited in a newly proposed process denominated water-alternated-emulsion (WAE) injection, which is the focus of this article. To this end, a capillary number dependence was added to our initial model
17
. The resulted parametrization of relative permeability curves as functions of the capillary number was implemented in a Matlab open-source code. A parametric analysis of a 1/4 five-spot geometry used on the first layer of the Tabert Formation shows that capillary number can significantly impact emulsion mobility control potential that has been shown to contribute to the observed oil recovery enhancement. Emulsions with adequate drop-to-pore size ratio and interfacial properties optimize emulsion mobility reduction and sweep efficiency. Results show that timing of the emulsion injection can promote conformance improvement and accelerate oil production. Mitigation of high injection pressure observed in continuous emulsion flooding is possible during cyclic WAE injection without significant oil recovery impairment.
Emulsion flooding has been shown to offer a significant potential as an enhanced-oil recovery (EOR) strategy. Moreover, recovery mechanisms of several chemical EOR methods, including alkaline and ...alkaline-surfactant flooding applied to heavy oil, are linked to in situ formation of emulsions. To enable emulsion flooding designs, EOR mechanisms must be adequately represented in reservoir simulators to upscale pore-level effects to the continuum in porous media. In this work, we have incorporated two known effects of emulsion flooding, namely an increased pore-level displacement efficiency and a macroscopic mobility control through changes in relative permeability curves. To this end, we used three types of emulsion and oil relative permeability curves: (1) through history matching of unsteady-state emulsion flooding data; (2) from direct use of Darcy law on steady state two-phase flow experiments; and (3) synthetic curves at which pore level displacement efficiency is characterized by the curve end-point saturation and the macroscopic sweep efficiency by the water curve end-point. A parametric analysis of a 1/4 of a 5-spot geometry shows that the displacement efficiency effect is predominantly responsible for the incremental oil recovery observed experimentally. The results also indicate that the amount of oil recovered depends on the complete relative permeability curves, and not only the end-point values. These findings imply that properly designed emulsions should produce significant recovery benefits.
•Macroscopic model of oil displacement by emulsion injection based on Kr curves.•Pore-level displacement efficiency influences oil recovery more than mobility control.•Emulsion injection benefits are obtained even in favorable mobility ratio scenarios.•Early emulsion injection leads to uniform sweeps and accelerates oil production.
Machine learning meets genome assembly Padovani de Souza, Kleber; Setubal, João Carlos; Ponce de Leon F. de Carvalho, André Carlos ...
Briefings in bioinformatics,
11/2019, Letnik:
20, Številka:
6
Journal Article
Recenzirano
Abstract
Motivation: With the recent advances in DNA sequencing technologies, the study of the genetic composition of living organisms has become more accessible for researchers. Several advances ...have been achieved because of it, especially in the health sciences. However, many challenges which emerge from the complexity of sequencing projects remain unsolved. Among them is the task of assembling DNA fragments from previously unsequenced organisms, which is classified as an NP-hard (nondeterministic polynomial time hard) problem, for which no efficient computational solution with reasonable execution time exists. However, several tools that produce approximate solutions have been used with results that have facilitated scientific discoveries, although there is ample room for improvement. As with other NP-hard problems, machine learning algorithms have been one of the approaches used in recent years in an attempt to find better solutions to the DNA fragment assembly problem, although still at a low scale.
Results: This paper presents a broad review of pioneering literature comprising artificial intelligence-based DNA assemblers—particularly the ones that use machine learning—to provide an overview of state-of-the-art approaches and to serve as a starting point for further study in this field.
Interleukin-2 (IL2) is a growth factor for several immune cells and its function depends on its binding to IL2Rs in the cell membrane. The most accepted model for the assembling of IL2-IL2R complexes ...in the cell membrane is the Affinity Conversion Model (ACM). This model postulates that IL2R receptor association is sequential and dependent on ligand binding. Most likely free IL2 binds first to IL2Rα, and then this complex binds to IL2Rβ, and finally to IL2Rγ (γc). However, in previous mathematical models representing this process, the binding of γc has not been taken into account. In this work, the quantitative contribution of the number of IL2Rγ chain to the IL2-IL2R apparent binding affinity and signaling is studied. A mathematical model of the affinity conversion process including the γ chain in the dynamic, has been formulated. The model was calibrated by fitting it to experimental data, specifically, Scatchard plots obtained using human cell lines. This paper demonstrates how the model correctly explains available experimental observations. It was estimated, for the first time, the value of the kinetic coefficients of IL2-IL2R complexes interaction in the cell membrane. Moreover, the number of IL2R components in different cell lines was also estimated. It was obtained a variable distribution in the number of IL2R components depending on the cell type and the activation state. Of most significance, the study predicts that not only the number of IL2Rα and IL2Rβ, but also the number of γc determine the capacity of the cell to capture and retain IL2 in signalling complexes. Moreover, it is also showed that different cells might use different pathways to bind IL2 as consequence of its IL2R components distribution in the membrane.
InAs/GaAs quantum dot solar cell structures have been grown by metal organic vapor phase epitaxy, using partial capping of the quantum dots plus a subsequent thermal anneal. The optical ...characteristics of the InAs quantum dot layers have been studied as a function of the GaAs capping layer thickness and annealing temperature. We observe that a thinner capping layer and a higher annealing temperature result in lower non-radiative defect density and in improved quantum dot size homogeneity, leading to intense and sharp photoluminescence emission at low temperatures. We use an effective mass approximation model to correlate the photoluminescence emission characteristics to the quantum dot composition and dimensions. The resulting InAs/GaAs intermediate band solar cells show the best performance for the case of a 3 nm thick capping layer and annealing at 700 °C.
•Different capping techniques are analyzed using TEM and PL results.•QD composition and morphological evolution during capping procedure are described.•Theoretical calculations are employed to describe the obtained results.•A thin capping layer annealed at higher temperature provides interconnected QDs.•The optimized capping procedure improves PV performance by a factor higher than 3.
Recent breakthroughs in cryogenic silicon detector technology allow for the observation of single electron-hole pairs released via particle interactions within the target material. This implies ...sensitivity to energy depositions as low as the smallest band gap, which is ∼ 1.2 eV for silicon, and therefore sensitivity to eV / c2-scale bosonic dark matter and to thermal dark matter at masses below 100 MeV / c2. Various interaction channels that can probe the lowest currently accessible masses in direct searches are related to standard photoelectric absorption. In any of these respective dark matter signal models any uncertainty on the photoelectric absorption cross section is propagated into the resulting exclusion limit or into the significance of a potential observation. Using first-time precision measurements of the photoelectric absorption cross section in silicon recently performed at Stanford University, this article examines the importance having accurate knowledge of this parameter at low energies and cryogenic temperatures for these dark matter searches.
The origin for high hole concentration in Mg‐doped GaN films grown by metal‐modulated epitaxy has been explored. We observe a Mg acceptor band characterized by a broad emission without phonon ...replicas and a high energy tail that overlaps with the valence band of GaN, giving rise to a reduced effective Mg activation energy. We attribute the high hole concentrations to the reduction of compensating nitrogen vacancy concentration and to effectively dispersed Mg atoms, which are incorporated into the lattice as single substitutional atoms. This has been achieved by a low temperature growth, a decrease in the III/V ratio, and a planar growth interface that results from the layer‐by‐layer approach using the metal‐modulated epitaxial technique.
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