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Tight reservoirs are considered one of the unconventional hydrocarbon reservoirs with low permeability and porosity, directly affecting the oil production rate rather than conventional reservoirs. Thereby, optimum enhanced oil recovery methods would help petroleum industries produce more oil volumes from these reservoirs. In this study, different chemical and thermal enhanced oil recoveries methods such as surfactant alternating gas (SAG), water alternating gas (WAG), surfactant and foam flooding, and carbon dioxide (continuous and cyclic) were experimentally investigated to measure oil recovery factor. According to the results of this study, 3.5% of surfactant concentration, 0.15 PV of surfactant slug size, and 0.75 PV was selected as the total surfactant injection volume was selected as the optimum concentration for the injectivity performances. SAG scenario provided the highest oil recovery factor among all injectivity scenarios. It is about 54% that indicated the best efficiency of enhanced oil recovery methods in tight reservoirs rather than conventional recovery methods. The second highest oil recovery factor is dedicated to the WAG injectivity scenario regarding the feasibility of CO2 phase through porous media. It is about 46%. Moreover, due to the -gas phase in WAG and SAG, water cut had fluctuated as the water and gas had been alternatively injected into the core samples.

To select the optimum methods, such criteria like reservoir heterogeneity, reservoir pressure, reservoir temperature, crude oil type API (American Petroleum Institute), and brine salinity. EOR methods contained water flooding, chemical flooding, nanofluids injection, CO2 (carbon dioxide) injection, SAGD/WAG (Surfactant assisted gas drainage/water alternative gas injection), and hybrid injection. Multi-criteria decision-making methods of FTOPSIS (a fuzzy technique for order preference by similarity to ideal solution) and FAHP (fuzzy analytic hierarchy process) were used to select the optimum in the EOR method. The hybrid injection is considered the preferable oil recovery enhancement method in both FTOPSIS and FAHP methods. It has a normalized weight of 74% and 23% for FTOPSIS and FAHP, respectively. In the FTOPSIS method, SAGD/WAG and CO2 methods are the second and third preferred enhanced oil recovery methods with the normalized weight of 65% and 56%, respectively. In the FAHP method, CO2 and SAGD/WAG methods are the second and third preferred enhanced oil recovery methods with the normalized weight of 19% and 14%.

Porosity estimation is one of the essential issues in petroleum industries to distinguish the reservoir characteristics properly. Therefore, it is of importance to predict porosity with the optimum way to reduce the logging tests. In this study, artificial neural network and fuzzy logics are considered efficient techniques to predict the Asmari formation’s porosity. The results of porosity estimation by intelligent neuro-phase method showed the ability of this method to estimate in complex conditions in Mansouri oilfield. Preparing data before training the neural network increases the power of the network in recognizing the appropriate pattern. In estimating the porosity in the Asmari reservoir of Mansouri field, gamma, acoustic, neutron and density and diameter measurements have a more influential role. Selecting the appropriate architecture for the neuro-phase network is effective in achieving more accurate results. This architecture includes selecting the type and number of membership functions for the inputs and the training algorithm with the appropriate number of iteration steps. The best estimation results by assigning four Gaussian membership functions to gamma image data, two Gaussian membership functions to each of the audio and neutron data, and three Gaussian membership functions to density image data and creating 40 laws in the data space. Inputs were obtained using a hybrid training algorithm. The average error of estimating porosity by the neuro-phase method in well C of Mansouri field is 1.28% in the validation data set, representing a correlation coefficient of 92.5% between the porosity extracted from the fuzzy neuro-fuzzy network and the porosity of the core.

Background: Women with polycystic ovary syndrome (PCOS) often change their metabolic profile over time to decrease levels of androgens while often gaining a propensity for the development of the metabolic syndrome. Recent discoveries indicate that microRNAs (miRNAs) play a role in the development of PCOS and constitute potential biomarkers for PCOS. We aimed to identify miRNAs associated with the development of an impaired metabolic profile in women with PCOS, in a follow-up study, compared with women without PCOS. Methods and materials: Clinical measurements of PCOS status and metabolic disease were obtained twice 6 years apart in a cohort of 46 women with PCOS and nine controls. All participants were evaluated for degree of metabolic disease (hypertension, dyslipidemia, central obesity, and impaired glucose tolerance). MiRNA levels were measured using Taqman® Array cards of 96 pre-selected miRNAs associated with PCOS and/or metabolic disease. Results: Women with PCOS decreased their levels of androgens during follow-up. Twenty-six of the miRNAs were significantly changed in circulation in women with PCOS during the follow-up, and twenty-four of them had decreased, while levels did not change in the control group. Four miRNAs were significantly different at baseline between healthy controls and women with PCOS; miR-103-3p, miR-139-5p, miR-28-3p, and miR-376a-3p, which were decreased in PCOS. After follow-up, miR-28-3p, miR-139-5p, and miR-376a-3p increased in PCOS women to the levels observed in healthy controls. Of these, miR-139-5p correlated with total testosterone levels (rho = 0.50, padj = 0.013), while miR-376-3p correlated significantly with the waist-hip ratio at follow-up (rho = 0.43, padj = 0.01). Predicted targets of miR-103-3p, miR-139-5p, miR-28-3p, and miR-376a-3p were enriched in pathways associated with Insulin/IGF signaling, interleukin signaling, the GNRH receptor pathways, and other signaling pathways. MiRNAs altered during follow-up in PCOS patients were enriched in pathways related to immune regulation, gonadotropin-releasing hormone signaling, tyrosine kinase signaling, and WNT signaling. Conclusions: These studies indicate that miRNAs associated with PCOS and androgen metabolism overall decrease during a 6-year follow-up, reflecting the phenotypic change in PCOS individuals towards a less hyperandrogenic profile.

Mixed-integer linear programming is adopted to translate the routing of service operation vessels that support the logistic aspects of the maintenance of offshore floating wind farms into mathematical language. The models attempt to help the decision-makers by providing quantified tools to screen out the optimal planning for preventive maintenance. The models search for the optimal offshore base location, vessel’s routing per day, vessel’s capacity, and vessel fleet composition that minimize the total fixed and variable infrastructure cost. The integration of the vehicle fleet size and mix problem, facility location–allocation problem, and vehicle-routing problem with time window advances the state of the art. A realistic case study is shown, and the results and discussions demonstrated that the practical insights of the solutions, as well as the identification of the route patterns through a navigation route table, may improve the decision planning of preventive maintenance.

Translatome remodelling controls stress-adaptive protein output. Here the authors reveal that in response to stimuli, eIF5A functions as a pH-regulated translation factor that responds to fermentation-induced acidosis affecting cellular metabolism.

On the example of the library and archival heritage of the Belarusian writer and savant Academician P. F. Glebka the cultural and historical ties of the Belarusian and Ukrainian peoples are considered. Documents from the personal archive and the book collection of the writer, including rare to date editions of the 1930s, the authors of which are the repressed Ukrainian literateurs, are introduced into scientific circulation.

Polycystic ovary syndrome (PCOS) remains one of the most common endocrine disorder in premenopausal women with an unfavorable metabolic risk profile. Here, we investigate whether biochemical hyperandrogenism, represented by elevated serum free testosterone, resulted in an aberrant circulating microRNA (miRNAs) expression profile and whether miRNAs can identify those PCOS women with metabolic syndrome (MetS). Accordingly, we measured serum levels of miRNAs as well as biochemical markers related to MetS in a case-control study of 42 PCOS patients and 20 Controls. Patients were diagnosed based on the Rotterdam consensus criteria and stratified based on serum free testosterone levels (≥0.034 nmol/l) into either a normoandrogenic (n = 23) or hyperandrogenic (n = 19) PCOS group. Overall, hyperandrogenic PCOS women were more insulin resistant compared to normoandrogenic PCOS women and had a higher prevalence of MetS. A total of 750 different miRNAs were analyzed using TaqMan Low-Density Arrays. Altered levels of seven miRNAs (miR-485-3p, -1290, -21-3p, -139-3p, -361-5p, -572, and -143-3p) were observed in PCOS patients when compared with healthy Controls. Stratification of PCOS women revealed that 20 miRNAs were differentially expressed between the three groups. Elevated serum free testosterone levels, adjusted for age and BMI, were significantly associated with five miRNAs (miR-1290, -20a-5p, -139-3p, -433-3p, and -361-5p). Using binary logistic regression and receiver operating characteristic curves (ROC), a combination panel of three miRNAs (miR-361-5p, -1225-3p, and -34-3p) could correctly identify all of the MetS cases within the PCOS group. This study is the first to report comprehensive miRNA profiling in different subgroups of PCOS women with respect to MetS and suggests that circulating miRNAs might be useful as diagnostic biomarkers of MetS for a different subset of PCOS.

Background:. Cell-enriched fat grafting has shown promising results for improving graft survival, although many questions remain unanswered. A large animal model is crucial for bridging the gap between rodent studies and human trials. We present a step-by-step approach in using the Göttingen minipig as a model for future studies of cell-enriched large volume fat grafting. Methods:. Fat grafting was performed as bolus injections and structural fat grafting. Graft retention was assessed by magnetic resonance imaging after 120 days. The stromal vascular fraction (SVF) was isolated from excised fat and liposuctioned fat from different anatomical sites and analyzed. Porcine adipose-derived stem/stromal cells (ASCs) were cultured in different growth supplements, and population doubling time, maximum cell yield, expression of surface markers, and differentiation potential were investigated. Results:. Structural fat grafting in the breast and subcutaneous bolus grafting in the abdomen revealed average graft retention of 53.55% and 15.28%, respectively, which are similar to human reports. Liposuction yielded fewer SVF cells than fat excision, and abdominal fat had the most SVF cells/g fat with SVF yields similar to humans. Additionally, we demonstrated that porcine ASCs can be readily isolated and expanded in culture in allogeneic porcine platelet lysate and fetal bovine serum and that the use of 10% porcine platelet lysate or 20% fetal bovine serum resulted in population doubling time, maximum cell yield, surface marker profile, and trilineage differentiation that were comparable with humans. Conclusions:. The Göttingen minipig is a feasible and cost-effective, large animal model for future translational studies of cell-enriched fat grafting.

The paper presents results of investigations of the obtained nanocomposite materials based on silver with addition of multiwall carbon nanotubes. The powder of carbon nanotubes content from 0.1 to 3 wt. % was produced by application of powder metallurgy methods, through mixing and high-energetic milling, and also chemical methods. Modification of carbon nanotubes included electroless deposition of silver particles on the carbon nanotube active surfaces and chemical reduction with strong reducing agent – sodium borohydride (NaBH4). The obtained powder mixtures were consolidated by SPS – Spark Plasma Sintering method. The formed composites were subjected to tests of relative density, electrical conductivity and electro-erosion properties. Detailed examinations of the structure with application of X-ray microanalysis, with consideration of carbon nanotubes distribution, were also carried out. The effect of manufacturing methods on properties of the obtained composites was observed.

The paper presents the study on manufacturing of nickel and cobalt powders by thermal plasma decomposition of the carbonates of these metals. It was shown the dependence of process parameters and grain size of initial powder on the composition of final product which was ether metal powder, collected in the container as well as the nanopowder with crystallite size of 70 - 90 nm, collected on the inner wall of the reaction chamber. The occurrence of metal oxides in the final products was confirmed and discussed.