Prediction of Gas Consumption During Hydrate Formation With or Without the Presence of Inhibitors in a Batch System Using the Esmaeilzadeh-Roshanfekr Equation of State

In this work, the ability of different equations of state to predict the gas consumption during hydrate formation in a batch system has been evaluated using the model of Kashchiev and Firoozabadi. The first state equation used for this purpose was the one developed by Esmaeilzadeh and Roshanfekr. The predictions were then extended using PR, SRK and Patel Teja equations. The ability of the different equations of state were evaluated for single gases of methane and ethane and their mixtures adding to more than a thousand experimental data existing in the literature. The consumption of gas during hydrate formation was predicted both with and without the presence of kinetic inhibitors. In the case of double hydrate formation, the state equation based on the Kashchiev and Firoozabadi model for simple gas was modified by lumping the component of hydrate formation as a pseudocomponent. The results of this extension study show that the equation developed by Esmaeilzadeh and Roshanfekr is just as suitable for predicting gas consumption during hydrate formation as any of the other well known state equations such as PR and SRK

Prevalence and new histopathological aspects of Haemoproteus spp. in pigeons from Iran

ΔΕΝ ΔΙΑΤΙΘΕΤΑΙ ΠΕΡΙΛΗΨΗHaemoproteus spp. is pathogenic protozoan that effecting blood circulatory system of birds. The present study was undertaken to evaluate the presence of Haemoproteus spp. in pigeons from Iran and associatedhistopathological changes. A total of 108 blood samples were taken from pigeons to investigate Haemoproteus spp. presence by blood smear and semi-nested PCR targeting the cytochrome b gene methods. Also, to evaluate histopathological changes 12 infected pigeons to Haemoproteus were sacrificed and studied. 34.2% of pigeons infected with Haemoproteus showed macro and microgametocytes in their erythrocytes while based on the molecular method 63.8% were infected. Focal lymphocytic aggregates, pigmentation and cell swelling were the main histopathological lesions in infected livers. Multifocal non- suppurative interstitial nephritis, pigmentation and splenic lymphoid hyperplasia were also seen in the infected pigeons. Mild lymphocytic myocarditis in the heart of one pigeon was the other finding. No histopathological changes were seen in brain, intestine, and pancreas. Schizonts with variable shapes and sizes were detected in infected livers, lungs, kidneys, and spleens but megaloschizonts were not found. This study also reports the molecular prevalence of Haemoproteus spp. in Ira

Evaluation of Two-Phase Turbulence Closure Models Modifications in Near Wall Region of Boundary Layer

Previous study of authors showed that kappa-taf turbulence model has a good accuracy for prediction of hydrodynamic behaviour of near wall turbulence in a gas-solid boundary layer flow. In that study two-phase kappa-taf model was derived from Yokomine et al. modified kappa-epsilon model. In the present study, a new version of two phase kappa-taf turbulence model has been presented. In this model we use Adeniji et.al. modifications to account for the effect of solid particles both on the turbulence kinetic energy and it's dissipation rate. The new modified kappa-taf has been compared with the later version of kappa-taf for prediction of flow behaviour in near wall region of two-phase boundary layer. The governing equations for two-phase boundary layer flow with Eulerin-Eulerian approach by two different modified kappa-taf turbulence models have been solved numerically using finite volume method. In comparison with available experimental data, the obtained results by modified kappa-taf, based on Yokomine et al. modifications, have better agreement than modified kappa-taf based on Adeniji et al. model

Two-Stage Inverter Based on Combination of High Gain DC-DC Converter and Five-Level Inverter for PV-Battery Energy Conversion

This paper proposes a new two-stage inverter based on transformer-less high gain DC-DC converter for energy conversion of a photovoltaic system. The designed system consists of a high gain DC-DC converter cascaded with a three-phase inverter. The proposed DC-DC converter has a simple structure, and it has one switch in its structure. The output voltage of the DC-DC converter supplies DC source for the inverter part of the multi-stage inverter. The advanced two-stage inverter sample was fabricated, then the findings of the acquired simulation and hardware warranted the configuration applicability. Finally, the MATLAB/SIMULINK is employed for the simulation of PV-battery system. The obtained results revel that the proposed power conversion system effectively chases the load and generation fluctuations and also properly handles the power mismatches in PV-battery system

The prevalence of depression among Iranian infertile couples: an update systematic review and meta-analysis

Background: Depression is a common mental disorder. Infertility can lead to depression. The current systematic review and meta-analysis were conducted to estimate the pooled prevalence of depression among Iranian infertile couples. Seven electronic databases (Google Scholar, MagIran, SID, Science Direct, PubMed, Scopus, Web of Science) were searched, up to August 2019, for relevant published studies. The pooled prevalence of depression also pooled mean of depression score was determined using a random-effects model with a 95 confidence interval (95 CI). All analyses performed using Stata ver11 (Stata Corporation, College Station, TX, USA). The 0.05 was considered a significant level. The main body: Totally, 230 studies were retrieved and 31 studies included in the meta-analysis. The pooled prevalence of depression among infertile couples was about 35.3 (95 CI 24.1�46.5), and the prevalence of depression among females and males was 48.7 (95 CI 24.0�73.3) and 9 (95 CI 0 to 23.7), respectively. Conclusions: Our findings suggest a high prevalence of depression in infertile couples. The results can highlight an important and growing mental disorder among infertile couples that may be overlooked. © 2020, The Author(s)

Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification

Attribution methods are an easy to use tool for investigating and validating machine learning models. Multiple methods have been suggested in the literature and it is not yet clear which method is most suitable for a given task. In this study, we tested the robustness of four attribution methods, namely gradient*input, guided backpropagation, layer-wise relevance propagation and occlusion, for the task of Alzheimer's disease classification. We have repeatedly trained a convolutional neural network (CNN) with identical training settings in order to separate structural MRI data of patients with Alzheimer's disease and healthy controls. Afterwards, we produced attribution maps for each subject in the test data and quantitatively compared them across models and attribution methods. We show that visual comparison is not sufficient and that some widely used attribution methods produce highly inconsistent outcomes

Separating mouse malignant cell line (EL4) from neonate spermatogonial stem cells utilizing microfluidic device in vitro

Background: Some children who have survived cancer will be azoospermic in the future. Performing isolation and purification procedures for spermatogonial stem cells (SSC) is very critical. In this regard, performing the process of decontamination of cancerous cells is the initial step. The major objective of the present study is to separate the malignant EL4 cell line in mice and spermatogonial stem cells in vitro. Methods: The spermatogonial stem cells of sixty neonatal mice were isolated, and the procedure of co-culturing was carried out by EL4 which were classified into 2 major groups: (1) the control group (co-culture in a growth medium) and (2) the group of co-cultured cells which were separated using the microfluidic device. The percentage of cells was assessed using flow cytometry technique and common laboratory technique of immunocytochemistry and finally was confirmed through the laboratory technique of reverse transcription-polymerase chain reaction (RT-PCR). Results: The actual percentage of EL4 and SSC after isolation was collected at two outlets: the outputs for the smaller outlet were 0.12 for SSC and 42.14 for EL4, while in the larger outlet, the outputs were 80.38 for SSC and 0.32 for EL4; in the control group, the percentages of cells were 21.44 for SSC and 23.28 for EL4 (based on t test (p � 0.05)). Conclusions: The present study demonstrates that the use of the microfluidic device is effective in separating cancer cells from spermatogonial stem cells. © 2020 The Author(s)

Shutdown Policies with Power Capping for Large Scale Computing Systems

International audienceLarge scale distributed systems are expected to consume huge amounts of energy. To solve this issue, shutdown policies constitute an appealing approach able to dynamically adapt the resource set to the actual workload. However, multiple constraints have to be taken into account for such policies to be applied on real infrastructures, in particular the time and energy cost of shutting down and waking up nodes, and power capping to avoid disruption of the system. In this paper, we propose models translating these various constraints into different shutdown policies that can be combined. Our models are validated through simulations on real workload traces and power measurements on real testbeds.

Correction to: Separating mouse malignant cell line (EL4) from neonate spermatogonial stem cells utilizing microfluidic device in vitro (Stem Cell Research & Therapy, (2020), 11, 1, (191), 10.1186/s13287-020-01671-1)

The original article 1 displays incorrect affiliation information; the correct affiliations for each author can be viewed in this Correction article. © 2020, The Author(s)