Influence of chemical fertilizers and bioinoculants on growth and yield of sunflower (Helianthus annuus L.)

The present study was conducted to investigate and compare the effect of applying various levels of chemical fertilizers and bioinoculants on the growth and yield of sunflower during the 2017-2018 crop year in Hamedan, Iran. This study was executed as two factorial experiments, as a randomized complete block design in three repetitions. Chemical fertilizers containing nitrogen (N) and phosphorus (P) were used in the first experiment, and nitrogen-fixing (NI) and phosphate-solubilizing (BI) bioinoculants were used in the second experiment. The experimental treatments included applying a urea fertilizer (N0=0, N1=45, N2=90 kg pure nitrogen/ha) and a triple superphosphate (P0=0, P1=40, P2=80 kg pure phosphorus/ha), as well as a nitroxin biofertilizer (NI0=0, NI1=0.5, NI2=1 L/ha) and a biophosphorus (BI0=0, BI1=0.5, BI2=1 L/ha). The results indicated that the highest levels of leaf dry weight, number of seeds per head, head diameter, head weight, seed yield, and the plant\u27s biological yield were obtained for the chemical treatment (N2P2) and biological treatment of (NI2BI2). Group comparisons between the chemical and biological treatments did not show a significant difference for any of the studied characteristics, therefore, the results of this study conclude that the investigated levels of bioinoculants could be appropriate alternatives to chemical fertilizers

Forecasting of Intelligent Thermal Performance in Two Types of Solar Air Heater Using Artificial Neural Networks

Applying solar collectors is a popular tool to harness solar energy. In this research, a flat plate solar air collector with two types of glass cover, including slatted and flat, was investigated under direct solar radiation. The study was conducted to evaluate the capability of Perceptron Neural Network for modeling and predicting the efficiency of heat collectors by input parameters, input fluid mass flow, inlet and outlet air temperature from collector, temperature of the absorber, its thickness and porosity, and also solar energy. The tests were conducted in three replications on very clear sky days during 11 to 13 O′ clock (average solar energy was reported to be 1040 Wm-2 during the interval). Values obtained from tests were compared with the predicted values of the neural network. According to obtained coefficient of determination, for flat (0.98) and slatted (0.99) glass cover, it has been concluded that using ANN is an accurate method to predict the thermal performance of solar air collectors

Willingness to Communicate in L2: Theoretical Roots and Pedagogical Implications

Abstract. This literature review paper provides the readers with the presentation of the theoretical and empirical issues pertinent to willingness to communicate in L2. In this paper, first the roots of this variable are presented, then different conceptualizations of the variable are discussed in brief. It also provides the readers with the review of the most prominent studies conducted on willingness to communicate. The last section of this paper deals with the pedagogical implications related to willingness to communicate

HRCTCov19 -- A High-Resolution Chest CT Scan Image Dataset for COVID-19 Diagnosis and Differentiation

Introduction: During the COVID-19 pandemic, computed tomography (CT) was a popular method for diagnosing COVID-19 patients. HRCT (High-Resolution Computed Tomography) is a form of computed tomography that uses advanced methods to improve image resolution. Publicly accessible COVID-19 CT image datasets are very difficult to come by due to privacy concerns, which impedes the study and development of AI-powered COVID-19 diagnostic algorithms based on CT images. Data description: To address this problem, we have introduced HRCTCov19, a new COVID-19 high-resolution chest CT scan image dataset that includes not only COVID-19 cases of Ground Glass Opacity (GGO), Crazy Paving, and Air Space Consolidation but also CT images of cases with negative COVID-19. The HRCTCov19 dataset, which includes slice-level, and patient-level labels, has the potential to aid COVID-19 research, especially for diagnosis and differentiation using artificial intelligence algorithms, machine learning, and deep learning methods. This dataset is accessible through the web at: http://databiox.com and includes 181,106 chest HRCT images from 395 patients with four labels: GGO, Crazy Paving, Air Space Consolidation, and Negative. Keywords: COVID-19, CT scan, Computed Tomography, Chest Image, Dataset, Medical ImagingComment: 5 pages, 2 figures and 1 tabl

The Effect of Low-Power Laser Therapy on the TGF/β Signaling Pathway in Chronic Kidney Disease: A Review

Objective: The purpose of this study is to investigate the effects of low-power lasers on kidney disease by investigating several studies.Methods: A number of articles from 1998 to 2019 were chosen from the sources of PubMed, Scopus, and only the articles studying the effect of low-power lasers on kidney disease were investigated.Results: After reviewing the literature, 21 articles examining only the effects of low-power lasers on kidney disease were found. The results of these studies showed that the parameter of the low-power laser would result in different outcomes. So, a low-power laser with various parameters can be effective in the treatment of kidney diseases such as acute kidney disease, diabetes, glomerulonephritis, nephrectomy, metabolic syndrome, and kidney fibrosis. Most studies have shown that low-power lasers can affect TGFβ1 signaling which is the most important signaling in the treatment of renal fibrosis.Conclusion: Lasers can be effective in reducing or enhancing inflammatory responses, reducing fibrosis factors, and decreasing reactive oxygen species (ROS) levels in kidney disease and glomerular cell proliferation

Predicting the Incidence and Trend of Breast Cancer Using Time Series Analysis for 2007-2016 in Qazvin

Introduction: Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The aim of this study was to analyze the trend and predict the incidence of breast cancer using time series analysis. Methods: In this study, data on breast cancer incidence in Qazvin province between 2007 and 2016 were analyzed using time series analysis with autoregressive integrated moving average (ARIMA) modeling to forecast the future pattern. The Box-Jenkins time series model and its diagnosis and evaluation methods were used to show the trend and forecasting the next year new cancers. To describe and fit the appropriate models, R statistical software version 3.6.3 was used. Results: Between 2007 and 2016, a total number of 1229 new patients had been registered (monthly mean [SD]: 10.24 [1.03]). Although the overall trend in the raw number of new breast cancer cases has been increasing over time, the change in observations over time has been increasing and decreasing. According to Bartlett test results, the variances of the data were not constant. Also, according to the results of Kolmogorov-Smirnov test, breast cancer series data were not normal. Among the studied models, ARIMA (1, 1, 1) was selected due to lower AIC criteria than other models, and this model was selected as the final model for predicting breast cancer for the next year. The confidence interval of the predicted values was relatively narrow, which indicates the appropriateness of the final model in the prediction. Conclusion: Time series analysis is an efficient tool to model the past and future data on the raw number of new cancer cases, and the goodness-of-fit indicators of the model showed that the Box-Jenkins model is a reliable model for fitting similar data. Keywords: Breast Cancer, Seasonal Trend, Time Series Analysis, Ira

Restoration of Harmane Induced Memory Consolidation Deficit by Alpha-lipoic Acid in Male Mice

Introduction: there has been a growing number of publications focusing on the effect of beta-carbolines (e.g., harmane) on cognitive behaviors such as different stages of memory formation process. Moreover, several studies have stated that Alpha-lipoic acid (ALA) induces some molecular pathways effects including antioxidant effect and reduction of inflammation process. Thus, in the lines that follow, the question of whether ALA could alter memory consolidation deficit caused by harmane in the male NMRI mice will be addressed. Materials and Methods: The data for this study were collected by step-down inhibitory avoidance task with one trial protocol for evaluation of memory consolidation. The ALA (35 mg/kg) was injected intraperitoneally immediately after training followed by subthreshold and effective doses of harmane (2.5, 5 and 10 mg/kg) with 15-minute interval period. Results: The results show that post-training injection of the highest dose of harmane (10 mg/kg) lowers step-down latency, indicating the amnesia induced by harmane (P<.001). In addition, similar injection of subthreshold dose of ALA (35 mg/kg), 15 minutes before injection of subthreshold and effective doses of harmane, restores step-down latency caused by higher dose of harmane (P<.001) without its effect on the responses induced by subthreshold doses of harmane, indicating benefit effect of ALA on amnesia induced by harmane. Conclusion: An implication of this study is the possibility that ALA can reverse the amnesia induced by harmane. Therefore, future studies on this topic such as molecular mechanisms are recommended. &nbsp

Investigation of Chronic Low-Dose Ionizing Radiation Effect on Gene Expression Profile of Human HUVECs Cells

Introduction: Understanding molecular mechanism of chronic low-dose ionizing radiation (LDIR) effects on human body is subject of many researches. Several aspects of cell function such as cell proliferation, apoptosis, inflammation, and tumorigenesis are affected by LDIR. Detection of the main biological process that is targeted by LIDR via network analysis is the main aim of this study.   Methods: GSE66720 including gene expression profiles of human umbilical vein endothelial cells (HUVECs) included irradiated and control cells is downloaded from gene expression omnibus (GEO). The significant differentially Expressed genes (DEGs) are determined and analyzed via protein-protein interaction (PPI) network analysis to find the central individuals. The main cell function which was related to the central nodes was introduced. Results: Among 64 queried DEGs 48 genes were recognized by STRING database. Five hub nodes including; C-X-C motif chemokine ligand 8 (CXCL8), intercellular adhesion molecule 1 (ICAM1), Melanoma growth-stimulatory activity/growth-regulated protein α (CXCL1), vascular cell adhesion molecule 1 (VCAM-1), and nerve growth factor (NGF) were introduced as hub nodes. Conclusion: Findings indicates that inflammation is the main initial target of LDIR in cellular level which is associated with alteration in the other essential functions of the irradiated cells

Hypofractionated Radiation Versus Conventional Fractionated Radiation: A Network Analysis

Hypofractionated Versus Conventional Fractionated Radiation: A Network Analysis Introduction: Conventional fractionated (CF) and hypofractionated (HF) are two radiotherapy methods against cancer which are applied in medicine. Understanding efficacy and molecular mechanism of two methods implies more investigations. In the present study proteomic findings about the mentioned methods relative to the controls are analyzed via network analysis.  Methods: The significant differentially expressed proteins (DEPs) of prostate cancer (PCa) cell line DU145 in response to CF and HF radiation therapy versus controls were extract from literature. The protein-protein interaction (PPI) networks were constructed via STRING database via cytoscape software. The Networks were analyzed by “NetworkAnalyzer” to determine hub DEPs. Results: Number of 126 and 63 significant DEPs were identified for treated DU145 with CF and HF radiation respectively. The PPI networks were constructed by the queried DEPs plus 100 first neighbors. ALB, CD44, THBS1, EPCAM, F2, KRT19, and MCAM were highlighted as common hubs. VTM, OCLN, HSPB1, FLNA, AHSG, and SERPINC1 were appeared as discriminator hub between the studied cells. Conclusion: The 70% of hubs were common between CF and HF conditions and induce radio-resistance activity in the survived cells. Six central proteins were introduced that discriminate function of the two group of irradiated cells. Based on these finding it seems that DU145-CF cells are more radio-resistant relative to the DU145-UF cells

Er:YAG Laser and Cyclosporin A Effect on Cell Cycle Regulation of Human Gingival Fibroblast Cells

Introduction: Periodontitis is a set of inflammatory disorders characterized by periodontal attachment loss and alveolar bone resorption. Because of deficiency in periodontitis mechanical therapy, this study was aimed to explore the molecular influence of the erbium-doped: yttrium aluminum garnet (Er:YAG) laser and cyclosporin A (CsA) on human gingival fibroblasts (HGFs) for improvement in periodontal diseases therapy.Methods: We focused on articles that studied the proteome profiles of HGFs after treatment with laser irradiation and application of CsA. The topological features of differentially expressed proteins were analyzed using Cytoscape Version 3.4.0 followed by module selection from the protein-protein interaction (PPI) network using Cluster ONE plugin. In addition, we performed gene ontology (GO) enrichment analysis for the densely connected region and key proteins in both PPI networks.Results: Analysis of PPI network of Er:YAG laser irradiation on HGFs lead to introducing YWHAZ, VCP, HNRNPU, YWHAE, UBA52, CLTC, FUS and IGHG1 as key proteins while similar analysis revealed that ACAT1, CTSD, ALDOA, ANXA2, PRDX1, LGALS3, ARHGDI and EEF1A1 are the crucial proteins related to the effect of drug. GO enrichment analysis of hub-bottleneck proteins of the 2 networks showed the different significant biological processes and cellular components. The functional enrichments of module of Er:YAG laser network are included as fatty acid transmembrane transport, cytokinesis, regulation of RNA splicing and asymmetric protein localization. There are not any significant clusters in network of HGF treated by CsA.Conclusion: The results indicate that there are 2 separate biomarker panels for the 2 treatment methods