Investigating the Effect of Spatial Distribution and Spatiotemporal Information on Speciation using Individual-Based Ecosystem Simulation

In this paper, we investigate the impact of species’spatial and spatiotemporal distribution information onspeciation, using an individual-based ecosystem simulation(Ecosim). For this purpose, using machine learning techniques,we try to predict if one species will split in near future. Because ofthe imbalanced nature of our dataset we use smote algorithm tomake a relatively balanced dataset to avoid dismissing the minorclass samples. Experimental results show very good predictionsfor the test set generated from the same run as the learning set. Italso shows good results on test sets generated from different runsof Ecosim. We also observe superior results when we use, for thelearning set, a run with more species compare to a run with lessspecies. Finally we can conclude that spatial and spatiotemporalinformation are very effective in predicting speciation

Understanding the Role of Social Media in Health Attitude Change among Older Adults

The power of social media to connect people and let them share knowledge and information provides a great opportunity for older adults, arguably more so than for other age groups, to take advantage of this technology to improve their health as they are more susceptible to health related issues and complications. In this work-in-progress research we aim to uncover the factors that make social media health interventions effective for older adults to persuade them to change their health attitudes and the relative importance of each of these factor. Based on the principles of the Health Belief Model and the Elaboration Likelihood Model and unique characteristics of social media, our research model proposes that perceived message credibility, attractiveness, and emotional support are more important determinants of health related perceptions and consequently the intention to engage in a health specific behavior than message quality in older adults compared to other age groups

Individual-Based Modeling and Data Analysis of Ecological Systems Using Machine Learning Techniques

Artificial life (Alife) studies the logic of living systems in an artificial environment in order to gain a deeper insight of the complex processes and governing rules in such systems. EcoSim, an Alife simulation for ecological modeling, is an individual-based predator-prey ecosystem simulation and a generic platform designed to investigate several broad ecological questions, as well as long-term evolutionary patterns and processes in biology and ecology. Speciation and extinction of species are two essential phenomena in evolutionary biology. Many factors are involved in the emergence and disappearance of species. Due to the complexity of the interactions between different factors, such as interaction of individuals with their environment, and the long time required for the observation, studying such phenomena is not easy in the real world. Using data sets obtained from EcoSim and machine learning techniques, we predicted speciation and extinction of species based on numerous factors. Experimental results showed that factors, such as demographics, genetics, and environment are important in the occurrence of these two events in EcoSim.We identified the best species-area relationship (SAR) models, using EcoSim, along with investigating how sampling approaches and sampling scales affect SARs. Further, we proposed a machine learning approach, based on extraction of rules that provide an interpretation of SAR coefficients, to find plausible relationships between the models\u27 coefficients and the spatial information that likely affect SARs. We found the power function family to be a reasonable choice for SAR. Furthermore, the simple power function was the best ranked model in nested sampling amongst models with two coefficients. For some of the SAR model coefficients, we obtained clear correlations with spatial information, thereby providing an interpretation of these coefficients. Rule extraction is a method to discover the rules explaining a predictive model of a specific phenomenon. A procedure for rule extraction from Random Forest (RF) is proposed. The proposed methods are evaluated on eighteen UCI machine learning repository and four microarray data sets. Our experimental results show that the proposed methods outperform one of the state-of-the art methods in terms of scalability and comprehensibility while preserving the same level of accuracy

Functional expression and impact of testis-specific gene antigen 10 in breast cancer: a combined in vitro and in silico analysis

Introduction: Testis-specific gene antigen 10 (TSGA10) is a less-known gene, which is involved in the vague biological paths of different cancers. Here, we investigated the TSGA10 expression using different concentrations of glucose under hypoxia and also its interaction with the hypoxia-inducible factor 1 (HIF-1). Methods: The breast cancer MDA-MB-231 and MCF-7 cells were cultured with different concentrations of glucose (5.5, 11.0 and 25.0 mM) under normoxia/hypoxia for 24, 48, and 72 hours and examined for the HIF-1α expression and cell migration by Western blotting and scratch assays. The qPCR was employed to analyze the expression of TSGA10. Three-dimensional (3D) structure and the energy minimization of the interacting domain of TSGA10 were performed by MODELLER v9.17 and Swiss-PDB viewer v4.1.0/UCSF Chimera v1.11. The UCSF Chimera v1.13.1 and Hex 6.0 were used for the molecular docking simulation. The Cytoscape v3.7.1 and STRING v11.0 were used for protein-protein interaction (PPI) network analysis. The HIF-1a related hypoxia pathways were obtained from BioModels database and reconstructed in CellDesigner v4.4.2. Results: The increased expression of TSGA10 was found to be significantly associated with the reduced metastasis in the MDA-MB-231 cells, while an inverse relationship was seen between the TSGA10 mRNA level and cellular migration but not in the MCF-7 cells. The C-terminal domain of TSGA10 interacted with HIF-1α with high affinity, resulting in PPI network with 10 key nodes (HIF-1α, VEGFA, HSP90AA1, AKT1, ARNT, TP53, TSGA10, VHL, JUN, and EGFR). Conclusions: Collectively, TSGA10 functional expression alters under the hyper-/hypo-glycemia and hypoxia, which indicates its importance as a candidate bio-target for the cancer therapy

Taking Advantage of Using Professionally-Oriented Social Network Sites: The Role of Users’ Actions and Profiles

The main objective of this research is to propose a model that explains the process by which individuals develop social capital through using Professionally-Oriented Social Network Sites (P-SNSs) such as LinkedIn. The theoretical framework of the proposed research draws upon the extant literature in social network analysis and social capital theory. The proposed research model aims to explain how people’s investment on their social networks by building their profiles and actively participating on P-SNSs can lead to developing sources of social capital which, in turn, can provide them valuable benefits. Our research results show that profile disclosure and active participation positively affect perceived social connectedness. However, only profile disclosure positively affects network size, and there is no association between active participation and network size. This study differs from previous studies in this field in that it highlights the role of one’s profile in the social capital formation process on P-SNSs. \ Keywords: \ Social network sites, social capital, social network analysis, social connectedness, networking value, LinkedIn

Preliminary results of post fire resprouting of manna oak (Quercus brantii Lindl.) in the Zagros forests, Kermanshah

Fire in the Zagros forests disturbs some parts of these forests every year. Manna oak species (Quercus brantii) as the main species of these forests is stimulated by fire. In order to investigate post-fire resprouting of Quercus brantii, 133 sprout clumps were selected randomly in a burnt area of the Zagros forests in Kermanshah province. Some variables were recorded and classified as follows: dbh of the thickest sprouts in 4 classes, number of pre-fire sprouts in 5 classes, fire intensity in 5 classes and the number of post-fire sprouts. This study was conducted under completely randomized design with three replications for each class. Results showed that post-fire resprouting is positively related to the number of pre-fire sprouts and the fire intensity, whereas it is negatively related to the diameter of the thickest sprout. In general, the more pre-fire sprouts and more fire intensity as well as the smaller diameter size of pre-fire sprouts, would cause more post-fire sprouting in manna oak

Alteration in CatSper1 and 2 genes expression, sperm parameters and testis histology in varicocelized rats

Background: CatSper gene, a member of cation channel sperm family, has an essential role in sperm motility and male fertility. Following varicocele, sperm parameters especially sperm movement decreases. For this reason, we hypothesized that CatSper gene expression might be reduced after varicocele induction in an animal model. Objective: The aim of this study was to evaluate the expression of CatSper 1 and 2 genes, sperm parameters and testis histology following varicocele induction. Materials and Methods: A total of 30 Wistar male rats were randomly divided into three following groups (n=10/ each): control, sham, and varicocele group. Experimental varicocele was induced by partial ligation of the left renal vein. The epididymal sperm parameters, CatSper1 and 2 genes expression, and testes histology were studied two months after varicocele induction. Results: Our results revealed that motility (32.73±16.14%), morphology (48.80±17%) and viability (31.23±9.82%) of sperms significantly reduced following varicocele induction. In addition, we showed a significant decrease in the number of spermatogonia (43.63±5.31) and seminiferous tubules diameters (190.51±19.23 mm) in experimental varicocele rats. The level of CatSper1 and 2 genes expression evaluated using real-time polymerase chain reaction was significantly downregulated 2 months after varicocele induction. Conclusion: Our data indicated that experimental varicocele has deleterious effects on sperm parameters, testis structure as well as the expression of CatSper 1 and 2 genes