Information sharing systems and teamwork between sub-teams: a mathematical modeling perspective

Teamwork contributes to a considerable improvement in quality and quantity of the ultimate outcome. Collaboration and alliance between team members bring a substantial progress for any business. However, it is imperative to acquire an appropriate team since many factors must be considered in this regard. Team size may represent the effectiveness of a team and it is of paramount importance to determine what the ideal team size exactly should be. In addition, information technology increasingly plays a differentiating role in productivity and adopting appropriate information sharing systems may contribute to improvement in efficiency especially in competitive markets when there are numerous producers that compete with each other. The significance of transmitting information to individuals is inevitable to assure an improvement in team performance. In this paper, a model of teamwork and its organizational structure are presented. Furthermore, a mathematical model is proposed in order to characterize a group of sub-teams according to two criteria: team size and information technology. The effect of information technology on performance of team and sub-teams as well as optimum size of those team and sub-teams from a productivity perspective are studied. Moreover, a quantitative sensitivity analysis is presented in order to analyze the interaction between these two factors through a sharing system

Azimuthal anisotropy and correlations at large transverse momenta in p+pp+p and Au+Au collisions at sNN\sqrt{s_{_{NN}}}= 200 GeV

Results on high transverse momentum charged particle emission with respect to the reaction plane are presented for Au+Au collisions at $\sqrt{s_{_{NN}}}$= 200 GeV. Two- and four-particle correlations results are presented as well as a comparison of azimuthal correlations in Au+Au collisions to those in $p+p$ at the same energy. Elliptic anisotropy, $v_2$, is found to reach its maximum at $p_t \sim 3$ GeV/c, then decrease slowly and remain significant up to $p_t\approx 7$ -- 10 GeV/c. Stronger suppression is found in the back-to-back high-$p_t$ particle correlations for particles emitted out-of-plane compared to those emitted in-plane. The centrality dependence of $v_2$ at intermediate $p_t$ is compared to simple models based on jet quenching.Comment: 4 figures. Published version as PRL 93, 252301 (2004

Azimuthal anisotropy in Au+Au collisions at sqrtsNN = 200 GeV

The results from the STAR Collaboration on directed flow (v_1), elliptic flow (v_2), and the fourth harmonic (v_4) in the anisotropic azimuthal distribution of particles from Au+Au collisions at sqrtsNN = 200 GeV are summarized and compared with results from other experiments and theoretical models. Results for identified particles are presented and fit with a Blast Wave model. Different anisotropic flow analysis methods are compared and nonflow effects are extracted from the data. For v_2, scaling with the number of constituent quarks and parton coalescence is discussed. For v_4, scaling with v_2^2 and quark coalescence is discussed.Comment: 26 pages. As accepted by Phys. Rev. C. Text rearranged, figures modified, but data the same. However, in Fig. 35 the hydro calculations are corrected in this version. The data tables are available at http://www.star.bnl.gov/central/publications/ by searching for "flow" and then this pape

Inhibition of Mesothelin as a Novel Strategy for Targeting Cancer Cells

Mesothelin, a differentiation antigen present in a series of malignancies such as mesothelioma, ovarian, lung and pancreatic cancer, has been studied as a marker for diagnosis and a target for immunotherapy. We, however, were interested in evaluating the effects of direct targeting of Mesothelin on the viability of cancer cells as the first step towards developing a novel therapeutic strategy. We report here that gene specific silencing for Mesothelin by distinct methods (siRNA and microRNA) decreased viability of cancer cells from different origins such as mesothelioma (H2373), ovarian cancer (Skov3 and Ovcar-5) and pancreatic cancer (Miapaca2 and Panc-1). Additionally, the invasiveness of cancer cells was also significantly decreased upon such treatment. We then investigated pro-oncogenic signaling characteristics of cells upon mesothelin-silencing which revealed a significant decrease in phospho-ERK1 and PI3K/AKT activity. The molecular mechanism of reduced invasiveness was connected to the reduced expression of β-Catenin, an important marker of EMT (epithelial-mesenchymal transition). Ero1, a protein involved in clearing unfolded proteins and a member of the ER-Stress (endoplasmic reticulum-stress) pathway was also markedly reduced. Furthermore, Mesothelin silencing caused a significant increase in fraction of cancer cells in S-phase. In next step, treatment of ovarian cancer cells (OVca429) with a lentivirus expressing anti-mesothelin microRNA resulted in significant loss of viability, invasiveness, and morphological alterations. Therefore, we propose the inhibition of Mesothelin as a potential novel strategy for targeting human malignancies

Genome-scale modeling of the protein secretory machinery in yeast

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery

An examination of the long-term business value of investments in information technology

In this paper, we examine the effects of investments in Information Technology (IT) on the long term business values of organizations. The regression discontinuity design is used in this research to examine eight hundred and ten IT investment announcements collected from the period 1982–2007. Our results found that press releases can affect the market value of a firm by possibly providing investors with a better idea of a firm’s current and future operations and strategy. On the other hand, these press releases also appear to attract more transient investors. The attraction of transient investors likely suggests the market believes the IT investing firm is serious about its potential for growth and expansion

Life Cycle Management of Infrastructures

By definition, life cycle management (LCM) is a framework “of concepts, techniques, and procedures to address environmental, economic, technological, and social aspects of products and organizations in order to achieve continuous ‘sustainable’ improvement from a life cycle perspective” (Hunkeler et al.\ua02001). Thus, LCM theoretically integrates all sustainability dimensions, and strives to provide a holistic perspective. It also assists in the efficient and effective use of constrained natural and financial resources to reduce negative impacts on society (Sonnemann and Leeuw\ua02006; Adibi et al.\ua02015). The LCM of infrastructures is the adaptation of product life cycle management (PLM) as techniques to the design, construction, and management of infrastructures. Infrastructure life cycle management requires accurate and extensive information that might be generated through different kinds of intelligent and connected information workflows, such as building information modeling (BIM)

The role of diet in the aetiopathogenesis of inflammatory bowel disease

Crohn’s disease and ulcerative colitis, collectively known as IBD, are chronic inflammatory disorders of the gastrointestinal tract. Although the aetiopathogenesis of IBD is largely unknown, it is widely thought that diet has a crucial role in the development and progression of IBD. Indeed, epidemiological and genetic association studies have identified a number of promising dietary and genetic risk factors for IBD. These preliminary studies have led to major interest in investigating the complex interaction between diet, host genetics, the gut microbiota and immune function in the pathogenesis of IBD. In this Review, we discuss the recent epidemiological, gene–environment interaction, microbiome and animal studies that have explored the relationship between diet and the risk of IBD. In addition, we highlight the limitations of these prior studies, in part by explaining their contradictory findings, and review future directions

An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data

Citation: Shi, Z. Z., Chapes, S. K., Ben-Arieh, D., & Wu, C. H. (2016). An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data. Plos One, 11(8), 39. doi:10.1371/journal.pone.0161131We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as "sepsis". Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-a ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies