Nonlinear wave transmission and pressure on the fixed truncated breakwater using NURBS numerical wave tank

Fully nonlinear wave interaction with a fixed breakwater is investigated in a numerical wave tank (NWT). The potential theory and high-order boundary element method are used to solve the boundary value problem. Time domain simulation by a mixed Eulerian-Lagrangian (MEL) formulation and high-order boundary integral method based on non uniform rational B-spline (NURBS) formulation is employed to solve the equations. At each time step, Laplace equation is solved in Eulerian frame and fully non-linear free-surface conditions are updated in Lagrangian manner through material node approach and fourth order Runge-Kutta time integration scheme. Incident wave is fed by specifying the normal flux of appropriate wave potential on the fixed inflow boundary. To ensure the open water condition and to reduce the reflected wave energy into the computational domain, two damping zones are provided on both ends of the numerical wave tank. The convergence and stability of the presented numerical procedure are examined and compared with the analytical solutions. Wave reflection and transmission of nonlinear waves with different steepness are investigated. Also, the calculation of wave load on the breakwater is evaluated by first and second order time derivatives of the potential

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

β-Adrenergic-stimulated macrophages: Comprehensive localization in the M1-M2 spectrum

β-Adrenergic signaling can regulate macrophage involvement in several diseases and often produces anti-inflammatory properties in macrophages, which are similar to M2 properties in a dichotomous M1 vs. M2 macrophage taxonomy. However, it is not clear that β-adrenergic-stimulated macrophages may be classified strictly as M2. In this in vitro study, we utilized recently published criteria and transcriptome-wide bioinformatics methods to map the relative polarity of murine β-adrenergic-stimulated macrophages within a wider M1-M2 spectrum. Results show that β-adrenergic-stimulated macrophages did not fit entirely into any one pre-defined category of the M1-M2 spectrum but did express genes that are representative of some M2 side categories. Moreover, transcript origin analysis of genome-wide transcriptional profiles located β-adrenergic-stimulated macrophages firmly on the M2 side of the M1-M2 spectrum and found active suppression of M1 side gene transcripts. The signal transduction pathways involved were mapped through blocking experiments and bioinformatics analysis of transcription factor binding motifs. M2-promoting effects were mediated specifically through β2-adrenergic receptors and were associated with CREB, C/EBPβ, and ATF transcription factor pathways but not with established M1-M2 STAT pathways. Thus, β-adrenergic-signaling induces a macrophage transcriptome that locates on the M2 side of the M1-M2 spectrum but likely accomplishes this effect through a signaling pathway that is atypical for M2-spectrum macrophages

Factors affecting the adoption of electronic marketplaces: A fuzzy AHP analysis

[[abstract]]Purpose – To present a three-layer hierarchical structure of the factors involved in adopting an electronic marketplace (EM) model and to examine the relative weightings given to various strategic factors by the securities industry (SI) and the heavy electric machinery industry in Taiwan. Design/methodology/approach – A literature review and a review of nine Taiwanese industries allow the formulation of a three-layer hierarchical structure of adoption factors. A fuzzy analytic hierarchical process (AHP) is then undertaken to ascertain the relative weightings of factors that affect entry to an EM in two of these industries which are studied in more detail. Findings – The weights of “proactive” factors are found to be greater than those of “defensive” factors. For example, contrary to previous findings in this area, the “risk of adopting new technology” is not found to be the major factor influencing decision making. Various factors are found to have different routes of influence in determining decision making in different industries. Practical implications – Enterprises that appreciate the weightings of factors to be considered will be able to facilitate the adoption of an EM model with lower costs and greater efficiency. Originality/value – The study provides novel and reliable information about strategic factors that are involved in corporate decisions about entering an EM

β-Adrenergic-stimulated macrophages: Comprehensive localization in the M1-M2 spectrum

β-adrenergic signaling can regulate macrophage involvement in several diseases and often produces anti-inflammatory properties in macrophages, which are similar to M2 properties in a dichotomous M1 vs. M2 macrophage taxonomy. However, it is not clear that β-adrenergic-stimulated macrophages may be classified strictly as M2. In this in vitro study, we utilized recently published criteria and transcriptome-wide bioinformatics methods to map the relative polarity of murine β-adrenergic-stimulated macrophages within a wider M1–M2 spectrum. Results show that β-adrenergic-stimulated macrophages did not fit entirely into any one predefined category of the M1–M2 spectrum but did express genes that are representative of some M2 side categories. Moreover, transcript origin analysis of genome-wide transcriptional profiles located β-adrenergic-stimulated macrophages firmly on the M2 side of the M1–M2 spectrum and found active suppression of M1 side gene transcripts. The signal transduction pathways involved were mapped through blocking experiments and bioinformatics analysis of transcription factor binding motifs. M2-promoting effects were mediated specifically through β(2)-adrenergic receptors and were associated with CREB, C/EBPβ, and ATF transcription factor pathways but not with established M1–M2 STAT pathways. Thus, β-adrenergic-signaling induces a macrophage transcriptome that locates on the M2 side of the M1–M2 spectrum but likely accomplishes this effect through a signaling pathway that is atypical for M2-spectrum macrophages