PAN AIR: A computer program for predicting subsonic or supersonic linear potential flows about arbitrary configurations using a higher order panel method. Volume 2: User's manual (version 3.0)

A comprehensive description of user problem definition for the PAN AIR (Panel Aerodynamics) system is given. PAN AIR solves the 3-D linear integral equations of subsonic and supersonic flow. Influence coefficient methods are used which employ source and doublet panels as boundary surfaces. Both analysis and design boundary conditions can be used. This User's Manual describes the information needed to use the PAN AIR system. The structure and organization of PAN AIR are described, including the job control and module execution control languages for execution of the program system. The engineering input data are described, including the mathematical and physical modeling requirements. Version 3.0 strictly applies only to PAN AIR version 3.0. The major revisions include: (1) inputs and guidelines for the new FDP module (which calculates streamlines and offbody points); (2) nine new class 1 and class 2 boundary conditions to cover commonly used modeling practices, in particular the vorticity matching Kutta condition; (3) use of the CRAY solid state Storage Device (SSD); and (4) incorporation of errata and typo's together with additional explanation and guidelines

PAN AIR: A computer program for predicting subsonic or supersonic linear potential flows about arbitrary configurations using a higher order panel method. Volume 4: Maintenance document (version 3.0)

The Maintenance Document Version 3.0 is a guide to the PAN AIR software system, a system which computes the subsonic or supersonic linear potential flow about a body of nearly arbitrary shape, using a higher order panel method. The document describes the overall system and each program module of the system. Sufficient detail is given for program maintenance, updating, and modification. It is assumed that the reader is familiar with programming and CRAY computer systems. The PAN AIR system was written in FORTRAN 4 language except for a few CAL language subroutines which exist in the PAN AIR library. Structured programming techniques were used to provide code documentation and maintainability. The operating systems accommodated are COS 1.11, COS 1.12, COS 1.13, and COS 1.14 on the CRAY 1S, 1M, and X-MP computing systems. The system is comprised of a data base management system, a program library, an execution control module, and nine separate FORTRAN technical modules. Each module calculates part of the posed PAN AIR problem. The data base manager is used to communicate between modules and within modules. The technical modules must be run in a prescribed fashion for each PAN AIR problem. In order to ease the problem of supplying the many JCL cards required to execute the modules, a set of CRAY procedures (PAPROCS) was created to automatically supply most of the JCL cards. Most of this document has not changed for Version 3.0. It now, however, strictly applies only to PAN AIR version 3.0. The major changes are: (1) additional sections covering the new FDP module (which calculates streamlines and offbody points); (2) a complete rewrite of the section on the MAG module; and (3) strict applicability to CRAY computing systems

Vapor of Volatile Oils from <em>Litsea cubeba</em> Seed Induces Apoptosis and Causes Cell Cycle Arrest in Lung Cancer Cells

<div><p>Non-small cell lung carcinoma (NSCLC) is a major killer in cancer related human death. Its therapeutic intervention requires superior efficient molecule(s) as it often becomes resistant to present chemotherapy options. Here we report that vapor of volatile oil compounds obtained from <em>Litsea cubeba</em> seeds killed human NSCLC cells, A549, through the induction of apoptosis and cell cycle arrest. Vapor generated from the combined oils (VCO) deactivated Akt, a key player in cancer cell survival and proliferation. Interestingly VCO dephosphorylated Akt at both Ser⁴⁷³ and Thr³⁰⁸; through the suppression of mTOR and pPDK1 respectively. As a consequence of this, diminished phosphorylation of Bad occurred along with the decreased Bcl-xL expression. This subsequently enhanced Bax levels permitting the release of mitochondrial cytochrome c into the cytosol which concomitantly activated caspase 9 and caspase 3 resulting apoptotic cell death. Impairment of Akt activation by VCO also deactivated Mdm2 that effected overexpression of p53 which in turn upregulated p21 expression. This causes enhanced p21 binding to cyclin D1 that halted G1 to S phase progression. Taken together, VCO produces two prong effects on lung cancer cells, it induces apoptosis and blocked cancer cell proliferation, both occurred due to the deactivation of Akt. In addition, it has another crucial advantage: VCO could be directly delivered to lung cancer tissue through inhalation.</p> </div

VCO induces apoptosis in A549 lung cancer cells.

<p>(<b>A</b>) Annexin-Cy3 (red) and 6-CFDA (green) double staining of apoptotic cells was examined by fluorescence microscopy where VCO treated A549 cells showed both green and red stains and control (untreated) cells stained green only. (<b>B</b>) Percentage of apoptotic A549 cells was measured at different time points (0 h, 12 h, 24 h, 36 h) with VCO treatments. (<b>C</b>) Mitochondrial membrane potential was observed in control and VCO exposed (36 h) A549 lung cancer cells by JC-1 staining assay. (<b>D</b>) Apoptotic DNA fragmentation was observed by VCO treated A-549 cells on 1.5% agarose gel electrophoresis. Data are presented as means ± SEM of three independent experiments. *p<0.05, **p<0.01 versus control (0 h). Bar represents 20 µm.</p

Time dependent inhibition of Akt phosphorylation by VCO.

<p>(<b>A</b>, <b>B</b>) Immunoblot analysis of Akt phosphorylation at Thr³⁰⁸ (A) and Ser⁴⁷³ (B) in A549 treated cells with VCO for the indicated time period (upper panel). Fold change represents the protein level of the VCO treated cells relative to the control cells. Bands were quantified by densitometric analysis where pAkt level was then normalized to the total Akt level (lower panel). β-actin served as loading control. (<b>C</b>, <b>D</b>) Immunoblot analysis of pPDK1 Ser ²⁴¹ (C) and mTOR (D) was done at different time hour (0 h, 12 h, 24 h, 36 h) exposure of VCO to A549 cells (upper panel). Bands were quantified by densitometric analysis where pPDK1 or mTOR level was then normalized with β-actin which is represented by folds change (lower panel). Figures are representative of three independent experiments, *p<0.01, **p<0.001 versus control (0 h).</p

Effect of VCO on the viability of A549 cells by MTT assay.

<p>(<b>A</b>) Cell viability of A549 lung cancer cells were measured when exposed to vapors of different dilutions (10⁶ to 10²) of crude oil for 72 h by using MTT assay and the data was expressed as % of cell survivability relative to control. (<b>B</b>) Chemical structures of four most available compounds (C1- Citronellal; C2- neo-isopulegol; C3- isopulegol; C4- citronellol) isolated from <i>Litsea cubeba</i> seed essential oil. (<b>C</b>) Percentage of cell death was observed when A549 cells were exposed individually with these compounds for 72 h. (<b>D</b>) Effect of VCO (C2∶C3∶C4 as 1∶1∶1) and C4 on cell death at 72 h was observed by MTT assay, which was visualized by microscopic images. (<b>E</b>) Cell survivability was measured at different time intervals (24, 48, 72 h) with VCO exposure on A549 cells. (<b>F</b>) Western blot of Akt phosphorylation at Thr³⁰⁸, Ser⁴⁷³ and total Akt in A549 cells treated without (Con) with C1, C2, C3, C4 and VCO for 36 hours. β-actin served as internal loading control. Values are means ± SEM of 3 individual experiments. *p<0.05, **p<0.01 versus control and #p<0.05 versus C4.</p

Deactivation of Bad with altered Bcl-xL/Bax ratio on mitochondrial membrane by VCO exposure.

<p>(<b>A</b>) Immunoblot analysis was performed to evaluate the level of pBad Ser¹³⁶ and Bad in A549 cells exposed with VCO for different time periods (0 h, 12 h, 24 h, 36 h). β-actin served as internal control. Bands were quantified by densitometric analysis where pBad level was compared with Bad level. (<b>B</b>) Protein level of Bcl-xL and Bax of these cells were also evaluated by immunoblot analysis. Densitometric analysis showed Bcl-xL was negatively correlated with Bax level when A549 cells were exposed with VCO. Values are means ± SEM of three independent experiments, *p<0.05, **p<0.01 versus control (0 h).</p

VCO induces apoptotic cell death by activating caspase cascade.

<p>(<b>A</b>) A549 cells were exposed with VCO for 36 h followed by staining of mitochondria with Mitotracker (red) and cytochrome c with FITC conjugated anti-cytochrome c antibody (green). (<b>B</b>) Immunoblot analysis was done by using anti-cleaved caspase-9 or caspase-3 antibodies in A-549 cells incubated in the presence of VCO at 0 h, 24 h, 36 h time intervals. β-actin used as internal control. (<b>C</b>) A549 cells were exposed with VCO for indicated time periods and on termination of exposure, cells were lysed and caspase 3 activity was measured in DTX multimode detector by using proluminescent caspase 3 as the substrate. (<b>D</b>) PARP cleavage was observed in VCO exposed cells by immunoblot analysis using anti-PARP antibody. β-actin used as loading control. Values are means ± SEM of three independent experiments, *p<0.01, **p<0.001 versus control (0 h). Bar represents 20 µm.</p

Assessing the long-term performance of cross-sectoral strategies for national infrastructure

National infrastructure systems (energy, transport, digital communications, water, and waste) provide essential services to society. Although for the most part these systems developed in a piecemeal way, they are now an integrated and highly interdependent “system of systems.” However, understanding the long-term performance trajectory of national infrastructure has proved to be very difficult because of the complexity of these systems (in physical and institutional terms) and because there is little tradition of thinking cross-sectorally about infrastructure system performance. Here, a methodology is proposed for analyzing national multisectoral infrastructure systems performance in the context of uncertain futures, incorporating interdependencies in demand across sectors. Three contrasting strategies are considered for infrastructure provision (capacity intensive, capacity constrained, and decentralized) and multiattribute performance metrics are analyzed in the context of low, medium, and high demographic and economic growth scenarios. The approach is illustrated using Great Britain and provides the basis for the development and testing of long-term strategies for national infrastructure provision. It is especially applicable to mature industrial economics with a large stock of existing infrastructure and challenges of future infrastructure provision