Interaction protocols for human-driven crisis resolution processes

This work aims at providing a crisis cell with process-oriented tools to manage crisis resolutions. Indeed, the crisis cell members have to define the crisis resolution process, adapt it to face crisis evolutions, and guide its execution. Crisis resolution processes are interaction-intensive processes: they not only coordinate the performance of tasks to be undertaken on the impacted world, but they also support regulatory interactions between possibly geographically distributed crisis cell members. In order to deal with such an interweaving, this paper proposes to use Interaction Protocols to both model formal interactions and ease a cooperative adaptation and guidance of crisis resolution processes. After highlighting the benefits of Interaction Protocols to support this human and collective dimension, the paper presents a protocol meta-model for their specification. It then shows how to suitably integrate specified protocols into crisis resolution processes and how to implement this conceptual framework into a service oriented architecture

Anticancer activity of a sub-fraction of dichloromethane extract of Strobilanthes crispus on human breast and prostate cancer cells in vitro

<p>Abstract</p> <p>Background</p> <p>The leaves of <it>Strobilanthes crispus </it>(<it>S. crispus</it>) which is native to the regions of Madagascar to the Malay Archipelago, are used in folk medicine for their antidiabetic, diuretic, anticancer and blood pressure lowering properties. Crude extracts of this plant have been found to be cytotoxic to human cancer cell lines and protective against chemically-induced hepatocarcinogenesis in rats. In this study, the cytotoxicity of various sub-fractions of dichloromethane extract isolated from the leaves of <it>S. crispus </it>was determined and the anticancer activity of one of the bioactive sub-fractions, SC/D-F9, was further analysed in breast and prostate cancer cell lines.</p> <p>Methods</p> <p>The dichloromethane extract of <it>S. crispus </it>was chromatographed on silica gel by flash column chromatography. The ability of the various sub-fractions obtained to induce cell death of MCF-7, MDA-MB-231, PC-3 and DU-145 cell lines was determined using the LDH assay. The dose-response effect and the EC₅₀values of the active sub-fraction, SC/D-F9, were determined. Apoptosis was detected using Annexin V antibody and propidium iodide staining and analysed by fluorescence microscopy and flow cytometry, while caspase 3/7 activity was detected using FLICA caspase inhibitor and analysed by fluorescence microscopy.</p> <p>Results</p> <p>Selected sub-fractions of the dichloromethane extract induced death of MCF-7, MDA-MB-231, PC-3 and DU-145 cells. The sub-fraction SC/D-F9, consistently killed breast and prostate cancer cell lines with low EC₅₀values but is non-cytotoxic to the normal breast epithelial cell line, MCF-10A. SC/D-F9 displayed relatively higher cytotoxicity compared to tamoxifen, paclitaxel, docetaxel and doxorubicin. Cell death induced by SC/D-F9 occurred via apoptosis with the involvement of caspase 3 and/or 7.</p> <p>Conclusions</p> <p>A dichloromethane sub-fraction of <it>S. crispus </it>displayed potent anticancer activities <it>in vitro </it>that can be further exploited for the development of a potential therapeutic anticancer agent.</p

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented

Microplastic in angling baits as a cryptic source of contamination in European freshwaters.

High environmental microplastic pollution, and its largely unquantified impacts on organisms, are driving studies to assess their potential entry pathways into freshwaters. Recreational angling, where many anglers release manufactured baits into freshwater ecosystems, is a widespread activity with important socio-economic implications in Europe. It also represents a potential microplastic pathway into freshwaters that has yet to be quantified. Correspondingly, we analysed three different categories of industrially-produced baits ('groundbait', 'boilies' and 'pellets') for their microplastic contamination (particles 700 µm to 5 mm). From 160 samples, 28 microplastics were identified in groundbait and boilies, with a mean concentration of 17.4 (± 48.1 SD) MP kg-1 and 6.78 (± 29.8 SD) mg kg-1, yet no microplastics within this size range were recorded in the pellets. Microplastic concentrations significantly differed between bait categories and companies, but microplastic characteristics did not vary. There was no correlation between microplastic contamination and the number of bait ingredients, but it was positively correlated with C:N ratio, indicating a higher contamination in baits with higher proportion of plant-based ingredients. We thus reveal that bait microplastics introduced accidentally during manufacturing and/or those originating from contaminated raw ingredients might be transferred into freshwaters. However, further studies are needed to quantify the relative importance of this cryptic source of contamination and how it influences microplastic levels in wild fish

A study on the frequency of iron deficiency and thalassaemia in blood donors at Pusat Darah Negara, Kuala Lumpur

This study was done to identify lood donors with thalassaemia and iron deficiency. A cross sectional study was carried out at Pusat Darah Negara (PDN), Kuala Lumpur in November 2003. Methods: Full blood counts were done on 242 blood donors (166 males and 76 females) Hb analysis and serum ferritin assay were done for all the samples. The first time donors were used as controls. Results: Only 20 (8.3%) donors had MCV Ferritin done for their iron status and if their MCV and MCH are low, Hb analysis for thalassaemia or haemoglobinopathy

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation sympt

The Application of TOPSIS Decision and Random Forests Method in Tone Recognition

The goal of tone recognition is to accurately identify the type and the name of the musical instruments through processing and analyzing the sound signals. In order to reduce the influence of feature confusion on classification process, a method of tone recognition based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Random Forests is proposed. In this process, Mel Frequency Cepstral Coefficients (MFCCs) are acquired, and the quadratic sum of distance between two MFCCs and the entropy of information are computed which are used as indices to analyze and select the MFCCs based the TOPSIS decision. The selected MFCCs are used to classify tone of trumpet-piano, trumpet-cello and piano-cello, and the recognition rates were 100%, 99.9% and 100% respectively. The results are satisfactory and verify feasibility of the developed method

Enhancement of prognostic models for short-term degradation of gas turbines

Deposition and congestion of foulants in the compressor section of gas turbine engines (GTE) degrades the compressor and leads to performance deterioration of the GTE at the system level. Compressor fouling may develop over a short time, but it is recoverable by washing and cleaning. Reliable prediction of the fouling as a function of time is helpful for planning compressor wash services. In this work, the fouling state is parametrized as the relative change of the ratio of the compressor mass flow and efficiency against ideal conditions. A regression-based prognostic model is developed to predict the fouling state as a function of time. In the next step, an adaptive neuro-fuzzy inference system (ANFIS) is developed that considers the rate of humidity condensation at the inlet of the compressor for the prognostic model. The performance of the developed models is evaluated with recorded operating data from a GTE in a power plant. The study shows that enhancement of the prognostic model may be accomplished by taking into account the effects of humidity on the rate of f

Performance-Based Gas Turbine Health Monitoring, Diagnostics, and Prognostics: A Survey

Health monitoring is an essential part of condition-based maintenance and prognostics and health management for gas turbines. Various health monitoring systems have been developed based on the measurement and observation of the fault symptoms including turbine performance parameters such as heat rate, and nonperformance symptoms such as structural vibration. This paper focuses on surveying state-of-the-art condition monitoring, diagnostic and prognostic techniques using performance parameters acquired from gas-path data that are mostly available from the operating systems of gas turbines. Performance parameters and the corresponding effective factors a

Solving the earthquake disaster shelter location-allocation problem using optimization heuristics

Earthquakes can cause significant disruption and devastation to populations of communities. Thus, in the event of an earthquake, it is necessary to have the right number of disaster shelters, with the appropriate capacity, in the right location in order to accommodate local communities. Mathematical models, allied with suitable optimization algorithms, have been used to determine the locations at which to construct disaster shelters and allocate the population to them. This paper compares the use of two optimization algorithms, namely a genetic algorithm and a modified particle swarm optimization, both of which have advantages and disadvantages when solving the disaster shelter location-allocation problem