Development of Android Based Real Time Monitoring System for Fire-fighters

Fire-fighters are trained rescuers especially in extinguishing hazardous fires and saving lives from dangerous situations however they tend to put their lives at risk while on the job. Statistic shows the number of deaths of fire-fighters while on the job are still high up to this year and a higher percentage of rapid fire progress and exertion are dedicated to the cause of death of fire-fighters while on the job. Therefore, a real-time monitoring on the physiological state for fire-fighters is something crucial to be done. However, the Fire and Rescue Department of Malaysia practices the traditional communication method which is by communicating via walkie-talkie. The practice of real-time assessment should be carried out by Fire and Rescue Department of Malaysia in order to avoid having a fire-fighter’s live at risk. This could be achieved by using the ARMOR (Android Based Real Time Monitoring System) whereby it can transmit voice data and physiological data such as heart rate, respirator rate, peak acceleration and posture. Based on the research and critical analysis, an android platform have been found to be a suitable selection as it supports Bluetooth Wi-Fi and Radio Frequency, accessible from any android devices and it is user friendly. As a result, a real-time intelligent monitoring system was successfully developed on an android platform. The physiological data for heart rate, respiration rate, posture, and peak acceleration was successfully transmitted and monitored on an android device at real-time

Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network

The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August 2012 to August 2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–20 3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea

Development of Android Based Real Time Monitoring System for Fire-fighters

Fire-fighters are trained rescuers especially in extinguishing hazardous fires and saving lives from dangerous situations however they tend to put their lives at risk while on the job. Statistic shows the number of deaths of fire-fighters while on the job are still high up to this year and a higher percentage of rapid fire progress and exertion are dedicated to the cause of death of fire-fighters while on the job. Therefore, a real-time monitoring on the physiological state for fire-fighters is something crucial to be done. However, the Fire and Rescue Department of Malaysia practices the traditional communication method which is by communicating via walkie-talkie. The practice of real-time assessment should be carried out by Fire and Rescue Department of Malaysia in order to avoid having a fire-fighter’s live at risk. This could be achieved by using the ARMOR (Android Based Real Time Monitoring System) whereby it can transmit voice data and physiological data such as heart rate, respirator rate, peak acceleration and posture. Based on the research and critical analysis, an android platform have been found to be a suitable selection as it supports Bluetooth Wi-Fi and Radio Frequency, accessible from any android devices and it is user friendly. As a result, a real-time intelligent monitoring system was successfully developed on an android platform. The physiological data for heart rate, respiration rate, posture, and peak acceleration was successfully transmitted and monitored on an android device at real-time

Metabolome Searcher: A High Throughput Tool for Metabolite Identification and Metabolic Pathway Mapping Directly from Mass Spectrometry and Using Genome Restriction

Background Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism’s genome as a database restricts metabolite identification to only those compounds that the organism can produce. Results To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment’s MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis. Conclusions Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome

Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

Background Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease. Methods Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology. Results Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years). Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied

Pipe network model for scaling of dynamic interfaces in porous media

We present a numerical study on the dynamics of imbibition fronts in porous media using a pipe network model. This model quantitatively reproduces the anomalous scaling behavior found in imbibition experiments [Phys. Rev. E {\bf 52}, 5166 (1995)]. Using simple scaling arguments, we derive a new identity among the scaling exponents in agreement with the experimental results.Comment: 13 pages, 3 figures, REVTeX, to appear in Phys. Rev. Let

Anomalous thermoelectric power of Mg1-xAlxB2 system with x = 0.0 to 1.0

Thermoelectric power, S(T) of the Mg1-xAlxB2 system has been measured for x = 0.0, 0.1, 0.2, 0.4, 0.6, 0.8 and 1.0. XRD, resistivity and magnetization measurements are also presented. It has been found that the thermoelectric power is positive for x = 0.4 and is negative for x = 0.6 over the entire temperature range studied up to 300 K. The thermoelectric power of x = 0.4 samples vanishes discontinuously below a certain temperature, implying existence of superconductivity. In general, the magnitude of the thermoelectric power increases with temperature up to a certain temperature, and then it starts to decrease towards zero base line. In order to explain the observed behavior of the thermoelectric power, we have used a model in which both diffusion and phonon drag processes are combined by using a phenomenological interpolation between the low and high temperature behaviors of the thermoelectric power. The considered model provides an excellent fit to the observed data. It is further found that Al doping enhances the Debye temperature.Comment: 19 pages Text + Figs. suggestions/comments([email protected]