An Analysis Of Air Pollution And Human Health Effects

Hazardous chemicals escape to the environment by a number of natural and/or anthropogenic activities and may cause adverse effects onhuman health and the environment. Increased combustion of fossil fuels in the last century is responsible for the progressive change in the atmosphericcomposition. Air pollutants, such as carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds(VOCs), ozone (O3), heavy metals, and respirable particulate matter, differ in their chemical composition, reaction properties,emission, time of disintegration and ability to diffuse in long or short distances. Air pollution has both acute and chronic effects on humanhealth, affecting a number of differentsystemsandorgans.Itranges from minor upper respiratory irritation to chronic respiratory and heartdisease, lungcancer,acuterespiratoryinfections in children and chronic bronchitis in adults, aggravating pre-existing heart and lung disease,or asthmatic attacks. In addition, short- and long- term exposures have also been linked with premature mortality and reduced life expectancy. This paper discussed about effects of air pollutants on human health

Cloning, Expression And Characterization Of Ahlinactivating aiiA Gene Homologue In Escherichia coli

Cell-to-cell communication pathway of single-celled microbes is usually coordinated by quorum sensing (QS) system mediated by signal molecules. This cell density-dependent system plays a vital role in functional coordination of most pathogenic bacteria. Laluan komunikasi antara sel-sel mikrob bersel tunggal biasanya diselaraskan oleh penderiaan kuorum yang dikoordinasikan oleh molekul isyarat. Sistem ini bergantung kepada kepadatan sel dan memainkan peranan penting dalam penyelarasan and pengekspresan gen kebanyakan bakteria patogenik

Predicting Property Rating Values Using Geographically Weighted Regression

Currently, the market value for rating valuation applied in Malaysia is the single property valuation technique. This technique is not efficient enough, involving high costs and large labor force because rating involves valuation of large number of properties. Multiple Regression Analysis (MRA) was applied due to these weaknesses. However, the MRA fails to account for the spatial effects (spatial heterogeneity and spatial dependence) inherent in property data. In this study, the Geographically Weighted Regression (GWR) model is introduced as a new method to value rating properties. The GWR model is able to capture spatial heterogeneity by allowing different relationships to occur between variables at different points in space. This study has two objectives. The first objective is to determine the attributes to be used for MRA and GWR model in this study. Data for this study were collected from two local authorities to represent rent and transaction data-based rating. Data for rent was obtained from Majlis Perbandaran Kajang (MPKj) and data for transaction was obtained from Majlis Perbandaran Kulai (MPKu). Final attributes for rent–based rating area are land area, main floor area, ancillary floor area, type of ceiling, property position, property type, age of building, distance to centre business of district and neighborhood quality and the attributes for transacted-based rating area are land area, main floor area, additional floor area and floor finishing. The second objective is to compare the performances of the GWR model with the MRA model in predicting rating values in the study areas. The result of R2, Adjusted R2, F-test and standard error of estimates proved that the GWR model provides better fitness compared to the MRA model. Residual analyses also reveal the same conclusion where residual for the GWR model is smaller in absolute values and probability distribution close to normal. The GWR model has also successfully captured spatial heterogeneity in almost all attributes. The prediction assessment of out-sample observations also revealed that the GWR model is able to produce better prediction. The ability of the GWR model to capture spatial effects is the main reason for this model to perform better; the GWR model is able to solve spatial heterogeneity problem explicitly and spatial dependence problem implicitly. Thus, the GWR which has been proven to be able to produce accurate prediction with small number of attributes should be used for rating valuation in Malaysia

Hotel Room Rate and Availability Parity Across Electronic Distribution Channels

This is an exploratory research paper looking at the parity of hotel room rates and hotel room availability across electronic distribution channels. The fulfillment of the best rate guarantee of hotels was also analyzed. The study surveyed 40 hotels in Singapore, covering 4 hotel segments, luxury, upscale, mid-market and budget with data collected over 5 dates. The results were analyzed across segments and dates of collection and it was found that neither rate nor room availability parity existed across all the hotels surveyed. In addition, majority of the hotels were unable to fulfill the best rate guarantee. Reasons for why the disparities occurred are discussed and include technological incapability, problems with control of distribution channels and relationships between hotel operators and online intermediaries. Solutions for dealing with these challenges are provided and discussed

A Prospective Open Labelled Phase-II Non Randomized Clinical Trial on Jaathipalathi Chooranam for the treatment of Swasakasam (Bronchial Asthma)

Increasing prevalence of the respiratory diseases are reporting both in developed and developing countries. On comparing the symptoms of “Swasakasam” it can be correlated to “Bronchial asthma” in modern science.40 patients (20-out patients and 20-in patients) were selected for the study conducted in GSMC& H, Palayamkottai.Trial medicine Jaathipalathi Chooranam 30 mg/ kg /BW thrice a day, after food along with honey for 30 days was administrated for entire study period. Jaathipalathi Chooranam has the reference from Sarabendhra Vaithiya Muraikal-Kasa Swasa Roga Sikicha, Vasudevasasthri, and Venkadarajan,2006. Trial medicine was subjected to various pre-clinical studies like bio- chemical, phytochemical, pharmacological and microbiological analysis. Safety profile of the trial drug was evaluated and no morbidity and mortality was noted in experimental analysis. The biochemistry analysis showed, the presence of Calcium, Starch, Ferrous iron, Tannic acid Unsaturated compound, Reducing sugar and aminoacid. The alkaloids, Carbohydrates, Glycosides, Phytosterols, Flavonoids, Tannin, Protien and Lignin were observed in Phytochemical analysis. Invivo and Invitro studies are showed the better results in Antihistaminic and Anti anaphylactic, Antiinflammotary and Bronchodilator activity. The trial medicine was found to have high sensitivity in Staphylococcus aureus, Streptococcus mutans, Bacillus subtilis, Klebsiella pneumoniae and E.coli organism. At the end of the study majority of the cases were analysed with fixed clinical criterias and showed good clinical improvement. All the relevant reports were statistically analysed and found to be significant

Audio-Video Detection and Fusion of Broad Casting Information

In the last few decade of multimedia information systems, audio-video data has become an glowing part in many digital computer applications. Audio-video classification has been becoming a focus in the research of audio-video processing and pattern recognition. Automatic audio-video classification is very useful to audio-video indexing, content-based audio-video retrieval and on-line audio-video distribution such as online audio-video shopping, but it is a challenge to extract the most similar and salient themes from huge data of audio-video. In this paper, we propose effective algorithms to automatically segmentation and classify audio-video clips into one of  Six classes: advertisement, cartoon, songs, serial,  movie and news. For these categories a number of acoustic and visual features that include Mel Frequency Cepstral Coefficients, Color Histogram are extracted to characterize the audio and video data. The autoassociative neural network model (AANN) is used to capture the distribution of the acoustic and visual feature vectors. The AANN model captures the distribution of the acoustic and visual features of a class, and the back propagation learning algorithm is used to adjust the weights of the network to minimize the mean square error for each feature vector. Keywords: - Audio and Video detection, Audio and Video fusion, Mel Frequency Cepstral Coefficient, Color Histogram, Autoassociative Neural Network Model(AANN