Abstract: Biochemical investigations were carried out to assess
the effect of different exposure regimes of Kazakhstan crude oil
(KCO) on hepatic antioxidant defense system in albino rats.
Contaminants were delivered under two different dosing regimes,
with all treatments receiving the same total contaminant load by the
end of the exposure period. Rats in regime A injected with KCO
once at a dose of 6 ml/kg bw while in regime B injected multiply at a
dose of 1.5 ml/kg bw on day 1, 3, 5 and 8. Antioxidant biomarkers
were measured in hepatic tissue after 1, 3, 5 and 8 days. Significant
induction was observed in serum aminotransferases (ALT, AST)
(p
Abstract: Food borne illnesses have been reported to be a global
health challenge. Annual incidences of food–related diseases involve
76 million cases, of which only 14 million can be traced to known
pathogens. Poor hygienic practices have contributed greatly to this. It
has been reported that in the year 2000 about 2.1 million people died
from diarrheal diseases, hence, there is a need to ensure food safety at
all level. This study focused on the sterility examination and
inhibitory effect of honey samples on selected gram negative and
gram positive food borne pathogen from South West Nigeria. The
laboratory examinations revealed the presence of some bacterial and
fungal contaminations of honey samples and that inhibitory activity
of the honey sample was more pronounced on the gram negative
bacteria than the gram positive bacterial isolates. Antibiotic
sensitivity test conducted on the different bacterial isolates also
showed that honey was able to inhibit the proliferation of the tested
bacteria than the employed antibiotics.
Abstract: Electrocardiogram (ECG) data compression algorithm
is needed that will reduce the amount of data to be transmitted, stored
and analyzed, but without losing the clinical information content. A
wavelet ECG data codec based on the Set Partitioning In Hierarchical
Trees (SPIHT) compression algorithm is proposed in this paper. The
SPIHT algorithm has achieved notable success in still image coding.
We modified the algorithm for the one-dimensional (1-D) case and
applied it to compression of ECG data.
By this compression method, small percent root mean square
difference (PRD) and high compression ratio with low
implementation complexity are achieved. Experiments on selected
records from the MIT-BIH arrhythmia database revealed that the
proposed codec is significantly more efficient in compression and in
computation than previously proposed ECG compression schemes.
Compression ratios of up to 48:1 for ECG signals lead to acceptable
results for visual inspection.
Abstract: ECG analysis method was developed using ROC
analysis of PVC detecting algorithm. ECG signal of MIT-BIH
arrhythmia database was analyzed by MATLAB. First of all, the
baseline was removed by median filter to preprocess the ECG signal.
R peaks were detected for ECG analysis method, and normal VCG
was extracted for VCG analysis method. Four PVC detecting
algorithm was analyzed by ROC curve, which parameters are
maximum amplitude of QRS complex, width of QRS complex, r-r
interval and geometric mean of VCG. To set cut-off value of
parameters, ROC curve was estimated by true-positive rate
(sensitivity) and false-positive rate. sensitivity and false negative rate
(specificity) of ROC curve calculated, and ECG was analyzed using
cut-off value which was estimated from ROC curve. As a result, PVC
detecting algorithm of VCG geometric mean have high availability,
and PVC could be detected more accurately with amplitude and width
of QRS complex.
Abstract: As part of national epidemiological survey on bovine
viral diarrhea virus (BVDV), a total of 274 dejecta samples were
collected from 14 cattle farms in 8 areas of Xinjiang Uygur
Autonomous Region in northwestern China. Total RNA was extracted
from each sample, and 5--untranslated region (UTR) of BVDV
genome was amplified by using two-step reverse
transcriptase-polymerase chain reaction (RT-PCR). The PCR products
were subsequently sequenced to study the genetic variations of BVDV
in these areas. Among the 274 samples, 33 samples were found
virus-positive. According to sequence analysis of the PCR products,
the 33 samples could be arranged into 16 groups. All the sequences,
however, were highly conserved with BVDV Osloss strains. The virus
possessed theses sequences belonged to BVDV-1b subtype by
phylogenetic analysis. Based on these data, we established a typing
tree for BVDV in these areas. Our results suggested that BVDV-1b
was a predominant subgenotype in northwestern China and no
correlation between the genetic and geographical distances could be
observed above the farm level.
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.
Abstract: The analysis to detect arrhythmias and life-threatening
conditions are highly essential in today world and this analysis
can be accomplished by advanced non-linear processing methods
for accurate analysis of the complex signals of heartbeat dynamics.
In this perspective, recent developments in the field of multiscale
information content have lead to the Microcanonical Multiscale
Formalism (MMF). We show that such framework provides several
signal analysis techniques that are especially adapted to the
study of heartbeat dynamics. In this paper, we just show first hand
results of whether the considered heartbeat dynamics signals have
the multiscale properties by computing local preticability exponents
(LPEs) and the Unpredictable Points Manifold (UPM), and thereby
computing the singularity spectrum.
Abstract: This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
Abstract: Health problems linked to urban growth are current
major concerns of developing countries. In 2002 and 2005, an
interdisciplinary program “Populations et Espaces ├á Risques
SANitaires" (PERSAN) was set up under the patronage of the
Development and Research Institute. Centered on health in
Cameroon-s urban environment, the program mainly sought to (i)
identify diarrhoea risk factors in Yaoundé, (ii) to measure their
prevalence and apprehend their spatial distribution. The crosssectional
epidemiological study that was carried out revealed a
diarrheic prevalence of 14.4% (437 cases of diarrhoea on the 3,034
children examined). Also, among risk factors studied, household
refuse management methods used by city dwellers were statistically
associated to these diarrhoeas. Moreover, it happened that levels of
diarrhoeal attacks varied consistently from one neighbourhood to
another because of the discrepancy urbanization process of the
Yaoundé metropolis.
Abstract: Potassium monopersulfate has been decomposed in
aqueous solution in the presence of Co(II). The effect of the main
operating variables has been assessed. Minimum variations in pH
exert a considerable influence on the process kinetics. Thus, when no
pH adjustment is considered, the actual effect of variables like initial
monopersulfate and/or catalyst concentration may be hindered. As
expected, temperature enhances the monopersulfate decomposition
rate by following the Arrhenius law. The activation energy in the
proximity of 85 kJ/mol has been obtained. Amongst the different
solids tested in the monopersulfate decomposition, only the
perovskite LaTi0.15Cu0.85O3 has shown a significant catalytic activity.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. Exclusive breastfeeding during the first 6 months of life is of fundamental importance because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in developed countries, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we study the factors that influence exclusive breastfeeding and use the Generalized Poisson regression model to analyze the practices of exclusive breastfeeding in Mauritius. We develop two sets of quasi-likelihood equations (QLE)to estimate the parameters.
Abstract: Electrocardiogram (ECG) is considered to be the
backbone of cardiology. ECG is composed of P, QRS & T waves and
information related to cardiac diseases can be extracted from the
intervals and amplitudes of these waves. The first step in extracting
ECG features starts from the accurate detection of R peaks in the
QRS complex. We have developed a robust R wave detector using
wavelets. The wavelets used for detection are Daubechies and
Symmetric. The method does not require any preprocessing therefore,
only needs the ECG correct recordings while implementing the
detection. The database has been collected from MIT-BIH arrhythmia
database and the signals from Lead-II have been analyzed. MatLab
7.0 has been used to develop the algorithm. The ECG signal under
test has been decomposed to the required level using the selected
wavelet and the selection of detail coefficient d4 has been done based
on energy, frequency and cross-correlation analysis of decomposition
structure of ECG signal. The robustness of the method is apparent
from the obtained results.