Abstract: To identify an endothelial cell-specific promoter suitable for vascular-specific targeting, we tested five promoters in vitro--Tie2SE, Tie2LE, ICAM2, Flt-1 and vWF--for promoter activity and specificity in endothelial cells, smooth muscle cells and non-vascular resident cells as well as tissues. These promoters, except for vWF, exhibited good endothelial activity and specificity in vitro. In a syngenic heart transplantation model, the ICAM2 promoter was variably functional in coronary endothelial cells of donor hearts. Thus, the ICAM2, Flt-1, Tie2SE and Tie2LE promoters hold promise for endothelial-specific targeting, but in vitro expression may not predict in vivo expression.
Abstract: This research was carried out to determine the
possible effects of low electromagnetic field (EMF) exposure to the
developing mice fetuses. Pregnant mice were exposed to EMF
exposure at 0mT (sham) and 1.2 mT for six hours per session, carried
out on gestation day 3, 6, 9, 12 and 15. Samples from the stillborn
offspring were observed for morphological defects. The heart didn-t
show progressive cellular damage, the lungs were congested and
emphysemics. The bones were in advance stage of hypertrophy.
Spectrums of morphological defects were observed over 70% of the
surviving offspring. These results indicate that even at lower
exposure to low EMF, is enough to induce morphological defects in
prenatal mice.
Abstract: Ventricular fibrillation is a very important health
problem as is the cause of most of the sudden deaths in the world.
Waves of electrical activity are sent by the SA node, propagate
through the cardiac tissue and activate the mechanisms of cell
contraction, and therefore are responsible to pump blood to the body
harmonically. A spiral wave is an abnormal auto sustainable wave
that is responsible of certain types of arrhythmias. When these waves
break up, give rise to the fibrillation regime, in which there is a
complete loss in the coordination of the contraction of the heart
muscle. Interaction of spiral waves and obstacles is also of great
importance as it is believed that the attachment of a spiral wave to an
obstacle can provide with a transition of two different arrhythmias.
An obstacle can be partially excitable or non excitable. In this talk,
we present a numerical study of the interaction of meandering spiral
waves with partially and non excitable obstacles and focus on the
problem where the obstacle plays a fundamental role in the switch
between different spiral regimes, which represent different
arrhythmic regimes. Particularly, we study the phenomenon of
destabilization of spiral waves due to the presence of obstacles, a
phenomenon not completely understood (This work will appear as a
Chapter in a Book named Cardiac Arrhytmias by INTECH under the
name "Spiral Waves, Obstacles and Cardiac Arrhythmias", ISBN
979-953-307-050-5.).
Abstract: Leonotisleonurus a shrub indigenous to Southern
Africa is widely used in traditional medicine to treat a variety of
conditions ranging from skin diseases and cough to epileptic fits and
‘heart problems’. Studies on the aqueous extract of the leaves have
indicated cycloxegenase enzyme inhibitory activity and an
antihypertensive effect.
Five methanol leaf extract fractions (MLEa - MLEe) of L.
leonurus were tested on anaesthetized normotensive male Wistar rats
(AWR) and isolated perfused working rat hearts (IWH). Fraction
MLEc (0.01mg/kg – 0.05mg/kg) induced significant increases in BP
and HR in AWR and positive chronotropic and inotropic effects in
IWH (1.0mg/ml – 5.0mg/ml). Pre-administration of atenolol
(2.0mg/kg) and prazosin (60μg/kg) significantly inhibited MLEc
effect on HR and MAP respectively in vivo, while atenolol
(7.0mg/ml) pre-perfusion significantly inhibited MLEc effect in vitro.
The hypertensive effect of MLEc is probably via β1agonism.
Results also indicate the presence of multiple cardioactive
compounds in L. leonurus.
Abstract: Proximate (moisture, protein, total fat, total ash) and mineral (K, P, Na, Mg, Ca, Zn, Fe, Cu and Mn) composition of chicken giblets (heart, liver and gizzard) were investigated. Phosphorous content, as well as proximate composition, were determined according to recommended ISO methods. The content of all elements, except phosphorus, of the giblets tissues were determined using inductively coupled plasma-optical emission spectrometry (ICP-OES), after dry ashing mineralization. Regarding proximate composition heart was the highest in total fat content, and the lowest in protein content. Liver was the highest in protein and total ash content, while gizzard was the highest in moisture and the lowest in total fat content. Regarding mineral composition liver was the highest for K, P, Ca, Mg, Fe, Zn, Cu, and Mn, while heart was the highest for Na content. The contents of almost all investigated minerals in analysed giblets tissues of chickens from Vojvodina were similar to values reported in the literature, i.e. in national food composition databases of other countries.
Abstract: An experiment was conducted with 80 unsexed
broilers of the Arbor Acress strain to determine the capability of a
carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado,
orange, melon and Dutch egg plant) in the same proportion for
replacing corn in broiler diet. This study involved a completely
randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of
juice wastes mixture in diets) and 4 replicates per treatment. Diets
were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg
diet). Measured variables were feed consumption, average daily
gain, feed conversion, as well as percentages of abdominal fat pad,
carcass, digestive organs (liver, pancreas and gizzard), and heart.
Data were analyzed by analysis of variance for CRD. Increasing
juice wastes mixture levels in diets increased feed consumption
(P
Abstract: Compensating physiological motion in the context
of minimally invasive cardiac surgery has become an attractive
issue since it outperforms traditional cardiac procedures offering
remarkable benefits. Owing to space restrictions, computer vision
techniques have proven to be the most practical and suitable solution.
However, the lack of robustness and efficiency of existing methods
make physiological motion compensation an open and challenging
problem. This work focusses on increasing robustness and efficiency
via exploration of the classes of 1−and 2−regularized optimization,
emphasizing the use of explicit regularization. Both approaches are
based on natural features of the heart using intensity information.
Results pointed out the 1−regularized optimization class as the best
since it offered the shortest computational cost, the smallest average
error and it proved to work even under complex deformations.
Abstract: Recent advancements in sensor technologies and
Wireless Body Area Networks (WBANs) have led to the
development of cost-effective healthcare devices which can be used
to monitor and analyse a person-s physiological parameters from
remote locations. These advancements provides a unique opportunity
to overcome current healthcare challenges of low quality service
provisioning, lack of easy accessibility to service varieties, high costs
of services and increasing population of the elderly experienced
globally. This paper reports on a prototype implementation of an
architecture that seamlessly integrates Wireless Body Area Network
(WBAN) with Web services (WS) to proactively collect
physiological data of remote patients to recommend diagnostic
services. Technologies based upon WBAN and WS can provide
ubiquitous accessibility to a variety of services by allowing
distributed healthcare resources to be massively reused to provide
cost-effective services without individuals physically moving to the
locations of those resources. In addition, these technologies can
reduce costs of healthcare services by allowing individuals to access
services to support their healthcare. The prototype uses WBAN body
sensors implemented on arduino fio platforms to be worn by the
patient and an android smart phone as a personal server. The
physiological data are collected and uploaded through GPRS/internet
to the Medical Health Server (MHS) to be analysed. The prototype
monitors the activities, location and physiological parameters such as
SpO2 and Heart Rate of the elderly and patients in rehabilitation.
Medical practitioners would have real time access to the uploaded
information through a web application.
Abstract: This paper discusses the designing of knowledge
integration of clinical information extracted from distributed medical
ontologies in order to ameliorate a machine learning-based multilabel
coding assignment system. The proposed approach is
implemented using a decision tree technique of the machine learning
on the university hospital data for patients with Coronary Heart
Disease (CHD). The preliminary results obtained show a satisfactory
finding that the use of medical ontologies improves the overall
system performance.
Abstract: Chronic diseases prevailed along with economic
growth as well as life style changed in recent years in Taiwan.
According to the governmental statistics, hypertension related disease
is the tenth of death causes with 1,816 died directly from hypertension
in 2010. There were more death causes amongst the top ten had been
proofed that having strong association with the hypertension, such as
heart diseases, cardiovascular diseases, and diabetes. Hypertension or
High blood pressure is one of the major indicators for chronic diseases,
and was generally perceived as the major causes of mortality. The
literature generally suggested that regular physical exercise was
helpful to prevent the occurrence or to ease the progress of a
hypertension. This paper reported the process and outcomes in
detailed of an improvement project of physical exercise intervention
specific for hypertension patients. Physical information were
measured before and after the project to obtain information such as
weight, waistline, cholesterol (HD & LD), blood examination, as well
as self-perceived health status. The intervention project involved a
six-week exercise program, of which contained three times a week, 30
minutes of tutored physical exercise intervention. The project had
achieved several gains in changing the subjects- behavior in terms of
many important biophysical indexes. Around 20% of the participants
had significantly improved their cholesterols, BMI, and changed
unhealthy behaviors. Results from the project were encouraging, and
would be good reference for other samples.
Abstract: The study will search the level of existence of the
sweethearting in Saudi Arabia's Supermarkets in Riyadh.
Sweethearting occurs when frontline workers give unauthorized free
or uncounted goods and services to customer-s conspirators. The
store managers and /or security managers were asked about the
sweethearting that occurs in the supermarkets. The characteristics of
sweethearting in Riyadh stores were investigated. Two independent
variables were related to the report of sweethearting. These
independent variables are: The effect of store environment on
sweethearting and the security techniques and loss prevention
electronics techniques used. This study expected to shed the light
about the level of sweethearting in Saudi Arabia and the factors
behind it. This study will serve as an exploratory study for such
phenomenon in Saudi Arabia as well as both descriptive for the
characteristics of sweethearting and explanatory study to link
between the environmental and security systems factors to
sweethearting.
Abstract: The linear methods of heart rate variability analysis
such as non-parametric (e.g. fast Fourier transform analysis) and
parametric methods (e.g. autoregressive modeling) has become an
established non-invasive tool for marking the cardiac health, but their
sensitivity and specificity were found to be lower than expected with
positive predictive value
Abstract: Work Breakdown Structure (WBS) is one of the
most vital planning processes of the project management since it
is considered to be the fundamental of other processes like
scheduling, controlling, assigning responsibilities, etc. In fact
WBS or activity list is the heart of a project and omission of a
simple task can lead to an irrecoverable result. There are some
tools in order to generate a project WBS. One of the most
powerful tools is mind mapping which is the basis of this article.
Mind map is a method for thinking together and helps a project
manager to stimulate the mind of project team members to
generate project WBS. Here we try to generate a WBS of a
sample project involving with the building construction using the
aid of mind map and the artificial intelligence (AI) programming
language. Since mind map structure can not represent data in a
computerized way, we convert it to a semantic network which can
be used by the computer and then extract the final WBS from the
semantic network by the prolog programming language. This
method will result a comprehensive WBS and decrease the
probability of omitting project tasks.
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: Many recent electrophysiological studies have
revealed the importance of investigating meditation state in order to
achieve an increased understanding of autonomous control of
cardiovascular functions. In this paper, we characterize heart rate
variability (HRV) time series acquired during meditation using
nonlinear dynamical parameters. We have computed minimum
embedding dimension (MED), correlation dimension (CD), largest
Lyapunov exponent (LLE), and nonlinearity scores (NLS) from HRV
time series of eight Chi and four Kundalini meditation practitioners.
The pre-meditation state has been used as a baseline (control) state to
compare the estimated parameters. The chaotic nature of HRV during
both pre-meditation and meditation is confirmed by MED. The
meditation state showed a significant decrease in the value of CD and
increase in the value of LLE of HRV, in comparison with premeditation
state, indicating a less complex and less predictable nature
of HRV. In addition, it was shown that the HRV of meditation state
is having highest NLS than pre-meditation state. The study indicated
highly nonlinear dynamic nature of cardiac states as revealed by
HRV during meditation state, rather considering it as a quiescent
state.
Abstract: Nuts are part of a healthy diet such as Mediterranean diet. Benefits of nuts in reducing the risk of heart disease has been reasonably attributed to their composition of vitamins, minerals, unsaturated fatty acids, fiber and phytochemicals such as polyphenols, tocopherols, squalene and phytosterols. More than 75% of total fatty acids of nuts are unsaturated. α- tocopherol is the main tocopherol isomer present in most of the nuts. While walnuts, Brazil nut, cashew nut, peanut, pecan and pistachio nuts are rich in γ- tocopherol. β- sitosterol is dominant sterol in nuts. Pistachio and pine nut have the highest total phytosterol and Brazil nut and English walnut the lowest. Walnuts also contain large amount of phenolic compounds compared with other nuts. Nuts are rich in compounds with antioxidant properties and their consumption can offer preventing from incidence of many diseases including cardiovascular.
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: The past decade has witnessed a good opportunities
for city development schemes in UK. The government encouraged
restoration of city centers to comprise mixed use developments with
high density residential apartments. Investments in regeneration areas
were doing well according to the analyses of Property Databank
(IPD). However, more recent analysis by IPD has shown that since
2007, property in regeneration areas has been more vulnerable to the
market downturn than other types of investment property. The early
stages of a property market downturn may be felt most in
regeneration where funding, investor confidence and occupier
demand would dissipate because the sector was considered more
marginal or risky when development costs rise. Moreover, the Bank
of England survey shows that lenders have sequentially tightened the
availability of credit for commercial real estate since mid-2007. A
sharp reduction in the willingness of banks to lend on commercial
property was recorded. The credit crunch has already affected
commercial property but its impact has been particularly severe in
certain kinds of properties where residential developments are
extremely difficult, in particular city centre apartments and buy-to-let
markets. Commercial property – retail, industrial leisure and mixed
use were also pressed, in Birmingham; tens of mixed use plots were
built to replace old factories in the heart of the city. The purpose of
these developments was to enable young professionals to work and
live in same place. Thousands of people lost their jobs during the
recession, moreover lending was more difficult and the future of
many developments is unknown. The recession casts its shadow upon
the society due to cuts in public spending by government, Inflation,
rising tuition fees and high rise in unemployment generated anger and
hatred was spreading among youth causing vandalism and riots in
many cities. Recent riots targeted many mixed used development in
the UK where banks, shops, restaurants and big stores were robbed
and set into fire leaving residents with horror and shock. This paper
examines the impact of the recession and riots on mixed use
development in UK.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.