Abstract: This study was aimed to measure effective transverse
relaxation rates (R2*) in the liver and muscle of normal New Zealand
White (NZW) rabbits. R2* relaxation rate has been widely used in
various hepatic diseases for iron overload by quantifying iron contents
in liver. R2* relaxation rate is defined as the reciprocal of T2*
relaxation time and mainly depends on the constituents of tissue.
Different tissues would have different R2* relaxation rates. The signal
intensity decay in Magnetic resonance imaging (MRI) may be
characterized by R2* relaxation rates. In this study, a 1.5T GE Signa
HDxt whole body MR scanner equipped with an 8-channel high
resolution knee coil was used to observe R2* values in NZW rabbit’s
liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were
recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture,
the abdomen of rabbit was landmarked at the center of knee coil to
perform 3-plane localizer scan using fast spoiled gradient echo
(FSPGR) pulse sequence. Afterwards, multi-planar fast gradient echo
(MFGR) scans were performed with 8 various echo times (TEs) to
acquire images for R2* measurements. Regions of interest (ROIs) at
liver and muscle were measured using Advantage workstation.
Finally, the R2* was obtained by a linear regression of ln(sı) on TE.
The results showed that the longer the echo time, the smaller the signal
intensity. The R2* values of liver and muscle were 44.8 ± 10.9 s-1 and
37.4 ± 9.5 s-1, respectively. It implies that the iron concentration of
liver is higher than that of muscle. In conclusion, the more the iron
contents in tissue, the higher the R2*. The correlations between R2*
and iron content in NZW rabbits might be valuable for further
exploration.
Abstract: High Performance Liquid Chromatography (HPLC)
method was developed and validated for simultaneous estimation of
6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing
ginger extract. The chromatographic separation was achieved by
using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase
containing acetonitrile and water (gradient elution). The flow rate
was 1.0 ml/min and the absorbance was monitored at 282 nm. The
proposed method was validated in terms of the analytical parameters
such as specificity, accuracy, precision, linearity, range, limit of
detection (LOD), limit of quantification (LOQ), and determined
based on the International Conference on Harmonization (ICH)
guidelines. The linearity ranges of 6G and 6S were obtained over 20-
60 and 6-18 μg/ml respectively. Good linearity was observed over the
above-mentioned range with linear regression equation Y= 11016x-
23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of
analytes in μg/ml and Y is peak area). The value of correlation
coefficient was found to be 0.9994 for both markers. The limit of
detection (LOD) and limit of quantification (LOQ) for 6G were
0.8567 and 2.8555 μg/ml and for 6S were 0.3672 and 1.2238 μg/ml
respectively. The recovery range for 6G and 6S were found to be
91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels.
The RSD values from repeated extractions for 6G and 6S were 3.43
and 3.09% respectively. The validation of developed method on
precision, accuracy, specificity, linearity, and range were also
performed with well-accepted results.
Abstract: Recent investigations have demonstrated the global
sea level rise due to climate change impacts. In this study, climate
changes study the effects of increasing water level in the strait of
Hormuz. The probable changes of sea level rise should be
investigated to employ the adaption strategies. The climatic output
data of a GCM (General Circulation Model) named CGCM3 under
climate change scenario of A1b and A2 were used. Among different
variables simulated by this model, those of maximum correlation
with sea level changes in the study region and least redundancy
among themselves were selected for sea level rise prediction by using
stepwise regression. One of models (Discrete Wavelet artificial
Neural Network) was developed to explore the relationship between
climatic variables and sea level changes. In these models, wavelet
was used to disaggregate the time series of input and output data into
different components and then ANN was used to relate the
disaggregated components of predictors and input parameters to each
other. The results showed in the Shahid Rajae Station for scenario
A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea
level rise is among 90 t0 105 cm. Furthermore, the result showed a
significant increase of sea level at the study region under climate
change impacts, which should be incorporated in coastal areas
management.
Abstract: Presently various computational techniques are used
in modeling and analyzing environmental engineering data. In the
present study, an intra-comparison of polynomial and radial basis
kernel functions based on Support Vector Regression and, in turn, an
inter-comparison with Multi Linear Regression has been attempted in
modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ
multiple plunging jets (varying from 1 to 16 numbers). The data set
used in this study consists of four input parameters with a total of
eighty eight cases, forty four each for vertical and inclined multiple
plunging jets. For testing, tenfold cross validation was used.
Correlation coefficient values of 0.971 and 0.981 along with
corresponding root mean square error values of 0.0025 and 0.0020
were achieved by using polynomial and radial basis kernel functions
based Support Vector Regression respectively. An intra-comparison
suggests improved performance by radial basis function in
comparison to polynomial kernel based Support Vector Regression.
Further, an inter-comparison with Multi Linear Regression
(correlation coefficient = 0.973 and root mean square error = 0.0024)
reveals that radial basis kernel functions based Support Vector
Regression performs better in modeling and estimating mass transfer
by multiple plunging jets.
Abstract: Prediction of maximum local scour is necessary for
the safety and economical design of the bridges. A number of
equations have been developed over the years to predict local scour
depth using laboratory data and a few pier equations have also been
proposed using field data. Most of these equations are empirical in
nature as indicated by the past publications. In this paper attempts
have been made to compute local depth of scour around bridge pier in
dimensional and non-dimensional form by using linear regression,
simple regression and SVM (Poly & Rbf) techniques along with few
conventional empirical equations. The outcome of this study suggests
that the SVM (Poly & Rbf) based modeling can be employed as an
alternate to linear regression, simple regression and the conventional
empirical equations in predicting scour depth of bridge piers. The
results of present study on the basis of non-dimensional form of
bridge pier scour indicate the improvement in the performance of
SVM (Poly & Rbf) in comparison to dimensional form of scour.
Abstract: Myocardial infarction is one of the leading causes of
death in the world. Some of these deaths occur even before the
patient reaches the hospital. Myocardial infarction occurs as a result
of impaired blood supply. Because the most of these deaths are due to
coronary artery disease, hence the awareness of the warning signs of
a heart attack is essential. Some heart attacks are sudden and intense,
but most of them start slowly, with mild pain or discomfort, then
early detection and successful treatment of these symptoms is vital to
save them. Therefore, importance and usefulness of a system
designing to assist physicians in early diagnosis of the acute heart
attacks is obvious. The main purpose of this study would be to enable patients to
become better informed about their condition and to encourage them
to seek professional care at an earlier stage in the appropriate
situations. For this purpose, the data were collected on 711 heart
patients in Iran hospitals. 28 attributes of clinical factors can be
reported by patients; were studied. Three logistic regression models
were made on the basis of the 28 features to predict the risk of heart
attacks. The best logistic regression model in terms of performance
had a C-index of 0.955 and with an accuracy of 94.9%. The variables,
severe chest pain, back pain, cold sweats, shortness of breath, nausea
and vomiting, were selected as the main features.
Abstract: Objectives: To determine the nutritional status and
risk factors associated with women practicing geophagia in QwaQwa,
South Africa. Materials and Methods: An observational epidemiological study
design was adopted which included an exposed (geophagia) and nonexposed
(control) group. A food frequency questionnaire, anthropometric measurements and blood sampling were applied to
determine nutritional status of participants. Logistic regression
analysis was performed in order to identify factors that were likely to
be associated with the practice of geophagia. Results: The mean total energy intake for the geophagia group (G)
and control group (C) were 10324.31 ± 2755.00 kJ and 10763.94 ±
2556.30 kJ respectively. Both groups fell within the overweight
category according to the mean Body Mass Index (BMI) of each
group (G= 25.59 kg/m2; C= 25.14 kg/m2). The mean serum iron
levels of the geophagia group (6.929 μmol/l) were significantly lower
than that of the control group (13.75 μmol/l) (p = 0.000). Serum
transferrin (G=3.23g/l; C=2.7054g/l) and serum transferrin saturation
(G=8.05%; C=18.74%) levels also differed significantly between
groups (p=0.00). Factors that were associated with the practice of
geophagia included haemoglobin (Odds ratio (OR):14.50), serumiron
(OR: 9.80), serum-ferritin (OR: 3.75), serum-transferrin (OR:
6.92) and transferrin saturation (OR: 14.50). A significant negative
association (p=0.014) was found between women who were wageearners
and those who were not wage-earners and the practice of
geophagia (OR: 0.143; CI: 0.027; 0.755). These findings seem to
indicate that a permanent income may decrease the likelihood of
practising geophagia. Key Findings: Geophagia was confirmed to be a risk factor for
iron deficiency in this community. The significantly strong
association between geophagia and iron deficiency emphasizes the
importance of identifying the practice of geophagia in women,
especially during their child bearing years.
Abstract: This paper tries to answer to the questions whether or
not trade openness causes economic growth and trade policy changes
are good for Turkey as a developing country in global economy
before and after 1980. We employ Johansen co-integration and
Granger causality tests with error correction modeling based on
vector autoregressive. Using WDI data from the pre-1980 and the
post-1980, we find that trade openness and economic growth are cointegrated
in the second term only. Also the results suggest a lack of
long-run causality between our two variables. These findings may
imply that trade policy of Turkey should concentrate more on extra
complementary economic reforms.
Abstract: The research explores the relationship between
management responsibility and corporate governance of listed
companies in Kazakhstan. This research employs firm level data of
selected listed non-financial firms and firm level data “operational”
financial sector, consisted from banking sector, insurance companies
and accumulated pension funds using multivariate regression analysis
under fixed effect model approach. Ownership structure includes
institutional ownership, managerial ownership and private investor’s
ownership. Management responsibility of the firm is expressed by the
decision of the firm on amount of leverage. Results of the cross
sectional panel study for non-financial firms showed that only
institutional shareholding is significantly negatively correlated with
debt to equity ratio. Findings from “operational” financial sector
show that leverage is significantly affected only by the CEO/Chair
duality and the size of financial institutions, and insignificantly
affected by ownership structure. Also, the findings show, that there is
a significant negative relationship between profitability and the debt
to equity ratio for non-financial firms, which is consistent with
pecking order theory. Generally, the found results suggest that
corporate governance and a management responsibility play
important role in corporate performance of listed firms in
Kazakhstan.
Abstract: This article presents an alternative collapse capacity
intensity measure in the three elements form which is influenced by
the spectral ordinates at periods longer than that of the first mode
period at near and far source sites. A parameter, denoted by β, is
defined by which the spectral ordinate effects, up to the effective
period (2T1), on the intensity measure are taken into account. The
methodology permits to meet the hazard-levelled target extreme
event in the probabilistic and deterministic forms. A MATLAB code
is developed involving OpenSees to calculate the collapse capacities
of the 8 archetype RC structures having 2 to 20 stories for regression
process. The incremental dynamic analysis (IDA) method is used to
calculate the structure’s collapse values accounting for the element
stiffness and strength deterioration. The general near field set
presented by FEMA is used in a series of performing nonlinear
analyses. 8 linear relationships are developed for the 8structutres
leading to the correlation coefficient up to 0.93. A collapse capacity
near field prediction equation is developed taking into account the
results of regression processes obtained from the 8 structures. The
proposed prediction equation is validated against a set of actual near
field records leading to a good agreement. Implementation of the
proposed equation to the four archetype RC structures demonstrated
different collapse capacities at near field site compared to those of
FEMA. The reasons of differences are believed to be due to
accounting for the spectral shape effects.
Abstract: The knitted fabric suffers a deformation in its
dimensions due to stretching and tension factors, transverse and
longitudinal respectively, during the process in rectilinear knitting
machines so it performs a dry relaxation shrinkage procedure and
thermal action of prefixed to obtain stable conditions in the knitting.
This paper presents a dry relaxation shrinkage prediction of Bordeaux
fiber using a feed forward neural network and linear regression
models. Six operational alternatives of shrinkage were predicted. A
comparison of the results was performed finding neural network
models with higher levels of explanation of the variability and
prediction. The presence of different reposes is included. The models
were obtained through a neural toolbox of Matlab and Minitab
software with real data in a knitting company of Southern
Guanajuato. The results allow predicting dry relaxation shrinkage of
each alternative operation.
Abstract: The work reported through this paper is an
experimental work conducted on High Performance Concrete (HPC)
with super plasticizer with the aim to develop some models suitable
for prediction of compressive strength of HPC mixes. In this study,
the effect of varying proportions of fly ash (0% to 50% @ 10%
increment) on compressive strength of high performance concrete has
been evaluated. The mix designs studied were M30, M40 and M50 to
compare the effect of fly ash addition on the properties of these
concrete mixes. In all eighteen concrete mixes that have been
designed, three were conventional concretes for three grades under
discussion and fifteen were HPC with fly ash with varying
percentages of fly ash. The concrete mix designing has been done in
accordance with Indian standard recommended guidelines. All the
concrete mixes have been studied in terms of compressive strength at
7 days, 28 days, 90 days, and 365 days. All the materials used have
been kept same throughout the study to get a perfect comparison of
values of results. The models for compressive strength prediction
have been developed using Linear Regression method (LR), Artificial
Neural Network (ANN) and Leave-One-Out Validation (LOOV)
methods.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: The paper aims to evaluate the effect of online
advertising on consumer purchase behavior in Malaysian
organizations. The paper has potential to extend and refine theory. A
survey was distributed among Students of UTM university during the
winter 2014 and 160 responses were collected. Regression analysis
was used to test the hypothesized relationships of the model. Result
shows that the predictors (cost saving factor, convenience factor and
customized product or services) have positive impact on intention to
continue seeking online advertising.
Abstract: Comparative analysis of the properties of melon seed,
coconut fruit and their oil yield were evaluated in this work using
standard analytical technique AOAC. The results of the analysis
carried out revealed that the moisture contents of the samples studied
are 11.15% (melon) and 7.59% (coconut). The crude lipid content are
46.10% (melon) and 55.15% (coconut).The treatment combinations
used (leaching time, leaching temperature and solute: solvent ratio)
showed significant difference (p < 0.05) in yield between the
samples, with melon oil seed flour having a higher percentage range
of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The
physical characterization of the extracted oil was also carried out.
The values gotten for refractive index are 1.487 (melon seed oil) and
1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and
0.002 (coconut oil). The chemical analysis of the extracted oils shows
acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil
(coconut oil) and saponification value of 187.00mg/KOH (melon oil)
and 183.26mg/KOH (coconut oil). The iodine value of the melon oil
gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard
statistical package Minitab version 16.0 was used in the regression
analysis and analysis of variance (ANOVA). The statistical software
mentioned above was also used to optimize the leaching process.
Both samples gave high oil yield at the same optimal conditions. The
optimal conditions to obtain highest oil yield ≥ 52% (melon seed)
and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml,
leaching time of 2hours and leaching temperature of 50oC. The two
samples studied have potential of yielding oil with melon seed giving
the higher yield.
Abstract: Currently, planners try to have more green travel
options to decrease economic, social and environmental problems.
Therefore, this study tries to find significant urban travel factors to be
used to increase the usage of alternative urban travel modes. This
paper attempts to identify the relationship between prominent urban
mobility indicators and daily trips by public transport in 30 cities
from various parts of the world. Different travel modes,
infrastructures and cost indicators were evaluated in this research as
mobility indicators. The results of multi-linear regression analysis
indicate that there is a significant relationship between mobility
indicators and the daily usage of public transport.
Abstract: A biosphere reserve is developed to create harmony
amongst economic development, community development, and
environmental protection, through partnership between human and
nature. Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB BR)
in Riau Province, Indonesia, is unique in that it has peat soil
dominating the area, many springs essential for human livelihood,
high biodiversity. Furthermore, it is the only biosphere reserve
covering privately managed production forest areas. In this research, we aimed at analyzing the threat of deforestation
and forest fire, and the potential of CO2 emission at GSKBB BR. We
used Landsat image, arcView software, and ERDAS IMAGINE 8.5
Software to conduct spatial analysis of land cover and land use
changes, calculated CO2 emission based on emission potential from
each land cover and land use type, and exercised simple linear
regression to demonstrate the relation between CO2 emission
potential and deforestation. The result showed that, beside in the buffer zone and transition
area, deforestation also occurred in the core area. Spatial analysis of
land cover and land use changes from years 2010, 2012, and 2014
revealed that there were changes of land cover and land use from
natural forest and industrial plantation forest to other land use types,
such as garden, mixed garden, settlement, paddy fields, burnt areas,
and dry agricultural land. Deforestation in core area, particularly at
the Giam Siak Kecil Wildlife Reserve and Bukit Batu Wildlife
Reserve, occurred in the form of changes from natural forest in to
garden, mixed garden, shrubs, swamp shrubs, dry agricultural land,
open area, and burnt area. In the buffer zone and transition area,
changes also happened, what once swamp forest changed into garden,
mixed garden, open area, shrubs, swamp shrubs, and dry agricultural
land. Spatial analysis on land cover and land use changes indicated
that deforestation rate in the biosphere reserve from 2010 to 2014 had
reached 16 119 ha/year. Beside deforestation, threat toward the
biosphere reserve area also came from forest fire. The occurrence of forest fire in 2014 had burned 101 723 ha of the
area, in which 9 355 ha of core area, and 92 368 ha of buffer zone
and transition area. Deforestation and forest fire had increased CO2
emission as much as 24 903 855 ton/year.
Abstract: As a basic physiology need, threat to sufficient food
production is threat to human survival. Food security has been an
issue that has gained global concern. This paper looks at the food
security in Nigeria by assessing the availability of food and
accessibility of the available food. The paper employed multiple
linear regression technique and graphic trends of growth rates of
relevant variables to show the situation of food security in Nigeria.
Results of the tests revealed that population growth rate was higher
than the growth rate of food availability in Nigeria for the earlier
period of the study. Commercial bank credit to agricultural sector,
foreign exchange utilization for food and the Agricultural Credit
Guarantee Scheme Fund (ACGSF) contributed significantly to food
availability in Nigeria. Food prices grew at a faster rate than the
average income level, making it difficult to access sufficient food. It
implies that prior to the year 2012; there was insufficient food to feed
the Nigerian populace. However, continued credit to the food and
agricultural sector will ensure sustained and sufficient production of
food in Nigeria. Microfinance banks should make sufficient credit
available to smallholder farmer. Government should further control
and subsidize the rising price of food to make it more accessible by
the people.
Abstract: This paper seeks to assess the implications of bank
consolidation on the performance of small and medium scale
enterprises in the Nigerian economy. Multiple linear regression
technique and correlation matrix test were employed to measure the
extent to which small and medium scale enterprises asset size,
survival and access to credit were influenced. The result showed that
bank deposit (BD) and bank credit (L or BC) impacted on asset size
and survival of small and medium scale enterprises. None of the
variables had significant impact on SMEs access to credit. There is a
shift of focus by commercial banks away from small and medium
scale enterprises (small customers), which is evidenced by the
significant negative influence of bank credit to both the survival and
asset size of small and medium enterprises. While micro finance
banks work hard at providing funds to small and medium scale
entrepreneurs, their capacity to meet the needs of these entrepreneurs
is constrained. CBN should make policies that will boost micro
finance bank’s capital and also monitor closely the management of
the banks to ensure prudent financing of small and medium scale
investments.
Abstract: The present paper attempts to investigate the
prediction of air entrainment rate and aeration efficiency of a free
overfall jets issuing from a triangular sharp crested weir by using
regression based modelling. The empirical equations, Support vector
machine (polynomial and radial basis function) models and the linear
regression techniques were applied on the triangular sharp crested
weirs relating the air entrainment rate and the aeration efficiency to
the input parameters namely drop height, discharge, and vertex angle.
It was observed that there exists a good agreement between the
measured values and the values obtained using empirical equations,
Support vector machine (Polynomial and rbf) models and the linear
regression techniques. The test results demonstrated that the SVM
based (Poly & rbf) model also provided acceptable prediction of the
measured values with reasonable accuracy along with empirical
equations and linear regression techniques in modelling the air
entrainment rate and the aeration efficiency of a free overfall jets
issuing from triangular sharp crested weir. Further sensitivity analysis
has also been performed to study the impact of input parameter on the
output in terms of air entrainment rate and aeration efficiency.