Abstract: This study aimed at investigating whether the
functional brain networks constructed using the initial EEG (obtained
when patients first visited hospital) can be correlated with the
progression of cognitive decline calculated as the changes of
mini-mental state examination (MMSE) scores between the latest and
initial examinations. We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions, and the network analysis based
on graph theory to investigate the organization of functional networks
in aMCI. Our finding suggested that higher integrated functional
network with sufficient connection strengths, dense connection
between local regions, and high network efficiency in processing
information at the initial stage may result in a better prognosis of the
subsequent cognitive functions for aMCI. In conclusion, the functional
connectivity can be a useful biomarker to assist in prediction of
cognitive declines in aMCI.
Abstract: Novel bio-based polymer electrolyte was synthesized
with LiClO4 as the main source of charge carrier. Initially,
polyurethane-LiClO4 polymer electrolytes were synthesized via
prepolymerization method with different NCO/OH ratios and labelled
them as PU1, PU2, PU3 and PU4. Fourier transform infrared (FTIR)
analysis indicates the co-ordination between Li+ ion and polyurethane
in PU1. Differential scanning calorimetry (DSC) analysis indicates
PU1 has the highest glass transition temperature (Tg) corresponds to
the most abundant urethane group which is the hard segment in PU1.
Scanning electron microscopy (SEM) shows the good miscibility
between lithium salt and the polymer. The study found that PU1
possessed the greatest ionic conductivity and the lowest activation
energy, Ea. All the polyurethanes exhibited linear Arrhenius
variations indicating ion transport via simple lithium ion hopping in
polyurethane. This research proves the NCO content in polyurethane
plays an important role in affecting the ionic conductivity of this
polymer electrolyte.
Abstract: This study was conducted to evaluate the manganese
removal from aqueous solution using Banana peels activated carbon
(BPAC). Batch experiments have been carried out to determine the
influence of parameters such as pH, biosorbent dose, initial metal ion
concentrations and contact times on the biosorption process. From
these investigations, a significant increase in percentage removal of
manganese 97.4% is observed at pH value 5.0, biosorbent dose 0.8 g,
initial concentration 20 ppm, temperature 25 ± 2°C, stirring rate 200
rpm and contact time 2h. The equilibrium concentration and the
adsorption capacity at equilibrium of the experimental results were
fitted to the Langmuir and Freundlich isotherm models; the Langmuir
isotherm was found to well represent the measured adsorption data
implying BPAC had heterogeneous surface. A raw groundwater
samples were collected from Baharmos groundwater treatment plant
network at Embaba and Manshiet Elkanater City/District-Giza,
Egypt, for treatment at the best conditions that reached at first phase
by BPAC. The treatment with BPAC could reduce iron and
manganese value of raw groundwater by 91.4% and 97.1%,
respectively and the effect of the treatment process on the
microbiological properties of groundwater sample showed decrease
of total bacterial count either at 22°C or at 37°C to 85.7% and 82.4%,
respectively. Also, BPAC was characterized using SEM and FTIR
spectroscopy.
Abstract: Artemisia species, which are medically beneficial, are
widespread in temperate regions of both Northern and Southern
hemispheres among which Iran is located. About 35 species of
Artemisia are indigenous in Iran among them some are widespread in
all or most provinces, yet some are restricted to some specific
regions. In this review paper, initially, GC-Mass results of some
experiments done in different provinces of Iran are mentioned among
them some compounds are common among species, some others are
mostly restricted to other species; after that, medical advantages
based on some researches on species of this genus are reviewed;
different qualities such as anti-leishmania, anti-bacteria, antiviral as
well as anti-proliferative could be mentioned.
Abstract: Calcium phosphate coating (CaP) has been employed
for protein delivery, but the typical direct protein adsorption on the
coating led to low incorporation content and fast release of the
protein from the coating. By using bovine serum albumin (BSA) as a
model protein, rapid biomimetic co-precipitation between calcium
phosphate and BSA was employed to control the distribution of BSA
within calcium phosphate coating during biomimetic formation on
titanium surface for only 6 h at 50oC in an accelerated calcium
phosphate solution. As a result, the amount of BSA incorporation and
release duration could be increased by using a rapid biomimetic coprecipitation
technique. Up to 43 fold increases in the BSA
incorporation content and the increase from 6 h to more than 360 h in
release duration compared to typical direct adsorption technique were
observed depending on the initial BSA concentration used during coprecipitation
(1, 10 and 100 μg.ml-1). From x-ray diffraction and
Fourier transform infrared spectroscopy studies, the coating
composition was not altered with the incorporation of BSA by this
rapid biomimetic co-precipitation and mainly comprised octacalcium
phosphate and hydroxyapatite. However, the microstructure of
calcium phosphate crystals changed from straight, plate-like units to
curved, plate-like units with increasing BSA content.
Abstract: The system is designed to show images which are
related to the query image. Extracting color, texture, and shape
features from an image plays a vital role in content-based image
retrieval (CBIR). Initially RGB image is converted into HSV color
space due to its perceptual uniformity. From the HSV image, Color
features are extracted using block color histogram, texture features
using Haar transform and shape feature using Fuzzy C-means
Algorithm. Then, the characteristics of the global and local color
histogram, texture features through co-occurrence matrix and Haar
wavelet transform and shape are compared and analyzed for CBIR.
Finally, the best method of each feature is fused during similarity
measure to improve image retrieval effectiveness and accuracy.
Abstract: In this paper, strontium ferrite (SrO.6Fe2O3) was
synthesized by the sol-gel auto-combustion process. The thermal
behavior of powder obtained from self-propagating combustion of
initial gel was evaluated by simultaneous differential thermal analysis
(DTA) and thermo gravimetric (TG), from room temperature to
1200°C. The as-burnt powder was calcined at various temperatures
from 700-900°C to achieve the single-phase Sr-ferrite. Phase
composition, morphology and magnetic properties were investigated
using X-ray diffraction (XRD), transmission electron microscopy
(TEM) and vibrating sample magnetometry (VSM) techniques.
Results showed that the single-phase and nano-sized hexagonal
strontium ferrite particles were formed at calcination temperature of
800°C with crystallite size of 27 nm and coercivity of 6238 Oe.
Abstract: The article presents the trends in Georgian wine
market development and evaluates the competitive advantages of
Georgia to enter the wine market based on its customs, traditions and
historical practices combined with modern technologies.
In order to analyze the supply of wine, dynamics of vineyard land
area and grape varieties are discussed, trends in wine production are
presented, trends in export and import are evaluated, local wine
market, its micro and macro environments are studied and analyzed
based on the interviews with experts and analysis of initial recording
materials.
For strengthening its position on the international market, the level
of competitiveness of Georgian wine is defined, which is evaluated
by “ex-ante” and “ex-post” methods, as well as by four basic and two
additional factors of the Porter’s diamond method; potential
advantages and disadvantages of Georgian wine are revealed.
Conclusions are made by identifying the factors that hinder the
development of Georgian wine market. Based on the conclusions,
relevant recommendations are developed.
Abstract: Artificial Neural Networks (ANN) trained using backpropagation
(BP) algorithm are commonly used for modeling
material behavior associated with non-linear, complex or unknown
interactions among the material constituents. Despite multidisciplinary
applications of back-propagation neural networks
(BPNN), the BP algorithm possesses the inherent drawback of
getting trapped in local minima and slowly converging to a global
optimum. The paper present a hybrid artificial neural networks and
genetic algorithm approach for modeling slump of ready mix
concrete based on its design mix constituents. Genetic algorithms
(GA) global search is employed for evolving the initial weights and
biases for training of neural networks, which are further fine tuned
using the BP algorithm. The study showed that, hybrid ANN-GA
model provided consistent predictions in comparison to commonly
used BPNN model. In comparison to BPNN model, the hybrid ANNGA
model was able to reach the desired performance goal quickly.
Apart from the modeling slump of ready mix concrete, the synaptic
weights of neural networks were harnessed for analyzing the relative
importance of concrete design mix constituents on the slump value.
The sand and water constituents of the concrete design mix were
found to exhibit maximum importance on the concrete slump value.
Abstract: Strontium hexaferrite (SrFe12O19; Sr-ferrite) is one of
the well-known materials for permanent magnets. In this study, Mtype
strontium ferrite was prepared by following the conventional
ceramic method from steelmaking by-product. Initial materials;
SrCO3 and by-product, were mixed together in the composition of
SrFe12O19 in different Sr/Fe ratios. The mixtures of these raw
materials were dry-milled for 6h. The blended powder was presintered
(i.e. calcination) at 1000°C for different times periods, then
cooled down to room temperature. These pre-sintered samples were
re-milled in a dry atmosphere for 1h and then fired at different
temperatures in atmospheric conditions, and cooled down to room
temperature. The produced magnetic powder has a dense hexagonal
grain shape structure. The calculated energy product values for the
produced samples ranged from 0.3 to 2.4 MGOe.
Abstract: A vacuum fractionation technique was introduced to remove ethanol from fermentation broth. The effect of initial glucose and ethanol concentrations were investigated for specific productivity. The inhibitory ethanol concentration was observed at 100 g/L. In order to increase the fermentation performance, the ethanol product was removed as soon as it is produced. The broth was boiled at 35oC by reducing the pressure to 65 mBar. The ethanol/water vapor was fractionated for up to 90 wt% before leaving the column. Ethanol concentration in the broth was kept lower than 25 g/L, thus minimized the product inhibition effect to the yeast cells. For batch extractive fermentation, a high substrate utilization rate was obtained at 26.6 g/L.h and most of glucose was consumed within 21 h. For repeated-batch extractive fermentation, addition of glucose was carried out up to 9 times and ethanol was produced more than 8-fold higher than batch fermentation.
Abstract: An optimisation method using both global and local
optimisation is implemented to determine the flapping profile which
will produce the most lift for an experimental wing-actuation system.
The optimisation method is tested using a numerical quasi-steady
analysis. Results of an optimised flapping profile show a 20% increase
in lift generated as compared to flapping profiles obtained by high
speed cinematography of a Sympetrum frequens dragonfly. Initial
optimisation procedures showed 3166 objective function evaluations.
The global optimisation parameters - initial sample size and stage
one sample size, were altered to reduce the number of function
evaluations. Altering the stage one sample size had no significant
effect. It was found that reducing the initial sample size to 400
would allow a reduction in computational effort to approximately
1500 function evaluations without compromising the global solvers
ability to locate potential minima. To further reduce the optimisation
effort required, we increase the local solver’s convergence tolerance
criterion. An increase in the tolerance from 0.02N to 0.05N decreased
the number of function evaluations by another 20%. However, this
potentially reduces the maximum obtainable lift by up to 0.025N.
Abstract: The study investigated the implementation of the
Neural Network (NN) techniques for prediction of the loading of Cu
ions onto clinoptilolite. The experimental design using analysis of
variance (ANOVA) was chosen for testing the adequacy of the
Neural Network and for optimizing of the effective input parameters
(pH, temperature and initial concentration). Feed forward, multi-layer
perceptron (MLP) NN successfully tracked the non-linear behavior of
the adsorption process versus the input parameters with mean squared
error (MSE), correlation coefficient (R) and minimum squared error
(MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed
that NN modeling techniques could effectively predict and simulate
the highly complex system and non-linear process such as ionexchange.
Abstract: Sustainable tall buildings that provide comfortable,
healthy and efficient indoor environments are clearly desirable as the
densification of living and working space for the world’s increasing
population proceeds. For environmental concerns, these buildings
must also be energy efficient. One component of these tasks is the
provision of indoor air quality and thermal comfort, which can be
enhanced with natural ventilation by the supply of fresh air. Working
spaces can only be naturally ventilated with connections to the
outdoors utilizing operable windows, double facades, ventilation
stacks, balconies, patios, terraces and skygardens. Large amounts of
fresh air can be provided to the indoor spaces without mechanical
air-conditioning systems, which are widely employed in
contemporary tall buildings.
This paper tends to present the concept of natural ventilation for
sustainable tall office buildings in order to achieve healthy and
comfortable working spaces, as well as energy efficient
environments. Initially the historical evolution of ventilation
strategies for tall buildings is presented, beginning with natural
ventilation and continuing with the introduction of mechanical airconditioning
systems. Then the emergence of natural ventilation due
to the health and environmental concerns in tall buildings is handled,
and the strategies for implementing this strategy are revealed. In the
next section, a number of case studies that utilize this strategy are
investigated. Finally, how tall office buildings can benefit from this
strategy is discussed.
Abstract: In this paper, we introduce a method for improving
the embedded Runge-Kutta-Fehlberg4(5) method. At each integration
step, the proposed method is comprised of two equations for the
solution and the error, respectively. These solution and error are
obtained by solving an initial value problem whose solution has the
information of the error at each integration step. The constructed algorithm
controls both the error and the time step size simultaneously and
possesses a good performance in the computational cost compared to
the original method. For the assessment of the effectiveness, EULR
problem is numerically solved.
Abstract: Prior literature on innovation diffusion or acceptance has almost exclusively concentrated on consumers’ positive attitudes and behaviors for new products/services. Consumers’ negative attitudes or behaviors to innovations have received relatively little marketing attention, but it happens frequently in practice. This study discusses consumer psychological factors when they try to learn or use new technologies. According to recent research, technological innovation acceptance has been considered as a dynamic or mediated process. This research argues that consumers can experience inertia and emotions in the initial use of new technologies. However, given such consumer psychology, the argument can be made as to whether the inclusion of consumer inertia (routine seeking and cognitive rigidity) and emotions increases the predictive power of new technology acceptance model. As data from the empirical study find, the process is potentially consumer emotion changing (independent of performance benefits) because of technology complexity and consumer inertia, and impact innovative technology use significantly. Finally, the study presents the superior predictability of the hypothesized model, which let managers can better predict and influence the successful diffusion of complex technological innovations.
Abstract: An alternative approach is proposed to develop the analytic solution for one dimensional heat conduction with one mixed type boundary condition and general time-dependent heat transfer coefficient. In this study, the physic meaning of the solution procedure is revealed. It is shown that the shifting function takes the physic meaning of the reciprocal of Biot function in the initial time. Numerical results show the accuracy of this study. Comparing with those given in the existing literature, the difference is less than 0.3%.
Abstract: This study deals with an advanced numerical
techniques to detect tensile forces in cable-stayed structures. The
proposed method allows us not only to avoid the trap of minimum at
initial searching stage but also to find their final solutions in better
numerical efficiency. The validity of the technique is numerically
verified using a set of dynamic data obtained from a simulation of the
cable model modeled using the finite element method. The results
indicate that the proposed method is computationally efficient in
characterizing the tensile force variation for cable-stayed structures.
Abstract: There are several types of metal-based devices conceived as dampers for the seismic energy absorber whereby damages to the major structural components could be minimized for both new and existing structures. This paper aimed to develop and evaluate structural performance of slit circular shear panel damper for passive seismic energy protection by inelastic deformation. Structural evaluation was done using commercially available nonlinear FE simulation program. The main parameters considered are: diameter-to-thickness (D/t) ratio and slit length-to-width ratio (l/w). Depending on these parameters three different buckling mode and hysteretic behavior was found: yielding prior to buckling without strength degradation, yielding prior to buckling with strength degradation and yielding with buckling and strength degradation which forms pinching at initial displacement. The susceptible location at which the possible crack is initiated is also identified for selected specimens using rupture index.
Abstract: Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.