Abstract: Alpfa-fetoprotein and its fragments may be an important vehicle for targeted delivery of radionuclides to the tumor. We investigated the effect of conditions on the labeling of biologically active synthetic peptide based on the (F-afp) with technetium-99m. The influence of the nature of the buffer solution, pH, concentration of reductant, concentration of the peptide and the reaction temperature on the yield of labeling was examined. As a result, the following optimal conditions for labeling of (F-afp) are found: pH 8.5 (phosphate and bicarbonate buffers) and pH from 1.7 to 7.0 (citrate buffer). The reaction proceeds with sufficient yield at room temperature for 30 min at the concentration of SnCl2 and (Fafp) (F-afp) is to be less than 10 mkg/ml and 25 mkg/ml, respectively. Investigations of the test drug accumulation in the tumor cells of human breast cancer were carried out. Results can be assumed that the in vivo study of the (F-afp) in experimental tumor lesions will show concentrations sufficient for imaging these lesions by SPECT.
Abstract: One of the best ways for achievement of conventional
vehicle changing to hybrid case is trustworthy simulation result and
using of driving realities. For this object, in this paper, at first sevendegree-
of-freedom dynamical model of vehicle will be shown. Then
by using of statically model of engine, gear box, clutch, differential,
electrical machine and battery, the hybrid automobile modeling will
be down and forward simulation of vehicle for pedals to wheels
power transformation will be obtained. Then by design of a fuzzy
controller and using the proper rule base, fuel economy and
regenerative braking will be marked. Finally a series of
MATLAB/SIMULINK simulation results will be proved the
effectiveness of proposed structure.
Abstract: As the web continues to grow exponentially, the idea
of crawling the entire web on a regular basis becomes less and less
feasible, so the need to include information on specific domain,
domain-specific search engines was proposed. As more information
becomes available on the World Wide Web, it becomes more difficult
to provide effective search tools for information access. Today,
people access web information through two main kinds of search
interfaces: Browsers (clicking and following hyperlinks) and Query
Engines (queries in the form of a set of keywords showing the topic
of interest) [2]. Better support is needed for expressing one's
information need and returning high quality search results by web
search tools. There appears to be a need for systems that do reasoning
under uncertainty and are flexible enough to recover from the
contradictions, inconsistencies, and irregularities that such reasoning
involves. In a multi-view problem, the features of the domain can be
partitioned into disjoint subsets (views) that are sufficient to learn the
target concept. Semi-supervised, multi-view algorithms, which
reduce the amount of labeled data required for learning, rely on the
assumptions that the views are compatible and uncorrelated. This
paper describes the use of semi-structured machine learning approach
with Active learning for the “Domain Specific Search Engines". A
domain-specific search engine is “An information access system that
allows access to all the information on the web that is relevant to a
particular domain. The proposed work shows that with the help of
this approach relevant data can be extracted with the minimum
queries fired by the user. It requires small number of labeled data and
pool of unlabelled data on which the learning algorithm is applied to
extract the required data.
Abstract: The prospective analysis is presented as an important tool to identify the most relevant opportunities and needs in research and development from planned interventions in innovation systems. This study chose Phyllanthus niruri, known as "stone break" to describe the knowledge about the specie, by using biotechnological forecasting through the software Vantage Point. It can be seen a considerable increase in studies on Phyllanthus niruri in recent years and that there are patents about this plant since twenty-five years ago. India was the country that most carried out research on the specie, showing interest, mainly in studies of hepatoprotection, antioxidant and anti-cancer activities. Brazil is in the second place, with special interest for anti-tumor studies. Given the identification of the Brazilian groups that exploit the species it is possible to mediate partnerships and cooperation aiming to help on the implementing of the Program of Herbal medicines (phytotherapics) in Brazil.
Abstract: We report a computational study of the spreading
dynamics of a viral infection in a complex (scale-free) network. The
final epidemic size distribution (FESD) was found to be unimodal or
bimodal depending on the value of the basic reproductive
number R0 . The FESDs occurred on time-scales long enough for
intermediate-time epidemic size distributions (IESDs) to be important
for control measures. The usefulness of R0 for deciding on the
timeliness and intensity of control measures was found to be limited
by the multimodal nature of the IESDs and by its inability to inform
on the speed at which the infection spreads through the population. A
reduction of the transmission probability at the hubs of the scale-free
network decreased the occurrence of the larger-sized epidemic events
of the multimodal distributions. For effective epidemic control, an
early reduction in transmission at the index cell and its neighbors was
essential.
Abstract: Data clustering is an important data exploration technique
with many applications in data mining. We present an enhanced
version of the well known single link clustering algorithm. We will
refer to this algorithm as DCBOR. The proposed algorithm alleviates
the chain effect by removing the outliers from the given dataset.
So this algorithm provides outlier detection and data clustering
simultaneously. This algorithm does not need to update the distance
matrix, since the algorithm depends on merging the most k-nearest
objects in one step and the cluster continues grow as long as possible
under specified condition. So the algorithm consists of two phases;
at the first phase, it removes the outliers from the input dataset. At
the second phase, it performs the clustering process. This algorithm
discovers clusters of different shapes, sizes, densities and requires
only one input parameter; this parameter represents a threshold for
outlier points. The value of the input parameter is ranging from 0 to
1. The algorithm supports the user in determining an appropriate
value for it. We have tested this algorithm on different datasets
contain outlier and connecting clusters by chain of density points,
and the algorithm discovers the correct clusters. The results of
our experiments demonstrate the effectiveness and the efficiency of
DCBOR.
Abstract: This paper presents a study of the Taguchi design
application to optimize surface quality in damper inserted end milling
operation. Maintaining good surface quality usually involves
additional manufacturing cost or loss of productivity. The Taguchi
design is an efficient and effective experimental method in which a
response variable can be optimized, given various factors, using
fewer resources than a factorial design. This Study included spindle
speed, feed rate, and depth of cut as control factors, usage of different
tools in the same specification, which introduced tool condition and
dimensional variability. An orthogonal array of L9(3^4)was used;
ANOVA analyses were carried out to identify the significant factors
affecting surface roughness, and the optimal cutting combination was
determined by seeking the best surface roughness (response) and
signal-to-noise ratio. Finally, confirmation tests verified that the
Taguchi design was successful in optimizing milling parameters for
surface roughness.
Abstract: Along with the advances in medicine, providing medical information to individual patient is becoming more important. In Japan such information via Braille is hardly provided to blind and partially sighted people. Thus we are researching and developing a Web-based automatic translation program “eBraille" to translate Japanese text into Japanese Braille. First we analyzed the Japanese transcription rules to implement them on our program. We then added medical words to the dictionary of the program to improve its translation accuracy for medical text. Finally we examined the efficacy of statistical learning models (SLMs) for further increase of word segmentation accuracy in braille translation. As a result, eBraille had the highest translation accuracy in the comparison with other translation programs, improved the accuracy for medical text and is utilized to make hospital brochures in braille for outpatients and inpatients.
Abstract: This paper investigated the impact of ceiling height and window head heights variation on daylighting inside architectural teaching studio with a full width window. In architectural education, using the studio is more than normal classroom in most credit hours. Therefore, window position, size and dimension of studio have direct influence on level of daylighting. Daylighting design is a critical factor that improves student learning, concentration and behavior, in addition to these, it also reduces energy consumption. The methodology of analysis involves using Radiance in IES software under overcast and cloudy sky in Malaysia. It has been established that presentation of daylighting of architecture studio can be enhanced by changing the ceiling heights and window level, because, different ceiling heights and window head heights can contribute to different range of daylight levels.
Abstract: IEEE has designed 802.11i protocol to address the
security issues in wireless local area networks. Formal analysis is
important to ensure that the protocols work properly without having
to resort to tedious testing and debugging which can only show the
presence of errors, never their absence. In this paper, we present
the formal verification of an abstract protocol model of 802.11i.
We translate the 802.11i protocol into the Strand Space Model and
then prove the authentication property of the resulting model using
the Strand Space formalism. The intruder in our model is imbued
with powerful capabilities and repercussions to possible attacks are
evaluated. Our analysis proves that the authentication of 802.11i is
not compromised in the presented model. We further demonstrate
how changes in our model will yield a successful man-in-the-middle
attack.
Abstract: Lately, an interest has grown greatly in the usages of
RFID in an un-presidential applications. It is shown in the adaptation
of major software companies such as Microsoft, IBM, and Oracle
the RFID capabilities in their major software products. For example
Microsoft SharePoints 2010 workflow is now fully compatible with
RFID platform. In addition, Microsoft BizTalk server is also capable
of all RFID sensors data acquisition. This will lead to applications
that required high bit rate, long range and a multimedia content in
nature. Higher frequencies of operation have been designated for
RFID tags, among them are the 2.45 and 5.8 GHz. The higher the
frequency means higher range, and higher bit rate, but the drawback
is the greater cost. In this paper we present a single layer, low
profile patch antenna operates at 5.8 GHz with pure resistive input
impedance of 50 and close to directive radiation. Also, we propose
a modification to the design in order to improve the operation band
width from 8.7 to 13.8
Abstract: Nozzle is the main part of various spinning systems
such as air-jet and Murata air vortex systems. Recently, many
researchers worked on the usage of the nozzle on different spinning
systems such as conventional ring and compact spinning systems. In
these applications, primary purpose is to improve the yarn quality. In
present study, it was produced the yarns with two different nozzle
types and determined the changes in yarn properties. In order to
explain the effect of the nozzle, airflow structure in the nozzle was
modelled and airflow variables were determined. In numerical
simulation, ANSYS 12.1 package program and Fluid Flow (CFX)
analysis method was used. As distinct from the literature, Shear
Stress Turbulent (SST) model is preferred. And also air pressure at
the nozzle inlet was measured by electronic mass flow meter and
these values were used for the simulation of the airflow. At last, the
yarn was modelled and the area from where the yarn is passing was
included to the numerical analysis.
Abstract: Scalability poses a severe threat to the existing
DRAM technology. The capacitors that are used for storing and
sensing charge in DRAM are generally not scaled beyond 42nm.
This is because; the capacitors must be sufficiently large for reliable
sensing and charge storage mechanism. This leaves DRAM memory
scaling in jeopardy, as charge sensing and storage mechanisms
become extremely difficult. In this paper we provide an overview of
the potential and the possibilities of using Phase Change Memory
(PCM) as an alternative for the existing DRAM technology. The
main challenges that we encounter in using PCM are, the limited
endurance, high access latencies, and higher dynamic energy
consumption than that of the conventional DRAM. We then provide
an overview of various methods, which can be employed to
overcome these drawbacks. Hybrid memories involving both PCM
and DRAM can be used, to achieve good tradeoffs in access latency
and storage density. We conclude by presenting, the results of these
methods that makes PCM a potential replacement for the current
DRAM technology.
Abstract: Hemorrhage Disease of Grass Carp (HDGC) is a kind
of commonly occurring illnesses in summer, and the extremely high
death rate result in colossal losses to aquaculture. As the complex
connections among each factor which influences aquiculture diseases,
there-s no quit reasonable mathematical model to solve the problem at
present.A BP neural network which with excellent nonlinear mapping
coherence was adopted to establish mathematical model;
Environmental factor, which can easily detected, such as breeding
density, water temperature, pH and light intensity was set as the main
analyzing object. 25 groups of experimental data were used for
training and test, and the accuracy of using the model to predict the
trend of HDGC was above 80%. It is demonstrated that BP neural
network for predicating diseases in HDGC has a particularly
objectivity and practicality, thus it can be spread to other aquiculture
disease.
Abstract: Due to the three- dimensional flow pattern interacting with bed material, the process of local scour around bridge piers is complex. Modeling 3D flow field and scour hole evolution around a bridge pier is more feasible nowadays because the computational cost and computational time have significantly decreased. In order to evaluate local flow and scouring around a bridge pier, a completely three-dimensional numerical model, SSIIM program, was used. The model solves 3-D Navier-Stokes equations and a bed load conservation equation. The model was applied to simulate local flow and scouring around a bridge pier in a large natural river with four piers. Computation for 1 day of flood condition was carried out to predict the maximum local scour depth. The results show that the SSIIM program can be used efficiently for simulating the scouring in natural rivers. The results also showed that among the various turbulence models, the k-ω model gives more reasonable results.
Abstract: This study proposes a basic molecular formula for all
proteins. A total of 10,739 proteins belonging to 9 different protein
groups classified on the basis of their functions were selected
randomly. They included enzymes, storage proteins, hormones,
signalling proteins, structural proteins, transport proteins,
immunoglobulins or antibodies, motor proteins and receptor proteins.
After obtaining the protein molecular formula using the ProtParam
tool, the H/C, N/C, O/C, and S/C ratios were determined for each
randomly selected sample. In this case, H, N, O, and S coefficients
were specified per carbon atom. Surprisingly, the results
demonstrated that H, N, O, and S coefficients for all 10,739 proteins
are similar and highly correlated. This study demonstrates that
despite differences in the structure and function, all known proteins
have a similar basic molecular formula CnH1.58 ± 0.015nN0.28 ± 0.005nO0.30
± 0.007nS0.01 ± 0.002n. The total correlation between all coefficients was
found to be 0.9999.
Abstract: In modern agriculture, polymeric hydrogels are
known as a component able to hold an amount of water due to their
3-dimensional network structure and their tendency to absorb water
in humid environments. In addition, these hydrogels are able to
controllably release the fertilisers and pesticides loaded in them.
Therefore, they deliver these materials to the plants' roots and help
them with growing. These hydrogels also reduce the pollution of
underground water sources by preventing the active components
from leaching. In this study, sIPN acrylamide based hydrogels are
synthesised by using acrylamide free radical, potassium acrylate, and
linear polyvinyl alcohol. Ammonium nitrate is loaded in the hydrogel
as the fertiliser. The effect of various amounts of monomers and
linear polymer, measured in molar ratio, on the swelling rate,
equilibrium swelling, and release of ammonium nitrate is studied.
Abstract: This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.
Abstract: In this paper we propose an intelligent agent approach
to control the electric power grid at a smaller granularity in order to
give it self-healing capabilities. We develop a method using the
influence model to transform transmission substations into
information processing, analyzing and decision making (intelligent
behavior) units. We also develop a wireless communication method
to deliver real-time uncorrupted information to an intelligent
controller in a power system environment. A combined networking
and information theoretic approach is adopted in meeting both the
delay and error probability requirements. We use a mobile agent
approach in optimizing the achievable information rate vector and in
the distribution of rates to users (sensors). We developed the concept
and the quantitative tools require in the creation of cooperating semiautonomous
subsystems which puts the electric grid on the path
towards intelligent and self-healing system.
Abstract: Nanoemulsions are a class of emulsions with a droplet
size in the range of 50–500 nm and have attracted a great deal of
attention in recent years because it is unique characteristics. The
physicochemical properties of nanoemulsion suggests that it can be
successfully used to recover the residual oil which is trapped in the
fine pore of reservoir rock by capillary forces after primary and
secondary recovery. Oil-in-water nanoemulsion which can be formed
by high-energy emulsification techniques using specific surfactants
can reduce oil-water interfacial tension (IFT) by 3-4 orders of
magnitude. The present work is aimed on characterization of oil-inwater
nanoemulsion in terms of its phase behavior, morphological
studies; interfacial energy; ability to reduce the interfacial tension and
understanding the mechanisms of mobilization and displacement of
entrapped oil blobs by lowering interfacial tension both at the
macroscopic and microscopic level. In order to investigate the
efficiency of oil-water nanoemulsion in enhanced oil recovery
(EOR), experiments were performed to characterize the emulsion in
terms of their physicochemical properties and size distribution of the
dispersed oil droplet in water phase. Synthetic mineral oil and a series
of surfactants were used to prepare oil-in-water emulsions.
Characterization of emulsion shows that it follows pseudo-plastic
behaviour and drop size of dispersed oil phase follows lognormal
distribution. Flooding experiments were also carried out in a
sandpack system to evaluate the effectiveness of the nanoemulsion as
displacing fluid for enhanced oil recovery. Substantial additional
recoveries (more than 25% of original oil in place) over conventional
water flooding were obtained in the present investigation.