Abstract: The prediction of transmembrane helical segments
(TMHs) in membrane proteins is an important field in the
bioinformatics research. In this paper, a new method based on discrete
wavelet transform (DWT) has been developed to predict the number
and location of TMHs in membrane proteins. PDB coded as 1KQG
was chosen as an example to describe the prediction of the number and
location of TMHs in membrane proteins by using this method. To
access the effect of the method, 80 proteins with known 3D-structure
from Mptopo database are chosen at random as the test objects
(including 325 TMHs), 308 of which can be predicted accurately, the
average predicted accuracy is 96.3%. In addition, the above 80
membrane proteins are divided into 13 groups according to their
function and type. In particular, the results of the prediction of TMHs
of the 13 groups are satisfying.
Abstract: In this paper after reviewing some previous studies, in
order to optimize the above knee prosthesis, beside the inertial
properties a new controlling parameter is informed. This controlling
parameter makes the prosthesis able to act as a multi behavior system
when the amputee is opposing to different environments. This active
prosthesis with the new controlling parameter can simplify the
control of prosthesis and reduce the rate of energy consumption in
comparison to recently presented similar prosthesis “Agonistantagonist
active knee prosthesis".
In this paper three models are generated, a passive, an active, and
an optimized active prosthesis. Second order Taylor series is the
numerical method in solution of the models equations and the
optimization procedure is genetic algorithm.
Modeling the prosthesis which comprises this new controlling
parameter (SEP) during the swing phase represents acceptable results
in comparison to natural behavior of shank. Reported results in this
paper represent 3.3 degrees as the maximum deviation of models
shank angle from the natural pattern. The natural gait pattern belongs
to walking at the speed of 81 m/min.
Abstract: Adaptive echo cancellers with two-path algorithm are
applied to avoid the false adaptation during the double-talk situation.
In the two-path algorithm, several transfer logic solutions have been
proposed to control the filter update. This paper presents an improved
transfer logic solution. It improves the convergence speed of the
two-path algorithm, and allows the reduction of the memory elements
and computational complexity. Results of simulations show the
improved performance of the proposed solution.
Abstract: Our aim in this piece of work is to demonstrate the
power of the Laplace Adomian decomposition method (LADM) in
approximating the solutions of nonlinear differential equations
governing the two-dimensional viscous flow induced by a shrinking
sheet.
Abstract: In the present study, we aimed to design the
intrauterine and extrauterine exposure to 1800 MHz GSM-like RF
radiation and investigate its possible bio-effects on infant female
rabbits. Totally thirty-six New Zealand White female rabbits, onemonth
old, were randomly divided into four groups which are
composed of 9 rabbits; i. Group I [Intrauterine (IU) exposure(-);
Extrauterine (EU) exposure (-)], Group II [IU exposure (-); EU
exposure (+)], Group III [IU exposure(+);EU exposure(-)], Group IV
[IU exposure (+);EU exposure(+)]. The master regulatory enzymes
activities of pentose phosphate pathway (glucose-6-phosphate
dehydrogenase, G-6PD; 6-phosphogluconate dehydrogenase, 6-
PGDH) and glutathione-dependent metabolism (glutathione
peroxidase, GSH-Px; glutathione reductase, GR; glutathione Stransferase,
GST, thioredoxin reductase, TRx) were analyzed in liver
tissues of young female rabbits. Decreased G-6PD, 6-PGD, GSH-Px,
GR activities were found in Group III compared to Group I (p
Abstract: The present paper is an experimental investigation of
roughness effects on nucleate pool boiling of refrigerant R113 on
horizontal circular copper surfaces. The copper samples were treated
by different sand paper grit sizes to achieve different surface
roughness. The average surface roughness of the four samples was
0.901, 0.735, 0.65, and 0.09, respectively. The experiments were
performed in the heat flux range of 8 to 200kW/m2. The heat transfer
coefficient was calculated by measuring wall superheat of the
samples and the input heat flux. The results show significant
improvement of heat transfer coefficient as the surface roughness is
increased. It is found that the heat transfer coefficient of the sample
with Ra=0.901 is 3.4, 10.5, and 38.5% higher in comparison with
surfaces with Ra of 0.735, 0.65, and 0.09 at heat flux of 170 kW/m2.
Moreover, the results are compared with literature data and the well
known Cooper correlation.
Abstract: Zero inflated Strict Arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, maximum likelihood estimation method is used in estimating the parameters for zero inflated strict arcsine model. Bootstrapping is then employed to compute the confidence intervals for the estimated parameters.
Abstract: Quantitative researching on the degree of incidence between the logistics industry and relevant macroscopic system elements is the basis of reasonable and scientific policy on industrial development. In the light of the macro-level, the logistics industry system is consisted of multiple macroscopic agents such as macro-economic, infrastructure, social environment, market demanding, the traditional industry, industry life cycle, policy , system and so on. This paper studies the grey incidence among the macroscopic agents in the logistics industry system. It is demonstrated that the releasing of the logistics services from the logistics outsourcing enterprises determines the growth of the logistics size. Although the information and communication technology is able to promote the formation of the modern logistics industry to some extent, the development of the modern logistics industry depends more on the development of national economy and the investment in the capital assets of the logistics industry.
Abstract: In order to develop any strategy, it is essential to first
identify opportunities, threats, weak and strong points. Assessment of
technology level provides the possibility of concentrating on weak
and strong points. The results of technology assessment have a direct
effect on decision making process in the field of technology transfer
or expansion of internal research capabilities so it has a critical role
in technology management. This paper presents a conceptual model
to analyze the technology capability of a company as a whole and in
four main aspects of technology. This model was tested on 10
automotive parts manufacturers in IRAN. Using this model,
capability level of manufacturers was investigated in four fields of
managing aspects, hard aspects, human aspects, and information and
knowledge aspects. Results show that these firms concentrate on hard
aspect of technology while others aspects are poor and need to be
supported more. So this industry should develop other aspects of
technology as well as hard aspect to have effective and efficient use
of its technology. These paper findings are useful for the technology
planning and management in automotive part manufactures in IRAN
and other Industries which are technology followers and transport
their needed technologies.
Abstract: In this paper, a comparative study of application of
supervised and unsupervised learning algorithms on illumination
invariant face recognition has been carried out. The supervised
learning has been carried out with the help of using a bi-layered
artificial neural network having one input, two hidden and one output
layer. The gradient descent with momentum and adaptive learning
rate back propagation learning algorithm has been used to implement
the supervised learning in a way that both the inputs and
corresponding outputs are provided at the time of training the
network, thus here is an inherent clustering and optimized learning of
weights which provide us with efficient results.. The unsupervised
learning has been implemented with the help of a modified
Counterpropagation network. The Counterpropagation network
involves the process of clustering followed by application of Outstar
rule to obtain the recognized face. The face recognition system has
been developed for recognizing faces which have varying
illumination intensities, where the database images vary in lighting
with respect to angle of illumination with horizontal and vertical
planes. The supervised and unsupervised learning algorithms have
been implemented and have been tested exhaustively, with and
without application of histogram equalization to get efficient results.
Abstract: The Navier Stokes Equations (NSE) for an incompressible fluid of variable viscosity in the presence of an unknown external force in Von-Mises system x,\ are transformed, and some new exact solutions for a class of flows characterized by equation y f x a\b for an arbitrary state equation are determined, where f x is a function, \ the stream function, a z 0 and b are the arbitrary constants. In three, out of four cases, the function f x is arbitrary, and the solutions are the solutions of the flow equations for all the flows characterized by the equationy f x a\b. Streamline patterns for some forms of f x in unbounded and bounded regions are given.
Abstract: A new numerical method for simultaneously updating mass and stiffness matrices based on incomplete modal measured data is presented. By using the Kronecker product, all the variables that are to be modified can be found out and then can be updated directly. The optimal approximation mass matrix and stiffness matrix which satisfy the required eigenvalue equation and orthogonality condition are found under the Frobenius norm sense. The physical configuration of the analytical model is preserved and the updated model will exactly reproduce the modal measured data. The numerical example seems to indicate that the method is quite accurate and efficient.
Abstract: Mutations of the telomeric copy of the survival motor neuron 1 (SMN1) gene cause spinal muscular atrophy. A deletion of the Eef1a2 gene leads to lower motor neuron degeneration in wasted mice. Indirect evidences have been shown that the eEF1A protein family may interact with SMN, and our previous study showed that abnormalities of neuromuscular junctions in wasted mice were similar to those of Smn mutant mice. To determine potential colocalization between SMN and tissue-specific translation elongation factor 1A2 (eEF1A2), an immunochemical analysis of HeLa cells transfected with the plasmid pcDNA3.1(+)C-hEEF1A2- myc and a new quantitative test of colocalization by intensity correlation analysis (ICA) was used to explore the association of SMN and eEF1A2. Here the results showed that eEF1A2 redistributed from the cytoplasm to the nucleus in response to serum and epidermal growth factor. In the cytoplasm, compelling evidence showed that staining for myc-tagged eEF1A2 varied in synchrony with that for SMN, consistent with the formation of a SMN-eEF1A2 complex in the cytoplasm of HeLa cells. These findings suggest that eEF1A2 may colocalize with SMN in the cytoplasm and may be a component of the SMN complex. However, the limitation of the ICA method is an inability to resolve colocalization in components of small organelles such as the nucleus.
Abstract: In this paper, the techniques for estimating the
residual stress in high velocity oxy fuel thermal spray coatings have
been discussed and compared. The development trend and the last
investigation have been studied. It is seemed that the there is not
effective study on the effect of the peening action in HVOF
analytically and numerically.
Abstract: A P0-matrix is a real square matrix all of whose principle minors are nonnegative. In this paper, we consider the class of P0-matrix. Our main aim is to determine which sign pattern matrices are admissible for this class of real matrices.
Abstract: The research objective was to study the toxicity of silver nanoparticles in aquatic organisms. Three forms of free silver ion nanoparticles (Ag+), silver nano particles (nano-Ag0) and silver oxide nanoparticles (nano Ag2O) were examined for toxic effects with Chlorella sp. and Moina macrocopa. The results showed that the toxicity of three silver ion forms to both organisms was examined
Abstract: When binary decision diagrams are formed from
uniformly distributed Monte Carlo data for a large number of
variables, the complexity of the decision diagrams exhibits a
predictable relationship to the number of variables and minterms. In
the present work, a neural network model has been used to analyze the
pattern of shortest path length for larger number of Monte Carlo data
points. The neural model shows a strong descriptive power for the
ISCAS benchmark data with an RMS error of 0.102 for the shortest
path length complexity. Therefore, the model can be considered as a
method of predicting path length complexities; this is expected to lead
to minimum time complexity of very large-scale integrated circuitries
and related computer-aided design tools that use binary decision
diagrams.
Abstract: Understanding how airborne pathogens are
transported through hospital wards is essential for determining the
infection risk to patients and healthcare workers. This study utilizes
Computational Fluid Dynamics (CFD) simulations to explore
possible pathogen transport within a six-bed partitioned Nightingalestyle
hospital ward.
Grid independence of a ward model was addressed using the Grid
Convergence Index (GCI) from solutions obtained using three fullystructured
grids. Pathogens were simulated using source terms in
conjunction with a scalar transport equation and a RANS turbulence
model. Errors were found to be less than 4% in the calculation of air
velocities but an average of 13% was seen in the scalar field.
A parametric study of variations in the pathogen release point
illustrated that its distribution is strongly influenced by the local
velocity field and the degree of air mixing present.
Abstract: In illumination variant face recognition, existing
methods extracting face albedo as light normalized image may lead to
loss of extensive facial details, with light template discarded. To
improve that, a novel approach for realistic facial texture
reconstruction by combining original image and albedo image is
proposed. First, light subspaces of different identities are established
from the given reference face images; then by projecting the original
and albedo image into each light subspace respectively, texture
reference images with corresponding lighting are reconstructed and
two texture subspaces are formed. According to the projections in
texture subspaces, facial texture with normal light can be synthesized.
Due to the combination of original image, facial details can be
preserved with face albedo. In addition, image partition is applied to
improve the synthesization performance. Experiments on Yale B and
CMUPIE databases demonstrate that this algorithm outperforms the
others both in image representation and in face recognition.
Abstract: Structural representation and technology mapping of
a Boolean function is an important problem in the design of nonregenerative
digital logic circuits (also called combinational logic
circuits). Library aware function manipulation offers a solution to
this problem. Compact multi-level representation of binary networks,
based on simple circuit structures, such as AND-Inverter Graphs
(AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR
Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter
Graphs, Reduced Boolean Circuits [8] does exist in
literature. In this work, we discuss a novel and efficient graph
realization for combinational logic circuits, represented using a
NAND-NOR-Inverter Graph (NNIG), which is composed of only
two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells.
The networks are constructed on the basis of irredundant disjunctive
and conjunctive normal forms, after factoring, comprising terms with
minimum support. Construction of a NNIG for a non-regenerative
function in normal form would be straightforward, whereas for the
complementary phase, it would be developed by considering a virtual
instance of the function. However, the choice of best NNIG for a
given function would be based upon literal count, cell count and
DAG node count of the implementation at the technology
independent stage. In case of a tie, the final decision would be made
after extracting the physical design parameters.
We have considered AIG representation for reduced disjunctive
normal form and the best of OIG/AOG/AOIG for the minimized
conjunctive normal forms. This is necessitated due to the nature of
certain functions, such as Achilles- heel functions. NNIGs are found
to exhibit 3.97% lesser node count compared to AIGs and
OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells
than AIGs and OIG/AOG/AOIGs for the various samples considered.
We compare the power efficiency and delay improvement achieved
by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for
various case studies. In comparison with functionally equivalent,
irredundant and compact AIGs, NNIGs report mean savings in power
and delay of 43.71% and 25.85% respectively, after technology
mapping with a 0.35 micron TSMC CMOS process. For a
comparison with OIG/AOG/AOIGs, NNIGs demonstrate average
savings in power and delay by 47.51% and 24.83%. With respect to
device count needed for implementation with static CMOS logic
style, NNIGs utilize 37.85% and 33.95% lesser transistors than their
AIG and OIG/AOG/AOIG counterparts.