Abstract: New methodologies for XOR-XNOR circuits are
proposed to improve the speed and power as these circuits are basic
building blocks of many arithmetic circuits. This paper evaluates and
compares the performance of various XOR-XNOR circuits. The
performance of the XOR-XNOR circuits based on TSMC 0.18μm
process models at all range of the supply voltage starting from 0.6V
to 3.3V is evaluated by the comparison of the simulation results
obtained from HSPICE. Simulation results reveal that the proposed
circuit exhibit lower PDP and EDP, more power efficient and faster
when compared with best available XOR-XNOR circuits in the
literature.
Abstract: In the current Grid environment, efficient workload
management presents a significant challenge, for which there are
exorbitant de facto standards encompassing resource discovery,
brokerage, and data transfer, among others. In addition, the real-time
resource status, essential for an optimal resource allocation strategy,
is often not readily accessible. To address these issues and provide a
cleaner abstraction of the Grid with the potential of generalizing into
arbitrary resource-sharing environment, this paper proposes a new
Condor-based pilot mechanism applied in the PanDA architecture,
PanDA-PF WMS, with the goal of providing a more generic yet
efficient resource allocating strategy. In this architecture, the PanDA
server primarily acts as a repository of user jobs, responding to pilot
requests from distributed, remote resources. Scheduling decisions are
subsequently made according to the real-time resource information
reported by pilots. Pilot Factory is a Condor-inspired solution for a
scalable pilot dissemination and effectively functions as a resource
provisioning mechanism through which the user-job server, PanDA,
reaches out to the candidate resources only on demand.
Abstract: In this paper two models using a functional network
were employed to solving classification problem. Functional networks
are generalized neural networks, which permit the specification of
their initial topology using knowledge about the problem at hand. In
this case, and after analyzing the available data and their relations, we
systematically discuss a numerical analysis method used for
functional network, and apply two functional network models to
solving XOR problem. The XOR problem that cannot be solved with
two-layered neural network can be solved by two-layered functional
network, which reveals a potent computational power of functional
networks, and the performance of the proposed model was validated
using classification problems.
Abstract: The nanosized polymeric micelles release the drug
due to acoustic cavitation, which is enhanced in dual frequency
ultrasonic fields. In this study, adult female Balb/C mice were
transplanted with spontaneous breast adenocarcinoma tumors and
were injected with a dose of 1.3 mg/kg doxorubicin in one of three
forms: free doxorubicin, micellar doxorubicin without sonication and
micellar doxorubicin with sonication. To increase cavitation yield,
the tumor region was sonicated with low level dual frequency of 3
MHz and 28 kHz. The animals were sacrificed 24 h after injection,
and their tumor, heart, spleen, liver, kidneys and plasma were
separated and homogenized. The drug content in their tumor, heart,
spleen, liver, kidneys and plasma was determined using tissue
fluorimetry. The results show that in the group that received micellar
doxorubicin with sonication, the drug concentration in the tumor
tissue was nine and three times higher than in the free doxorubicin
group and the micellar doxorubicin without sonication group,
respectively. In the micellar doxorubicin with sonication group, the
drug concentration in other tissues was lower than other groups
(p
Abstract: Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.
Abstract: with increasing circuits- complexity and demand to
use portable devices, power consumption is one of the most
important parameters these days. Full adders are the basic block of
many circuits. Therefore reducing power consumption in full adders
is very important in low power circuits. One of the most powerconsuming
modules in full adders is XOR/XNOR circuit. This paper
presents two new full adders based on two new logic approaches. The
proposed logic approaches use one XOR or XNOR gate to implement
a full adder cell. Therefore, delay and power will be decreased. Using
two new approaches and two XOR and XNOR gates, two new full
adders have been implemented in this paper. Simulations are carried
out by HSPICE in 0.18μm bulk technology with 1.8V supply voltage.
The results show that the ten-transistors proposed full adder has 12%
less power consumption and is 5% faster in comparison to MB12T
full adder. 9T is more efficient in area and is 24% better than similar
10T full adder in term of power consumption. The main drawback of
the proposed circuits is output threshold loss problem.
Abstract: This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: We consider a two-way relay network where two sources exchange information. A relay helps the two sources exchange information using the decode-and-XOR-forward protocol. We investigate the power minimization problem with minimum rate constraints. The system needs two time slots and in each time slot the required rate pair should be achievable. The power consumption is minimized in each time slot and we obtained the closed form solution. The simulation results confirm that the proposed power allocation scheme consumes lower total power than the conventional schemes.
Abstract: pH-sensitive drug targeting using nanoparticles for
cancer chemotherapy have been spotlighted in recent decades. Graft
copolymer composed of poly (L-histidine) (PHS) and dextran
(DexPHS) was synthesized and pH-sensitive nanoparticles were
fabricated for pH-responsive drug delivery of doxorubicin (DOX).
Nanoparticles of DexPHS showed pH-sensitive changes in particle
sizes and drug release behavior, i.e. particle sizes and drug release rate
were increased at acidic pH, indicating that DexPHS nanoparticles
have pH-sensitive drug delivery potentials. Antitumor activity of
DOX-incorporated DexPHS nanoparticles were studied using CT26
colorectal carcinoma cells. Results indicated that fluorescence
intensity was higher at acidic pH than basic pH. These results
indicated that DexPHS nanoparticles have pH-responsive drug
targeting.
Abstract: Since hyaluronic acid (HA) receptor such as CD44 is
over-expressed at sites of cancer cells, HA can be used as a targeting
vehicles for anti-cancer drugs. The aim of this study is to synthesize
block copolymer composed of hyaluronic acid and
poly(ε-caprolactone) (HAPCL) and to fabricate polymeric micelles for
anticancer drug targeting against CD44 receptor of tumor cells.
Chemical composition of HAPCL was confirmed using 1H NMR
spectroscopy. Doxorubicin (DOX) was incorporated into polymeric
micelles of HAPCL. The diameters of HAPHS polymeric micelles
were changed around 80nm and have spherical shapes. Targeting
potential was investigated using CD44-overexpressing. When
DOX-incorporated polymeric micelles was added to KB cells, they
revealed strong red fluorescence color while blocking of CD44
receptor by pretreatment of free HA resulted in reduced intensity,
indicating that HAPCL polymeric micelles have targetability against
CD44 receptor.
Abstract: The paper proposes the novel design of a 3T XOR gate combining complementary CMOS with pass transistor logic. The design has been compared with earlier proposed 4T and 6T XOR gates and a significant improvement in silicon area and power-delay product has been obtained. An eight transistor full adder has been designed using the proposed three-transistor XOR gate and its performance has been investigated using 0.15um and 0.35um technologies. Compared to the earlier designed 10 transistor full adder, the proposed adder shows a significant improvement in silicon area and power delay product. The whole simulation has been carried out using HSPICE.
Abstract: The back propagation algorithm calculates the weight
changes of artificial neural networks, and a common approach is to
use a training algorithm consisting of a learning rate and a
momentum factor. The major drawbacks of above learning algorithm
are the problems of local minima and slow convergence speeds. The
addition of an extra term, called a proportional factor reduces the
convergence of the back propagation algorithm. We have applied the
three term back propagation to multiplicative neural network
learning. The algorithm is tested on XOR and parity problem and
compared with the standard back propagation training algorithm.
Abstract: In this paper, we consider the problem of logic simplification for a special class of logic functions, namely complementary Boolean functions (CBF), targeting low power implementation using static CMOS logic style. The functions are uniquely characterized by the presence of terms, where for a canonical binary 2-tuple, D(mj) ∪ D(mk) = { } and therefore, we have | D(mj) ∪ D(mk) | = 0 [19]. Similarly, D(Mj) ∪ D(Mk) = { } and hence | D(Mj) ∪ D(Mk) | = 0. Here, 'mk' and 'Mk' represent a minterm and maxterm respectively. We compare the circuits minimized with our proposed method with those corresponding to factored Reed-Muller (f-RM) form, factored Pseudo Kronecker Reed-Muller (f-PKRM) form, and factored Generalized Reed-Muller (f-GRM) form. We have opted for algebraic factorization of the Reed-Muller (RM) form and its different variants, using the factorization rules of [1], as it is simple and requires much less CPU execution time compared to Boolean factorization operations. This technique has enabled us to greatly reduce the literal count as well as the gate count needed for such RM realizations, which are generally prone to consuming more cells and subsequently more power consumption. However, this leads to a drawback in terms of the design-for-test attribute associated with the various RM forms. Though we still preserve the definition of those forms viz. realizing such functionality with only select types of logic gates (AND gate and XOR gate), the structural integrity of the logic levels is not preserved. This would consequently alter the testability properties of such circuits i.e. it may increase/decrease/maintain the same number of test input vectors needed for their exhaustive testability, subsequently affecting their generalized test vector computation. We do not consider the issue of design-for-testability here, but, instead focus on the power consumption of the final logic implementation, after realization with a conventional CMOS process technology (0.35 micron TSMC process). The quality of the resulting circuits evaluated on the basis of an established cost metric viz., power consumption, demonstrate average savings by 26.79% for the samples considered in this work, besides reduction in number of gates and input literals by 39.66% and 12.98% respectively, in comparison with other factored RM forms.
Abstract: This study determines the effect of naked and heparinbased
super-paramagnetic iron oxide nanoparticles on the human
cancer cell lines of A2780. Doxorubicin was used as the anticancer
drug, entrapped in the SPIO-NPs. This study aimed to decorate
nanoparticles with heparin, a molecular ligand for 'active' targeting
of cancerous cells and the application of modified-nanoparticles in
cancer treatment. The nanoparticles containing the anticancer drug
DOX were prepared by a solvent evaporation and emulsification
cross-linking method. The physicochemical properties of the
nanoparticles were characterized by various techniques, and uniform
nanoparticles with an average particle size of 110±15 nm with high
encapsulation efficiencies (EE) were obtained. Additionally, a
sustained release of DOX from the SPIO-NPs was successful.
Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell
toxicity than the individual HP and confocal microscopy analysis
confirmed excellent cellular uptake efficiency. These results indicate
that HP based SPIO-NPs have potential uses as anticancer drug
carriers and also have an enhanced anticancer effect.