Abstract: COPD is characterized by loss of elastic fibers from
small airways and alveolar walls, with the decrease in elastin
increasing with disease severity. It is unclear why there is a lack of
repair of elastic fibers. We have examined fibroblasts cultured from
lung tissue from normal and COPD subjects to determine if the
secretory profile explains lack of tissue repair. In this study,
fibroblasts were cultured from lung parenchyma of bronchial
carcinoma patients with varying degrees of COPD; controls
(non-COPD, n=5), mild COPD (GOLD 1, n=5) and moderate-severe
COPD (GOLD 2-3, n=12). Measurements were made of proliferation,
senescence-associated beta-galactosidase-1, mRNA expression of
IL-6, IL-8, MMP-1, tropoelastin and versican, and protein levels for
IL-6, IL-8, PGE2, tropoelastin, insoluble elastin, and versican. It was
found that GOLD 2-3 fibroblasts proliferated more slowly (p
Abstract: This paper presents a part of research on the
rheological properties of bitumen modified by thermoplastic namely
linear low density polyethylene (LLDPE), high density polyethylene
(HDPE) and polypropylene (PP) and its interaction with 80 pen base
bitumen. As it is known that the modification of bitumen by the use
of polymers enhances its performance characteristics but at the same
time significantly alters its rheological properties. The rheological
study of polymer modified bitumen (PMB) was made through
penetration, ring & ball softening point and viscosity test. The results
were then related to the changes in the rheological properties of
polymer modified bitumen. It was observed that thermoplastic
copolymer shows profound effect on penetration rather than
softening point. The viscoelastic behavior of polymer modified
bitumen depend on the concentration of polymer, mixing
temperature, mixing technique, solvating power of base bitumen and
molecular structure of polymer used. PP offer better blend in
comparison to HDPE and LLDPE. The viscosity of base bitumen was
also enhanced with the addition of polymer. The pseudoplastic
behavior was more prominent for HDPE and LLDPE than PP. Best
results were obtained when polymer concentration was kept below
3%
Abstract: In this paper, a predator-prey model with time delay and habitat complexity is investigated. By analyzing the characteristic equations, the local stability of each feasible equilibria of the system is discussed and the existence of a Hopf bifurcation at the coexistence equilibrium is established. By choosing the sum of two delays as a bifurcation parameter, we show that Hopf bifurcations can occur as crosses some critical values. By deriving the equation describing the flow on the center manifold, we can determine the direction of the Hopf bifurcations and the stability of the bifurcating periodic solutions. Numerical simulations are carried out to illustrate the main theoretical results.
Abstract: Decision Feedback equalizers (DFEs) usually outperform linear equalizers for channels with intersymbol interference. However, the DFE performance is highly dependent on the availability of reliable past decisions. Hence, in coded systems, where reliable decisions are only available after decoding the full block, the performance of the DFE will be affected. A symbol based DFE is a DFE that only uses the decision after the block is decoded. In this paper we derive the optimal settings of both the feedforward and feedback taps of the symbol based equalizer. We present a novel symbol based DFE filterbank, and derive its taps optimal settings. We also show that it outperforms the classic DFE in terms of complexity and/or performance.
Abstract: In this article we explore how computer assisted exercises may allow for bridging the traditional gap between theory and practice in professional education. To educate officers able to master the complexity of the battlefield the Norwegian Military Academy needs to develop a learning environment that allows for creating viable connections between the educational environment and the field of practice. In response to this challenge we explore the conditions necessary to make computer assisted training systems (CATS) a useful tool to create structural similarities between an educational context and the field of military practice. Although, CATS may facilitate work procedures close to real life situations, this case do demonstrate how professional competence also must build on viable learning theories and environments. This paper explores the conditions that allow for using simulators to facilitate professional competence from within an educational setting. We develop a generic didactic model that ascribes learning to participation in iterative cycles of action and reflection. The development of this model is motivated by the need to develop an interdisciplinary professional education rooted in the pattern of military practice.
Abstract: Abdominal aortic aneurysms rupture (AAAs) is one of the main causes of death in the world. This is a very complex phenomenon that usually occurs “without previous warning". Currently, criteria to assess the aneurysm rupture risk (peak diameter and growth rate) can not be considered as reliable indicators. In a first approach, the main geometric parameters of aneurysms have been linked into five biomechanical factors. These are combined to obtain a dimensionless rupture risk index, RI(t), which has been validated preliminarily with a clinical case and others from literature. This quantitative indicator is easy to understand, it allows estimating the aneurysms rupture risks and it is expected to be able to identify the one in aneurysm whose peak diameter is less than the threshold value. Based on initial results, a broader study has begun with twelve patients from the Clinic Hospital of Valladolid-Spain, which are submitted to periodic follow-up examinations.
Abstract: The substrate heater designed for this investigation is a front side substrate heating system. It consists of 10 conventional tungsten halogen lamps and an aluminum reflector, total input electrical power of 5 kW. The substrate is heated by means of a radiation from conventional tungsten halogen lamps directed to the substrate through a glass window. This design allows easy replacement of the lamps and maintenance of the system. Within 2 to 6 minutes the substrate temperature reaches 500 to 830 C by varying the vertical distance between the glass window and the substrate holder. Moreover, the substrate temperature can be easily controlled by controlling the input power to the system. This design gives excellent opportunity to deposit many deferent films at deferent temperatures in the same deposition time. This substrate heater was successfully used for Chemical Vapor Deposition (CVD) of many thin films, such as Silicon, iron, etc.
Abstract: We prove detailed analysis of a waveguide-based Schottky barrier photodetector (SBPD) where a thin silicide film is put on the top of a silicon-on-insulator (SOI) channel waveguide to absorb light propagating along the waveguide. Taking both the confinement factor of light absorption and the wall scanning induced gain of the photoexcited carriers into account, an optimized silicide thickness is extracted to maximize the effective gain, thereby the responsivity. For typical lengths of the thin silicide film (10-20 Ðçm), the optimized thickness is estimated to be in the range of 1-2 nm, and only about 50-80% light power is absorbed to reach the maximum responsivity. Resonant waveguide-based SBPDs are proposed, which consist of a microloop, microdisc, or microring waveguide structure to allow light multiply propagating along the circular Si waveguide beneath the thin silicide film. Simulation results suggest that such resonant waveguide-based SBPDs have much higher repsonsivity at the resonant wavelengths as compared to the straight waveguidebased detectors. Some experimental results about Si waveguide-based SBPD are also reported.
Abstract: The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.
Abstract: Fundamental sensor-motor couplings form the backbone
of most mobile robot control tasks, and often need to be implemented
fast, efficiently and nevertheless reliably. Machine learning
techniques are therefore often used to obtain the desired sensor-motor
competences.
In this paper we present an alternative to established machine
learning methods such as artificial neural networks, that is very fast,
easy to implement, and has the distinct advantage that it generates
transparent, analysable sensor-motor couplings: system identification
through nonlinear polynomial mapping.
This work, which is part of the RobotMODIC project at the
universities of Essex and Sheffield, aims to develop a theoretical understanding
of the interaction between the robot and its environment.
One of the purposes of this research is to enable the principled design
of robot control programs.
As a first step towards this aim we model the behaviour of the
robot, as this emerges from its interaction with the environment, with
the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving
Average models with eXogenous inputs). This method produces
explicit polynomial functions that can be subsequently analysed using
established mathematical methods.
In this paper we demonstrate the fidelity of the obtained NARMAX
models in the challenging task of robot route learning; we present a
set of experiments in which a Magellan Pro mobile robot was taught
to follow four different routes, always using the same mechanism to
obtain the required control law.
Abstract: Concerning the measurement of friction properties of
textiles and fabrics using Kawabata Evaluation System (KES), whose
output is constrained to the surface friction factor of fabric, and no
other data would be generated; this research has been conducted to
gain information about surface roughness regarding its surface
friction factor. To assess roughness properties of light nonwovens, a
3-dimensional model of a surface has been simulated with regular
sinuous waves through it as an ideal surface. A new factor was
defined, namely Surface Roughness Factor, through comparing
roughness properties of simulated surface and real specimens. The
relation between the proposed factor and friction factor of specimens
has been analyzed by regression, and results showed a meaningful
correlation between them. It can be inferred that the new presented
factor can be used as an acceptable criterion for evaluating the
roughness properties of light nonwoven fabrics.
Abstract: This paper proposes and analyses the wireless
telecommunication system with multiple antennas to the emission
and reception MIMO (multiple input multiple output) with space
diversity in a OFDM context. In particular it analyses the
performance of a DTT (Digital Terrestrial Television) broadcasting
system that includes MIMO-OFDM techniques. Different
propagation channel models and configurations are considered for
each diversity scheme. This study has been carried out in the context
of development of the next generation DVB-T/H and WRAN.
Abstract: Oxidative stress is considered to be the cause for onset
and the progression of type 2 diabetes mellitus (T2DM) and
complications including neuropathy. It is a deleterious process that
can be an important mediator of damage to cell structures: protein,
lipids and DNA. Data suggest that in patients with diabetes and
diabetic neuropathy DNA repair is impaired, which prevents effective
removal of lesions. Objective: The aim of our study was to evaluate
the association of the hOGG1 (326 Ser/Cys) and XRCC1 (194
Arg/Trp, 399 Arg/Gln) gene polymorphisms whose protein is
involved in the BER pathway with DNA repair efficiency in patients
with diabetes type 2 and diabetic neuropathy compared to the healthy
subjects. Genotypes were determined by PCR-RFLP analysis in 385
subjects, including 117 with type 2 diabetes, 56 with diabetic
neuropathy and 212 with normal glucose metabolism. The
polymorphisms studied include codon 326 of hOGG1 and 194, 399
of XRCC1 in the base excision repair (BER) genes. Comet assay was
carried out using peripheral blood lymphocytes from the patients and
controls. This test enabled the evaluation of DNA damage in cells
exposed to hydrogen peroxide alone and in the combination with the
endonuclease III (Nth). The results of the analysis of polymorphism
were statistically examination by calculating the odds ratio (OR) and
their 95% confidence intervals (95% CI) using the ¤ç2-tests. Our data
indicate that patients with diabetes mellitus type 2 (including those
with neuropathy) had higher frequencies of the XRCC1 399Arg/Gln
polymorphism in homozygote (GG) (OR: 1.85 [95% CI: 1.07-3.22],
P=0.3) and also increased frequency of 399Gln (G) allele (OR: 1.38
[95% CI: 1.03-1.83], P=0.3). No relation to other polymorphisms
with increased risk of diabetes or diabetic neuropathy. In T2DM
patients complicated by neuropathy, there was less efficient repair of
oxidative DNA damage induced by hydrogen peroxide in both the
presence and absence of the Nth enzyme. The results of our study
suggest that the XRCC1 399 Arg/Gln polymorphism is a significant
risk factor of T2DM in Polish population. Obtained data suggest a
decreased efficiency of DNA repair in cells from patients with
diabetes and neuropathy may be associated with oxidative stress.
Additionally, patients with neuropathy are characterized by even
greater sensitivity to oxidative damage than patients with diabetes,
which suggests participation of free radicals in the pathogenesis of
neuropathy.
Abstract: In this paper, image compression using hybrid vector
quantization scheme such as Multistage Vector Quantization
(MSVQ) and Pyramid Vector Quantization (PVQ) are introduced. A
combined MSVQ and PVQ are utilized to take advantages provided
by both of them. In the wavelet decomposition of the image, most of
the information often resides in the lowest frequency subband.
MSVQ is applied to significant low frequency coefficients. PVQ is
utilized to quantize the coefficients of other high frequency
subbands. The wavelet coefficients are derived using lifting scheme.
The main aim of the proposed scheme is to achieve high compression
ratio without much compromise in the image quality. The results are
compared with the existing image compression scheme using MSVQ.
Abstract: The segmentation of mouth and lips is a fundamental
problem in facial image analyisis. In this paper we propose a method
for lip segmentation based on rg-color histogram. Statistical analysis
shows, using the rg-color-space is optimal for this purpose of a pure
color based segmentation. Initially a rough adaptive threshold selects
a histogram region, that assures that all pixels in that region are
skin pixels. Based on that pixels we build a gaussian model which
represents the skin pixels distribution and is utilized to obtain a
refined, optimal threshold. We are not incorporating shape or edge
information. In experiments we show the performance of our lip pixel
segmentation method compared to the ground truth of our dataset and
a conventional watershed algorithm.
Abstract: Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.
Abstract: Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.
Abstract: In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.
Abstract: Restoration research has become important on principle recently in Czech Republic. The reason is simple. More than 70 % of mined brown coal comes from the North Bohemian Basin these days. Open cast brown coal mining has lead to large damage on the landscape. Reclamation of phytotoxic areas is one of the serious problems in the North Bohemian Basin. It mainly concerns the areas with the occurrence of overburden rocks from the coal bed enriched with coal. The presented paper includes the characteristics of the important phytotoxic areas and the methodology of their reclamation. The results are documented with the long term monitoring of physical, mineralogical, chemical and pedological parameters of rocks in the testing areas.
Abstract: Knowledge bases are basic components of expert
systems or intelligent computational programs. Knowledge bases
provide knowledge, events that serve deduction activity,
computation and control. Therefore, researching and developing of
models for knowledge representation play an important role in
computer science, especially in Artificial Intelligence Science and
intelligent educational software. In this paper, the extensive
deduction computational model is proposed to design knowledge
bases whose attributes are able to be real values or functional values.
The system can also solve problems based on knowledge bases.
Moreover, the models and algorithms are applied to produce the
educational software for solving alternating current problems or
solving set of equations automatically.