Abstract: Recently, there has been a considerable increase in the
number of procedures carried out under regional anesthesia.
However, percutaneous nephrolithotomy (PCNL) procedures are
usually performed under general anesthesia. The aim of this study
was to assess the safety and efficacy of PCNL under spinal anesthesia
in patients with renal calculi. We describe our 9 years experience of
performing PCNL under spinal anesthesia for 387 patients with large
stones of the upper urinary tract, with regard to the effectiveness and
side effects. All patients received spinal anesthetics (Lidocain 5%, or
Bupivacaine 0.75%) and underwent PCNL in prone position. The
success rate was 94.1%. The incidence of complications was 11.6%.
PCNL under spinal anesthesia is feasible, safe, and well-tolerated in
management of patients with renal stones.
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: In the present study, the effect of ferrous sulfate concentration and total solids on bioleaching of heavy metals from sewage sludge has been examined using indigenous iron-oxidizing microorganisms. The experiments on effects of ferrous sulfate concentrations on bioleaching were carried out using ferrous sulfate of different concentrations (5-20 g L-1) to optimize the concentration of ferrous sulfate for maximum bioleaching. A rapid change in the pH and ORP took place in first 2 days followed by a slow change till 16th day in all the sludge samples. A 10 g L-1 ferrous sulfate concentration was found to be sufficient in metal bioleaching in the following order: Zn: 69%>Cu: 52%>Cr: 46%>Ni: 45. Further, bioleaching using 10 g/L ferrous sulfate was found to be efficient up to 20 g L-1 sludge solids concentration. The results of the present study strongly indicate that using 10 g L-1 ferrous sulfate indigenous iron-oxidizing microorganisms can bring down pH to a value needed for significant metal solubilization.
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: In the paper the results of calculations of the dynamic
response of a multi-storey reinforced concrete building to a strong
mining shock originated from the main region of mining activity in
Poland (i.e. the Legnica-Glogow Copper District) are presented. The
representative time histories of accelerations registered in three
directions were used as ground motion data in calculations of the
dynamic response of the structure. Two variants of a numerical model
were applied: the model including only structural elements of the
building and the model including both structural and non-structural
elements (i.e. partition walls and ventilation ducts made of brick). It
turned out that non-structural elements of multi-storey RC buildings
have a small impact of about 10 % on natural frequencies of these
structures. It was also proved that the dynamic response of building
to mining shock obtained in case of inclusion of all non-structural
elements in the numerical model is about 20 % smaller than in case
of consideration of structural elements only. The principal stresses
obtained in calculations of dynamic response of multi-storey building
to strong mining shock are situated on the level of about 30% of
values obtained from static analysis (dead load).
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 objective from this paper is to design a solar
thermal engine for space vehicles orbital control and electricity
generation. A computational model is developed for the prediction of
the solar thermal engine performance for different design parameters and conditions in order to enhance the engine efficiency. The engine is divided into two main subsystems. First, the concentrator dish
which receives solar energy from the sun and reflects them to the
cavity receiver. The second one is the cavity receiver which receives
the heat flux reflected from the concentrator and transfers heat to the
fluid passing over. Other subsystems depend on the application required from the engine. For thrust application, a nozzle is
introduced to the system for the fluid to expand and produce thrust.
Hydrogen is preferred as a working fluid in the thruster application.
Results model developed is used to determine the thrust for a
concentrator dish 4 meters in diameter (provides 10 kW of energy),
focusing solar energy to a 10 cm aperture diameter cavity receiver.
The cavity receiver outer length is 50 cm and the internal cavity is 47
cm in length. The suggested design material of the internal cavity is
tungsten to withstand high temperature. The thermal model and
analysis shows that the hydrogen temperature at the plenum reaches
2000oK after about 250 seconds for hot start operation for a flow rate
of 0.1 g/sec.Using solar thermal engine as an electricity generation
device on earth is also discussed. In this case a compressor and
turbine are used to convert the heat gained by the working fluid (air)
into mechanical power. This mechanical power can be converted into
electrical power by using a generator.
Abstract: This study shows palynomorphological description of
pollen grains of Lamium garganicum, species of the family Labiatae.
Fresh material of this plant is taken in Mount Llogara, in Albania. By
comparison made between palinomorphological characteristics of
pollen grains of Lamium garganicum with those of Lamium
maculatum and Lamium purpureum, showed that granules have
similarities in the number of furrows. The pollen grains of Lamium
garganicum were larger in length and width than those of Lamium
maculatum and almost equal with those of Lamium purpureum.
Furrows are longer than those of pollen grains in Lamium maculatum
and shorter than those of Lamium purpureum. The layer of exine of
Lamium garganicum was thinner than that of two others. The
sculpture of exine was fine reticulate, where reticulas were uniform
whereas in Lamium purpureum was verrucate, with small verrucae; in
Lamium maculatum was reticulate.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
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: Cement, the most widely used construction material
is very brittle and characterized by low tensile strength and strain
capacity. Macro to nano fibers are added to cement to provide
tensile strength and ductility to it. Carbon Nanotube (CNT), one of
the nanofibers, has proven to be a promising reinforcing material in
the cement composites because of its outstanding mechanical
properties and its ability to close cracks at the nano level. The
experimental investigations for CNT reinforced cement is costly,
time consuming and involves huge number of trials. Mathematical
modeling of CNT reinforced cement can be done effectively and
efficiently to arrive at the mechanical properties and to reduce the
number of trials in the experiments. Hence, an attempt is made to
numerically study the effective mechanical properties of CNT
reinforced cement numerically using Representative Volume
Element (RVE) method. The enhancement in its mechanical
properties for different percentage of CNTs is studied in detail.
Abstract: In this work, we obtain some analytic solutions for the (3+1)-dimensional breaking soliton after obtaining its Hirota-s bilinear form. Our calculations show that, three-wave method is very easy and straightforward to solve nonlinear partial differential equations.
Abstract: A new OTA-based logarithmic-control variable gain
current amplifier (LCCA) is presented. It consists of two Operational
Transconductance Amplifier (OTA) and two PMOS transistors
biased in weak inversion region. The circuit operates from 0.6V DC
power supply and consumes 0.6 μW. The linear-dB controllable
output range is 43 dB with maximum error less than 0.5dB. The
functionality of the proposed design was confirmed using HSPICE in
0.35μm CMOS process technology.
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: Many natural language expressions are ambiguous, and
need to draw on other sources of information to be interpreted.
Interpretation of the e word تعاون to be considered as a noun or a verb
depends on the presence of contextual cues. To interpret words we
need to be able to discriminate between different usages. This paper
proposes a hybrid of based- rules and a machine learning method for
tagging Arabic words. The particularity of Arabic word that may be
composed of stem, plus affixes and clitics, a small number of rules
dominate the performance (affixes include inflexional markers for
tense, gender and number/ clitics include some prepositions,
conjunctions and others). Tagging is closely related to the notion of
word class used in syntax. This method is based firstly on rules (that
considered the post-position, ending of a word, and patterns), and
then the anomaly are corrected by adopting a memory-based learning
method (MBL). The memory_based learning is an efficient method to
integrate various sources of information, and handling exceptional
data in natural language processing tasks. Secondly checking the
exceptional cases of rules and more information is made available to
the learner for treating those exceptional cases. To evaluate the
proposed method a number of experiments has been run, and in
order, to improve the importance of the various information in
learning.
Abstract: Quantitative trait loci (QTL) experiments have yielded
important biological and biochemical information necessary for
understanding the relationship between genetic markers and
quantitative traits. For many years, most QTL algorithms only
allowed one observation per genotype. Recently, there has been an
increasing demand for QTL algorithms that can accommodate more
than one observation per genotypic distribution. The Bayesian
hierarchical model is very flexible and can easily incorporate this
information into the model. Herein a methodology is presented that
uses a Bayesian hierarchical model to capture the complexity of the
data. Furthermore, the Markov chain Monte Carlo model composition
(MC3) algorithm is used to search and identify important markers. An
extensive simulation study illustrates that the method captures the
true QTL, even under nonnormal noise and up to 6 QTL.
Abstract: The overall objective of this research is a strain
improvement technology for efficient pectinase production. A novel
cells cultivation technology by immobilization of fungal cells has
been studied in long time continuous fermentations. Immobilization
was achieved by using of new material for absorption of stores of
immobilized cultures which was for the first time used for
immobilization of microorganisms. Effects of various conditions of
nitrogen and carbon nutrition on the biosynthesis of pectolytic
enzymes in Aspergillus awamori 1-8 strain were studied. Proposed
cultivation technology along with optimization of media components
for pectinase overproduction led to increased pectinase productivity
in Aspergillus awamori 1-8 from 7 to 8 times. Proposed technology
can be applied successfully for production of major industrial
enzymes such as α-amylase, protease, collagenase etc.