Abstract: Yield and Crop Water Productivity are crucial issues
in sustainable agriculture, especially in high-demand resource crops such as sweet corn. This study was conducted to investigate
agronomic responses such as plant growth, yield and soil parameters (EC and Nitrate accumulation) to several deficit irrigation treatments
(100, 75, 50, 25 and 0% of ETm) applied during vegetative growth
stage, rainfed treatment was also tested.
The finding of this research indicates that under deficit irrigation
during vegetative growth stage applying 75% of ETm lead to increasing of 19.4% in terms of fresh ear yield, 9.4% in terms of dry grain yield, 10.5% in terms of number of ears per plant, 11.5% for
the 1000 grains weight and 19% in terms of crop water productivity compared with fully irrigated treatment. While those parameters in
addition to root, shoot and plant height has been affected by deficit
irrigation during vegetative growth stage when increasing water stress degree more than 50% of ETm.
Abstract: Obesity is frequent attendant phenomenon of patients
with endocrinological disease. Between BMI and endocrinological
diseases is close correlation. In thesis we focused on the allocation of
hormone concentration – PTH and TSH, CHOL a mineral element Ca
in a blood serum. The examined group was formed by 100
respondents (women) aged 36 – 83 years, who were divided into two
groups – control group (CG), group with diagnosed endocrine disease
(DED). The concentration of PTH and TSH, Ca and CHOL was
measured through the medium of analyzers Cobas e411 (Japan);
Cobas Integra 400 (Switzerland). At individuals was measured body
weight as well as stature and thereupon from those data we
enumerated BMI. On the basis of Student T-test in biochemical
parameter of PTH and Ca we found out significantly meaningful
difference (p
Abstract: Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.
Abstract: Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.
Abstract: With the development of the Polyvinyl chloride
(PVC) products in many applications, the challenge of investigating
the raw material composition and reducing the cost have both
become more and more important. Considerable research has been
done investigating the effect of additives on the PVC products. Most
of the PVC composites research investigates only the effect of
single/few factors, at a time. This isolated consideration of the input
factors does not take in consideration the interaction effect of the
different factors. This paper implements a mixture experimental
design approach to find out a cost-effective PVC composition for the
production of electrical-insulation cables considering the ASTM
Designation (D) 6096. The results analysis showed that a minimum
cost can be achieved through using 20% virgin PVC, 18.75%
recycled PVC, 43.75% CaCO3 with participle size 10 microns, 14%
DOP plasticizer, and 3.5% CPW plasticizer. For maximum UTS the
compound should consist of: 17.5% DOP, 62.5% virgin PVC, and
20.0% CaCO3 of particle size 5 microns. Finally, for the highest
ductility the compound should be made of 35% virgin PVC, 20%
CaCO3 of particle size 5 microns, and 45.0% DOP plasticizer.
Abstract: The theoretical investigation is carried out to describe
the effect of increase of pressure waves amplitude in clean and bubbly liquid. The goal of the work is to capture the regime of multiple magnification of acoustic and shock waves in the liquid,
which enables to get appropriate conditions to enlarge collapses of
micro-bubbles. The influence of boundary conditions and frequency
of the governing acoustic field is studied for the case of the
cylindrical acoustic resonator. It has been observed the formation of
standing waves with large amplitude at resonant frequencies. The
interaction of the compression wave with gas and vapor bubbles is
investigated for the convergent channel. It is shown theoretically that
the chemical reactions, which occur inside gas bubbles, provide additional impulse to the wave, that affect strongly on the collapses
of the vapor bubbles
Abstract: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.
Abstract: Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.
Abstract: This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.
Abstract: In this study, an experimental investigation was carried
out to fix CO2 into the electronic arc furnace (EAF) reducing slag from
stainless steelmaking process under wet grinding. The slag was ground
by the vibrating ball mill with the CO2 and pure water. The reaction
behavior was monitored with constant pressure method, and the
change of CO2 volume in the experimental system with grinding time
was measured. It was found that the CO2 absorption occurred as soon
as the grinding started. The CO2 absorption under wet grinding was
significantly larger than that under dry grinding. Generally, the
amount of CO2 absorption increased as the amount of water, the
amount of slag, the diameter of alumina ball and the initial pressure of
CO2 increased. However, the initial absorption rate was scarcely
influenced by the experimental conditions except for the initial CO2
pressure. According to this research, the CO2 reacted with the CaO
inside the slag to form CaCO3.
Abstract: The majority of existing predictors for time series are
model-dependent and therefore require some prior knowledge for the
identification of complex systems, usually involving system
identification, extensive training, or online adaptation in the case of
time-varying systems. Additionally, since a time series is usually
generated by complex processes such as the stock market or other
chaotic systems, identification, modeling or the online updating of
parameters can be problematic. In this paper a model-free predictor
(MFP) for a time series produced by an unknown nonlinear system or
process is derived using tracking theory. An identical derivation of the
MFP using the property of the Newton form of the interpolating
polynomial is also presented. The MFP is able to accurately predict
future values of a time series, is stable, has few tuning parameters and
is desirable for engineering applications due to its simplicity, fast
prediction speed and extremely low computational load. The
performance of the proposed MFP is demonstrated using the
prediction of the Dow Jones Industrial Average stock index.
Abstract: The aim of this article is to narrate the utility of novel simulation approach i.e. convolution method to predict blood concentration of drug utilizing dissolution data of salbutamol sulphate microparticulate formulations with different release patterns (1:1, 1:2 and 1:3, drug:polymer). Dissolution apparatus II USP 2007 and 900 ml double distilled water stirrd at 50 rpm was employed for dissolution analysis. From dissolution data, blood drug concentration was determined, and in return predicted blood drug concentration data was used to calculate the pharmacokinetic parameters i.e. Cmax, Tmax, and AUC. Convolution is a good biwaiver technique; however its better utility needs it application in the conditions where biorelevant dissolution media are used.
Abstract: Microbubbbles incorporating ultrasound have been used to increase the efficacy of targeted drug delivery, because microstreaming induced by cavitating bubbles affects the drug perfusion into the target cells and tissues. In order to clarify the physical effects of microstreaming on drug perfusion into tissues, a preliminary experimental study of perfusion enhancement by a stably oscillating microbubble was performed. Microstreaming was induced by an oscillating bubble at 15 kHz, and perfusion of dye into an agar phantom was optically measured by histology on agar phantom. Surface color intensity and the penetration length of dye in the agar phantom were increased more than 70% and 30%, respectively, due to the microstreaming induced by an oscillating bubble. The mass of dye perfused into a tissue phantom for 30 s was increased about 80% in the phantom with an oscillating bubble. This preliminary experiment shows the physical effects of steady streaming by an oscillating bubble can enhance the drug perfusion into the tissues while minimizing the biological effects.
Abstract: The current speech interfaces in many military
applications may be adequate for native speakers. However,
the recognition rate drops quite a lot for non-native speakers
(people with foreign accents). This is mainly because the nonnative
speakers have large temporal and intra-phoneme
variations when they pronounce the same words. This
problem is also complicated by the presence of large
environmental noise such as tank noise, helicopter noise, etc.
In this paper, we proposed a novel continuous acoustic feature
adaptation algorithm for on-line accent and environmental
adaptation. Implemented by incremental singular value
decomposition (SVD), the algorithm captures local acoustic
variation and runs in real-time. This feature-based adaptation
method is then integrated with conventional model-based
maximum likelihood linear regression (MLLR) algorithm.
Extensive experiments have been performed on the NATO
non-native speech corpus with baseline acoustic model trained
on native American English. The proposed feature-based
adaptation algorithm improved the average recognition
accuracy by 15%, while the MLLR model based adaptation
achieved 11% improvement. The corresponding word error
rate (WER) reduction was 25.8% and 2.73%, as compared to
that without adaptation. The combined adaptation achieved
overall recognition accuracy improvement of 29.5%, and
WER reduction of 31.8%, as compared to that without
adaptation.
Abstract: Pharmacology curriculum plays an integral role in
medical education. Learning pharmacology to choose and prescribe
drugs is a major challenge encountered by students. We developed
pharmacology applied learning activities for first year medical
students that included realistic clinical situations with escalating
complications which required the students to analyze the situation
and think critically to choose a safe drug. Tutor feedback was
provided at the end of session. Evaluation was done to assess the
students- level of interest and usefulness of the sessions in rational
selection of drugs. Majority (98 %) of the students agreed that the
session was an extremely useful learning exercise and agreed that
similar sessions would help in rational selection of drugs. Applied
learning sessions in the early years of medical program may promote
deep learning and bridge the gap between pharmacology theory and
clinical practice. Besides, it may also enhance safe prescribing skills.
Abstract: In intensity modulated radiation therapy (IMRT)
treatment planning, beam angles are usually preselected on the basis of
experience and intuition. Therefore, getting an appropriate beam
configuration needs a very long time. Based on the present situation,
the paper puts forward beam orientation optimization using ant colony
optimization (ACO). We use ant colony optimization to select the
beam configurations, after getting the beam configuration using
Conjugate Gradient (CG) algorithm to optimize the intensity profiles.
Combining with the information of the effect of pencil beam, we can
get the global optimal solution accelerating. In order to verify the
feasibility of the presented method, a simulated and clinical case was
tested, compared with dose-volume histogram and isodose line
between target area and organ at risk. The results showed that the
effect was improved after optimizing beam configurations. The
optimization approach could make treatment planning meet clinical
requirements more efficiently, so it had extensive application
perspective.
Abstract: Carbon tetrachloride (CCl4) is a well-known
hepatotoxin and exposure to this chemical is known to induce
oxidative stress and causes liver injury by the formation of free
radicals. Flacourtia indica commonly known as 'Baichi' has been
reported as an effective remedy for the treatment of a variety of
diseases. The objective of this study was to investigate the
hepatoprotective activity of aqueous extract of leaves of Flacourtia
indica against CCl4 induced hepatotoxicity. Animals were pretreated
with the aqueous extract of Flacourtia indica (250 & 500 mg/kg
body weight) for one week and then challenged with CCl4 (1.5 ml/kg
bw) in olive oil (1:1, v/v) on 7th day. Serum marker enzymes (ALP,
AST, ALT, Total Protein & Total Bilirubin) and TBARS level
(Marker for oxidative stress) were estimated in all the study groups.
Alteration in the levels of biochemical markers of hepatic damage
like AST, ALT, ALP, Total Protein, Total Bilirubin and lipid
peroxides (TBARS) were tested in both CCl4 treated and extract
treated groups. CCl4 has enhanced the AST, ALT, ALP and the
Lipid peroxides (TBARS) in liver. Treatment of aqueous extract of
Flacourtia indica leaves (250 & 500 mg/kg) exhibited a significant
protective effect by altering the serum levels of AST, ALT, ALP,
Total Protein, Total Bilirubin and liver TBARS. These biochemical
observations were supported by histopathological study of liver
sections. From this preliminary study it has been concluded that the
aqueous extract of the leaves of Flacourtia indica protects liver
against oxidative damages and could be used as an effective protector
against CCl4 induced hepatic damage. Our findings suggested that
Flacourtia indica possessed good hepatoprotective activity
Abstract: Dust acoustic solitary waves are studied in warm
dusty plasma containing negatively charged dusts, nonthermal ions
and Boltzmann distributed electrons. Sagdeev pseudopotential
method is used in order to investigate solitary wave solutions in the
plasmas. The existence of compressive and rarefractive solitons is
studied.
Abstract: A mathematical model of the respiratory system is
introduced in this study. Geometrical dimensions of the respiratory
system were used to compute the acoustic properties of the
respiratory system using the electro-acoustic analogy. The effect of
the geometrical proportions of the respiratory system is observed in
the paper.
Abstract: In this paper we present a general formalism for the
establishment of the family of selective regressor affine projection
algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA),
the SR partial rank algorithm (SR-PRA), the SR binormalized
data reusing least mean squares (SR-BNDR-LMS), and the SR normalized
LMS with orthogonal correction factors (SR-NLMS-OCF)
algorithms are established by this general formalism. We demonstrate
the performance of the presented algorithms through simulations in
acoustic echo cancellation scenario.