Abstract: Water 2H NMR signal on the surface of nano-silica material, MCM-41, consists of two overlapping resonances. The 2H water spectrum shows a superposition of a Lorentzian line shape and the familiar NMR powder pattern line shape, indicating the existence of two spin components. Chemical exchange occurs between these two groups. Decomposition of the two signals is a crucial starting point for study the exchange process. In this article we have determined these spin component populations along with other important parameters for the 2H water NMR signal over a temperature range between 223 K and 343 K.
Abstract: High level and high velocity flood flows are
potentially harmful to bridge piers as evidenced in many toppled
piers, and among them the single-column piers were considered as
the most vulnerable. The flood flow characteristic parameters
including drag coefficient, scouring and vortex shedding are built into
a pier-flood interaction model to investigate structural safety against
flood hazards considering the effects of local scouring, hydrodynamic
forces, and vortex induced resonance vibrations. By extracting the
pier-flood simulation results embedded in a neural networks code,
two cases of pier toppling occurred in typhoon days were reexamined:
(1) a bridge overcome by flash flood near a mountain side;
(2) a bridge washed off in flood across a wide channel near the
estuary. The modeling procedures and simulations are capable of
identifying the probable causes for the tumbled bridge piers during
heavy floods, which include the excessive pier bending moments and
resonance in structural vibrations.
Abstract: The absolute Cu atoms density in Cu(2S1/22P1/2)
ground state has been measured by Resonance Optical Absorption
(ROA) technique in a DC magnetron sputtering deposition with
argon. We measured these densities under variety of operation
conditions: pressure from 0.6 μbar to 14 μbar, input power from
10W to 200W and N2 mixture from 0% to 100%. For measuring the
gas temperature, we used the simulation of N2 rotational spectra
with a special computer code. The absolute number density of Cu
atoms decreases with increasing the N2 percentage of buffer gas at
any conditions of this work. But the deposition rate, is not decreased
with the same manner. The deposition rate variation is very small
and in the limit of quartz balance measuring equipment accuracy. So
we conclude that decrease in the absolute number density of Cu
atoms in magnetron plasma has not a big effect on deposition rate,
because the diffusion of Cu atoms to the chamber volume and
deviation of Cu atoms from direct path (towards the substrate)
decreases with increasing of N2 percentage of buffer gas. This is
because of the lower mass of N2 atoms compared to the argon ones.
Abstract: In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.
Abstract: We discuss the signal detection through nonlinear
threshold systems. The detection performance is assessed by the
probability of error Per . We establish that: (1) when the signal is
complete suprathreshold, noise always degrades the signal detection
both in the single threshold system and in the parallel array of
threshold devices. (2) When the signal is a little subthreshold, noise
degrades signal detection in the single threshold system. But in the
parallel array, noise can improve signal detection, i.e., stochastic
resonance (SR) exists in the array. (3) When the signal is predominant
subthreshold, noise always can improve signal detection and SR
always exists not only in the single threshold system but also in the
parallel array. (4) Array can improve signal detection by raising the
number of threshold devices. These results extend further the
applicability of SR in signal detection.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a level-sets approach to delineating three-dimensional brain tumors. Then we introduce a compression plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: The use of Inverse Discrete Fourier Transform (IDFT) implemented in the form of Inverse Fourier Transform (IFFT) is one of the standard method of reconstructing Magnetic Resonance Imaging (MRI) from uniformly sampled K-space data. In this tutorial, three of the major problems associated with the use of IFFT in MRI reconstruction are highlighted. The tutorial also gives brief introduction to MRI physics; MRI system from instrumentation point of view; K-space signal and the process of IDFT and IFFT for One and two dimensional (1D and 2D) data.
Abstract: Dynamic shear test on simulated phantom can be used
to validate magnetic resonance elastography (MRE) measurements.
Phantom gel has been usually utilized for the cell culture of cartilage
and soft tissue and also been used for mechanical property
characterization using imaging systems. The viscoelastic property of
the phantom would be important for dynamic experiments and
analyses. In this study, An axisymmetric FE model is presented for
determining the dynamic shear behaviour of brain simulated phantom
using ABAQUS. The main objective of this study was to investigate
the effect of excitation frequencies and boundary conditions on shear
modulus and shear viscosity in viscoelastic media.
Abstract: Visual attention allows user to select the most relevant
information to ongoing behaviour. This paper presents a study on; i)
the performance of people measurements, ii) accurateness of people
measurement of the peaks that correspond to chemical quantities
from the Magnetic Resonance Spectroscopy (MRS) graphs and iii)
affects of people measurements to the algorithm-based diagnosis.
Participant-s eye-movement was recorded using eye-tracker tool
(Eyelink II). This experiment involves three participants for
examining 20 MRS graphs to estimate the peaks of chemical
quantities which indicate the abnormalities associated with
Cerebellar Tumours (CT). The status of each MRS is verified by
using decision algorithm. Analysis involves determination of
humans-s eye movement pattern in measuring the peak of
spectrograms, scan path and determining the relationship of
distributions of fixation durations with the accuracy of measurement.
In particular, the eye-tracking data revealed which aspects of the
spectrogram received more visual attention and in what order they
were viewed. This preliminary investigation provides a proof of
concept for use of the eye tracking technology as the basis for
expanded CT diagnosis.
Abstract: Cry j 1 is a causative substance of Japanese cedar
pollinosis, and it may deteriorate by Cry j 1 invasion to a lower
respiratory tract. We observed airborne particles containing Cry j 1 by
an immunofluorescence technique using a fluorescence microscope,
and we clarified that Cry j 1 exist as aggregates of airborne fine
particles (< 1.1 μm) in the urban atmosphere. Airborne Cry j 1 may
react with air pollutants and be denature to a substance deteriorated
Japanese cedar pollinosis. Therefore, we applied a sodium dodecyl
sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to evaluate a
Cry j 1 reacted with various air pollutants by liquid phase reaction,
and calculated kinetics constants of Cry j 1 extracted from pollens
collected in various sites and airborne fine particles containing Cry j
1 by using a surface plasmon resonance (SPR) method. As a result, it
is suggested that Cry j 1 may be denatured by air pollutants during
the transportation to the urban atmosphere.
Abstract: The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose to develop an approach for designing optimal RF pulses under theoretically any constraints. The new technique will pose the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function will be proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach will be verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results and compared to previous works in this field. The results show a significant improvement over conventional design techniques, select the best options and parameters for GA to get most improvement over the previous works, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.
Abstract: The compatibility of optical resonators with microfluidic systems may be relevant for chemical and biological applications. Here, a fluorescent-core microcavity (FCM) is investigated as a refractometric sensor for heavy oils. A high-index film of silicon quantum dots (QDs) was formed inside the capillary, supporting cylindrical fluorescence whispering gallery modes (WGMs). A set of standard refractive index oils was injected into a capillary, causing a shift of the WGM resonances toward longer wavelengths. A maximum sensitivity of 240 nm/RIU (refractive index unit) was found for a nominal oil index of 1.74. As well, a sensitivity of 22 nm/RIU was obtained for a lower index of 1.48, more typical of fuel hydrocarbons. Furthermore, the observed spectra and sensitivities were compared to theoretical predictions and reproduced via FDTD simulations, showing in general an excellent agreement. This work demonstrates the potential use of FCMs for oil sensing applications and the more generally for detecting liquid solutions with a high refractive index or high viscosity.
Abstract: A fundamental model consisting of charged particles
moving in free space exposed to alternating and direct current (ACDC)
electromagnetic fields is analyzed. Effects of charged particles
initial position and initial velocity to cyclotron resonance frequency
are observed. Strong effects are observed revealing that effects of
electric and magnetic fields on a charged particle in free space
varies with the initial conditions. This indicates the frequency where
maximum displacement occur can be changed. At this frequency
the amplitude of oscillation of the particle displacement becomes
unbounded.
Abstract: Ferroresonance is an electrical phenomenon in
nonlinear character, which frequently occurs in power system due to
transmission line faults and single or more-phase switching on the
lines as well as usage of the saturable transformers. In this study, the
ferroresonance phenomena are investigated under the modeling of the
West Anatolian Electric Power Network of 380 kV in Turkey. The
ferroresonance event is observed as a result of removing the loads at
the end of the lines. In this sense, two different cases are considered.
At first, the switching is applied at 2nd second and the ferroresonance
affects are observed between 2nd and 4th seconds in the voltage
variations of the phase-R. Hence the ferroresonance and nonferroresonance
parts of the overall data are compared with each
others using the Fourier transform techniques to show the
ferroresonance affects.
Abstract: In this paper, the direct AnsAz method is used for constructing the multi-wave solutions to the (2+1)-dimensional extension of the Korteweg de-Vries (shortly EKdV) equation. A new breather type of three-wave solutions including periodic breather type soliton solution, breather type of two-solitary solution are obtained. Some cases with specific values of the involved parameters are plotted for each of the three-wave solutions. Mechanical features of resonance interaction among the multi-wave are discussed. These results enrich the variety of the dynamics of higher-dimensional nonlinear wave field.
Abstract: Medical image modalities such as computed
tomography (CT), magnetic resonance imaging (MRI), ultrasound
(US), X-ray are adapted to diagnose disease. These modalities
provide flexible means of reviewing anatomical cross-sections and
physiological state in different parts of the human body. The raw
medical images have a huge file size and need large storage
requirements. So it should be such a way to reduce the size of those
image files to be valid for telemedicine applications. Thus the image
compression is a key factor to reduce the bit rate for transmission or
storage while maintaining an acceptable reproduction quality, but it is
natural to rise the question of how much an image can be compressed
and still preserve sufficient information for a given clinical
application. Many techniques for achieving data compression have
been introduced. In this study, three different MRI modalities which
are Brain, Spine and Knee have been compressed and reconstructed
using wavelet transform. Subjective and objective evaluation has
been done to investigate the clinical information quality of the
compressed images. For the objective evaluation, the results show
that the PSNR which indicates the quality of the reconstructed image
is ranging from (21.95 dB to 30.80 dB, 27.25 dB to 35.75 dB, and
26.93 dB to 34.93 dB) for Brain, Spine, and Knee respectively. For
the subjective evaluation test, the results show that the compression
ratio of 40:1 was acceptable for brain image, whereas for spine and
knee images 50:1 was acceptable.
Abstract: The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.
Abstract: Segmenting the lungs in medical images is a
challenging and important task for many applications. In particular,
automatic segmentation of lung cavities from multiple magnetic
resonance (MR) images is very useful for oncological applications
such as radiotherapy treatment planning. However, distinguishing of
the lung areas is not trivial due to largely changing lung shapes, low
contrast and poorly defined boundaries. In this paper, we address
lung segmentation problem from pulmonary magnetic resonance
images and propose an automated method based on a robust regionaided
geometric snake with a modified diffused region force into the
standard geometric model definition. The extra region force gives the
snake a global complementary view of the lung boundary
information within the image which along with the local gradient
flow, helps detect fuzzy boundaries. The proposed method has been
successful in segmenting the lungs in every slice of 30 magnetic
resonance images with 80 consecutive slices in each image. We
present results by comparing our automatic method to manually
segmented lung cavities provided by an expert radiologist and with
those of previous works, showing encouraging results and high
robustness of our approach.
Abstract: Presence of phytosterol compound in Durian seed
(Durio zibethinus) or known as King of fruits has been discovered
from screening work using reagent test. Further analysis work has
been carried out using mass spectrometer in order to support the
priliminary finding. Isolation and purification of the major
phytosterol has been carried out using an open column
chromatography. The separation was monitored using thin layer
chromatography (TLC). Major isolated compounds and purified
phytosterol were identified using mass spectrometer and nuclear
magnetic resonance (NMR). This novel finding could promote
utilization of durian seeds as a functional ingredient in food products
through production of standardized extract based on phytosterol
content.
Abstract: Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.