Paper Title, Authors, Abstract (Issue 1, Volume 2, 2008)

Pages

A In-vitro investigation of RBCs flow characteristics and hemodynamic feature through a microchannel with a micro-stenosis
Myungjin Kang, Ho Seong Ji, Kyung Chun Kim

Abstract: To investigate hemodynamic behavior and Red Blood Cells (RBCs) movement related with circulatory diseases, an in-vitro experiment was carried out using a high speed visualization technique. The high speed visualization system employed in this study was consisted of the high speed camera, inverted microscope, oil-immersion objective lens, and halogen light. To simulate blood vessel with circulatory diseases, PDMS microchannel with a sinusoidal throat of 80% severity was employed. To investigate the hemohynamic behavior and RBCs movement, blood flow with 5% hematocrit was supplied into the micro-stenosis channel. The flow characteristics and transport of RBCs through the micro-stenosis were investigated with varying flow rate. In diffusion, the RBCs show deformation, twisting, rolling motion and tumbling motion due to the flow choking characteristics at the stenotic throat region.
 

Stochastic Algorithms for Adaptive Lighting Control using Psycho-Physiological Features
Ovidiu Grigore, Inge Gavat, Marius Cotescu, Corina Grigore

Abstract: Light has a real important impact on our life, determining the circadian rhythm, the rhythm of our daily activity. Light is benefic for healthy people, but it can be also very helpful for treating disease or for enhancing the comfort and wellbeing. In the frame of our European project, ALADIN, light is intended to be a support for the elderly, in order to enhance their daily performance. The performance is appreciated by activity specific values of psycho-physiological features that can be modified by light. This paper will describe the signal processing techniques deployed for extracting useful features and the algorithms used for developing an adaptive light controller. Two algorithms were used to implement the light controller: Monte Carlo and Simulated Annealing. Experimental results obtained using the Simulated Annealing algorithm will be presented.
 

Assessment of Biomedical Waste Situation in Hospitals of Dolj District
Carmen Aurora V. Bulucea, Aida V. Bulucea, Marius C. Popescu, Anca F. Patrascu

Abstract: The purpose of this position paper will be to summarize the available scientific data regarding biomedical waste management with respect to the environmental impacts. Effective management of biomedical waste incorporates a waste reduction and neutralization component where appropriate. Examining various treatment options underscores the importance of considering the properties of different types of medical waste and matching them to the capabilities of the treatment technologies. An attempt has been made to critically review the current biomedical waste management practices followed by the hospitals of Dolj District – Romania. In the paper the assessment of biomedical waste situation in 11 hospitals of Dolj District will be presented. Following the rules and legislation both of Romania and of European Union, the methods for segregation, packaging, labeling and the treatment techniques for reduction in volume, neutralization and final disposal of the biomedical waste will be analyzed.
 

Applications of Rapid Prototyping in Cranio-Maxilofacial Surgery Procedures
Igor Drstvensek, Natasa Ihan Hren, Tadej Strojnik, Tomaz Brajlih, Bogdan Valentan, Vojko Pogacar, Tjasa Zupancic Hartner

Abstract: In the last decades, the technical field of additive layered manufacturing (ALM) has offered aid in medical reconstruction procedures in order to help surgeons reconstruct physical faults and anomalies of their patients. Using a combination of Computer Assisted Design (CAD), high medical skills and latest ALM technologies, it is now possible to help patients with birth defects or those suffering from craniofacial injuries of variable severities, retain aesthetic and functional properties of their bodies. Combined with traditional CT scanning techniques rapid technologies (prototyping and tooling) can be used as instruments for better (three-dimensional) visualization, simulation of procedures and treatment of patients. They also improve the overall performances of medical and nursing staff thus influencing the quality of medical service. Using a combination of Computer Assisted Design (CAD), high medical skills and latest rapid prototyping and manufacturing technologies, it is now possible to help patients with craniofacial deformities as birth defects, orthognathic deformities, deformities after malignancy treatment or the consequences of craniofacial injuries of variable severities, resulting in both aesthetic and functional alterations. This paper presents some clinical cases, carried out in cooperation of Faculty of Mechanical Engineering in Maribor and both University Clinical Centres in Slovenia, where virtual models have been used for surgical preparations and RP models for manufacturing of implants.
 

Numerical Analysis of Factors which Influent the Biotic Systems Using the Ferment Activity of Beer Yeast
Mariana R. Milici, Rodica Rotar, L. Dan Milici

Abstract: The beer producing is one of the eldest technological process which uses the beer yeasts to transform the fermentable glucides into ethylic alchool, carbon dioxide and aroma compound. The alive cells are open sistems, separated by environment through the cytoplasmatic membrane, and them physiological state is determined by controled transport of nutritives to the inside of cell or of the metabolism products to the outside of cell. The study proposes to find the most efficient way to grow the intracellular trehaloze content through beer yeast suspending into trehaloze solutions by different concentrations, at different thermo-stating temperatures and in different contact times, taking into account that this technique allows the passive transfer of exogenetic trehaloze inside the cells both at a new propagated cell population, and at cells resulted from an industrial inoculums.
 

    Paper Title, Authors, Abstract (Issue 2, Volume 2, 2008)

Pages

Different Species Classifier and Hemoglobin Structure Predictor based on DNA Sequences
Roaa I. Mubark, Hesham A. Keshk, Mohamed I. Eladawy

Abstract: Large-scale analysis studies of genetic sequence data are in progress around the world; one of these studies is to recognize the type of the species that the sequence belongs to. This is very important especially when the source of the sequence is unknown. The complete genome sequence of the hemoglobin provides an excellent basis for studying the clustering of different species. In this paper 13 different species classifier based on hemoglobin sequence will be introduced. Two different classifiers systems also have been used; one of them based on neural network and the other based on extracting 84 pattern feature from the DNA sequence of hemoglobin with the Euclidean distance technique. Also one of the greatest challenges today in bioinformatics is to predict the structure of the protein from the DNA sequence. Protein structural domains are often associated with a particular protein function also the structure contains a valuable information to the biologists instead of the meaningless sequence. Because the experimental techniques that used to determine protein structure such as the x-ray crystallography and Nuclear Magnetic Resonance “NMR” spectroscopy are very expensive and can not be applied all the time, so the prediction may be the way to get the protein structure. In this work we will be able to predict the 3D structure of hemoglobin using two techniques; the neural network and hidden Markov model. Also, the prediction of the secondary structure is applied using multiple alignments.
 

Artifact and Noise Stripping on Low-Field Brain MRI
Nur Faiza Ishak, Rajasvaran Logeswaran, Wooi-Haw Tan

Abstract: Low-field Magnetic Resonance Imaging (MRI) is a relatively new technology that is used in operating rooms to allow real-time imaging. The images produced are valuable for guidance and assessment during the surgery, but the low signal strength produces very low resolution images with noise and artifacts. This study shows that implementation of a dynamic pre-processing algorithm to extract the brain region in low-field MRI images is crucial in order to accurately segment the brain image. Conceptually, histogram-based analysis indicates that most low-field MR images consist of three peaks, where the first and second peaks summarize the background and artifacts, respectively, while the third peak is the region-of-interest (ROI). This paper provides some useful insight of steps that could be taken prior to brain segmentation. Promising results are reported for both qualitative and quantitative measurements.
 

Analysis of Signal Transduction Networks in Michaelis-Menten Equations and S-Systems
Chun-Liang Lin, Yuan-Wei Liu, Chia-Hua Chuang

Abstract: Signal transduction networks of biological systems are highly complicated. How to mathematically describe a signal transduction network by systematic approaches so as to further exploit appropriate control strategies is becoming attractive to engineers. In this paper, a mathematical model of signal transduction networks with a simplified structure is proposed and related analyses are performed.
 

An Intravascular Ultrasound-based Tissue Characterization Using Shift-invariant Features Extracted by Adaptive Subspace SOM
Ryosuke Kubota, Mami Kunihiro, Noriaki Suetake, Eiji Uchino, Genta Hashimoto, Takafumi Hiro, Masunori Matsuzaki

Abstract: Tissue characterization of a plaque is important for a diagnosis of the acute coronary syndromes (ACS). An intravascular ultrasound (IVUS) technique with a probe mounted at the tip of a catheter is often used. As the conventional tissue characterization methods using the IVUS technique, an integrated backscatter (IB) analysis in the time domain and a spectral analysis in the frequency domain have been proposed so far. However, those conventional methods can not perform a good classification. The IB values are substantially affected by the intensity of the backscattered ultrasound, and the frequency characteristics of some types of tissues are similar with others. In this paper, we propose a novel tissue characterization method by using an adaptive subspace self-organizing map (ASSOM). ASSOM can extract various features from the IVUS signal. Those features are suitable for the tissue characterization, because the overlap of the distributions of the extracted features is much smaller than the one, e.g., by the IB analysis or by a traditional Fourier spectrum analysis. A tissue is characterized by using the statistical information of the features extracted by ASSOM. Through the application to the tissue characterization of the real IVUS signal, the performance of the proposed method has been verified by comparing it with the conventional methods.
 

 Paper Title, Authors, Abstract (Issue 3, Volume 2, 2008)  

Pages

Measurement of the Electrical Properties of Ungelled ECG Electrodes
A. Baba, M. J. Burke

Abstract: This paper reports the measurement of the properties of dry or pasteless conductive electrodes to be used for long-term recording of the human electrocardiogram (ECG). Knowledge of these properties is essential for the correct design of the input stage of associated recording amplifiers. Measurements were made on seven commercially available conductive carbon based electrodes at pressures of 5mmHg (0.67kPa) and 20mmHg (2.7kPa), located on the lower abdomen and chest of the body on seven subjects having different skin types. Parameter values were fitted to a two-time-constant based model of the electrode using data measured over a period of 10s. Values of resistance, ranging from 23k? to 1850k? and of capacitance ranging from 0.01?F to 65?F were obtained for the components, while the values of the time-constants varied from 0.02s to 7.2s.
 

Different Species Classifier and Hemoglobin Structure Predictor based on DNA Sequences
Roaa I. Mubark, Hesham A. Keshk, Mohamed I. Eladawy

Abstract: Large-scale analysis studies of genetic sequence data are in progress around the world; one of these studies is to recognize the type of the species that the sequence belongs to. This is very important especially when the source of the sequence is unknown. The complete genome sequence of the hemoglobin provides an excellent basis for studying the clustering of different species. In this paper 13 different species classifier based on hemoglobin sequence will be introduced. Two different classifiers systems also have been used; one of them based on neural network and the other based on extracting 84 pattern feature from the DNA sequence of hemoglobin with the Euclidean distance technique. Also one of the greatest challenges today in bioinformatics is to predict the structure of the protein from the DNA sequence. Protein structural domains are often associated with a particular protein function also the structure contains a valuable information to the biologists instead of the meaningless sequence. Because the experimental techniques that used to determine protein structure such as the x-ray crystallography and Nuclear Magnetic Resonance “NMR” spectroscopy are very expensive and can not be applied all the time, so the prediction may be the way to get the protein structure. In this work we will be able to predict the 3D structure of hemoglobin using two techniques; the neural network and hidden Markov model. Also, the prediction of the secondary structure is applied using multiple alignments.
 

System Identification and Control Using DNA Computing Algorithms
Ching-Huei Huang, Chun-Liang Lin, Horn-Yong Jan

Abstract: A DNA computing algorithm (DNACA) with an electron-ion interaction potential (EIIP) decoding scheme is proposed to identify a class of transfer functions. The DNACA includes crossover, mutation, enzyme and virus operators providing a highly modular, flexible, and accurate self-organizing structure. Simulation study based on the De Jong’s test functions show its superior performance when compared with the improved and standard genetic algorithms (GAs). The algorithm is also applied to control design with the simplest controller through special frameshift mutation such as enzyme and virus.
 

 Paper Title, Authors, Abstract (Issue 4, Volume 2, 2008)  

Pages

Different Species and Proteins Classifiers and Protein's Structure Predictors Systems
Roaa I. Mubark, Hesham A. Keshk, Mohamed I. Eladawy

Abstract: Because the experimental techniques that have been used to determine protein structure such as the x-ray crystallography and Nuclear Magnetic Resonance “NMR” spectroscopy are very expensive and cannot be applied all the time, so the prediction may be the way to get the protein structure. Most of previous works in the field of protein structure prediction given a certain protein sequence works on a database of proteins from different species. In this proposed work we will use a given protein sequence such as hemoglobin, insulin, and albumin to recognize first the species that this sequence belongs to. Knowing the species to which the sequence belongs will give better results in predicting the structure of that sequence, either the 3D or the secondary structures. Knowing the species can even help in the correct recognition of the protein type given the protein sequence. In this paper we used the neural network, Hidden Markov model, and Euclidean distance techniques in the classification and prediction processes.
 

The Papain Local Depot Impairs the Capsule Fibrous Healing Around Textured Silicone Implants in Rats
Marcio Moreira, Djalma Jose Fagundes, Sanderland Jose Tavares Gurgel

Abstract: To study the tissue repair around the textured mammary implants under the action of papain (PA). Methods: Thirty-six Wistar rats were evaluated and randomly distributed into two groups (n = 18): papain (PA) and control (CT). Each group was equally distributed into 3 subgroups (n = 6) and observed on seventh, thirtieth-fifth and ninth pos-operative days. Each animal received a textured implant in the left dorso-axillary region (sham - SH), on were instilled 0.5 mL saline solution 0.9%, and another textured implant on the right dorso-axillary region (papain - PA), on were instilled 0.5 mL of water-soluble solution of papain. The control group (CT) received only textured implant in the left dorso-axillary region with prior instillation of 0.5 mL of saline solution 0.9%. The histological analysis of the 3 subgroups was carried out using picrosirius-red stain and an image analyzing system using the Image Pro Plus™ program to evaluate the thickness and maturation and deposition of collagen fibers. Immunohistochemical evaluation was performed, using micrometric reticules of Weiss (Olympus Labstore™), for myofibroblasts counting only in the 90th day subgroup. Results: At 35th and 90th days, the papain group (PA) presented reduction on the fibrous capsule thickness around the implant, in the number of collagen fibers and myofibroblasts, comparing to the control group (CT). Conclusion: The papain drug decreased the fibrous capsule formation around the textured silicon implants in rats.
 

Simulation of da Vinci Surgical Robot Using Mobotsim Program
Marius-Constantin O. S. Popescu, Nikos E. Mastorakis

Abstract: This paper presents a simulated control applications and remote perception, generically called telepresence and teleoperare. In essence, it is transmitted remotely by the IT environment, the signals captured by equipment and controls to the equipment, decided by an operator or an automatic system. In general, sending commands to remote equipment is called teleoperare, who decides whether the control is a human operator or an automatic driving system. An important issue of medical world concerns the creation of systems for online medical parameters monitoring. The solution is to pervade into computing systems which have the capabilities of monitoring, data acquisition and data transfer from medical devices. We describe in this paper the use of integrated planning and simulation for robotic surgery.