| Volume 22, Issue 3 | |
| Optimization of Continuous Bioconversion Process of Glycerol to 1,3-Propanediol | 199-212 |
| Gongxian Xu, Dan Wang, Caixia Li | |
| doi: 10.7546/ijba.2018.22.3.199-212 | |
| [ +/- how to cite ][ +/- abstract ][ full text ] | |
| Gongxian Xu, Dan Wang, Caixia Li (2018) Optimization of Continuous Bioconversion Process of Glycerol to 1,3-Propanediol, Int J Bioautomation, 22 (3), 199-212, doi: 10.7546/ijba.2018.22.3.199-212 | |
| Abstract: This paper addresses the optimization of continuous bioconversion process of glycerol to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae. The studied bioprocess is a complex nonlinear system that involves the gene regulation for dha regulon, enzyme-catalytic kinetics on the reductive pathway, the active transport of glycerol and (passive) diffusion of 1,3-PD across the cell membrane, and the inhibition of glycerol dehydratase (GDHt) and 1,3-propanediol oxidoreductase (PDOR) by 3-hydroxypropionaldehy (3-HPA). We first propose a nonlinear optimization model that can maximize the production rate of 1,3-PD. Then the optimal solution of this optimization problem is obtained by using an interior point method. In this approach a sequence of barrier problems are solved iteratively. We finally obtain the maximum production rate of 1,3-PD increased more than 22.86 times its initial value. Keywords: Optimization, Bioconversion process, Continuous bioprocess, Interior point method, 1,3-propanediol, Glycerol | |
| Modelling the Distribution of Lasers in Biological Tissues | 213-228 |
| Teodora Petrova, Zhivo Petrov | |
| doi: 10.7546/ijba.2018.22.3.213-228 | |
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| Teodora Petrova, Zhivo Petrov (2018) Modelling the Distribution of Lasers in Biological Tissues, Int J Bioautomation, 22 (3), 213-228, doi: 10.7546/ijba.2018.22.3.213-228 | |
| Abstract: For the time being there is no accurate theory about the spread of light in a structurally non-homogeneous medium whereas the experimental research is additionally hindered because of the necessity to maintain constant structural-dynamic parameters. In this respect numerical modelling of the processes of spreading of laser radiation plays increasingly important role. Keywords: Biomedical technologies, Lasers, Mathematical model | |
| Adaptive Meshing Based on the Multi-level Partition of Unity and Dynamic Particle Systems for Medical Image Datasets | 229-238 |
| Zhong Chen, Zhiwei Hou, Quanquan Yang, Xiaobing Chen | |
| doi: 10.7546/ijba.2018.22.3.229-238 | |
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| Zhong Chen, Zhiwei Hou, Quanquan Yang, Xiaobing Chen (2018) Adaptive Meshing Based on the Multi-level Partition of Unity and Dynamic Particle Systems for Medical Image Datasets, Int J Bioautomation, 22 (3), 229-238, doi: 10.7546/ijba.2018.22.3.229-238 | |
| Abstract: Surface meshes extracted from sparse medical images contain surface artifacts, there will produce serious distortion and generate numerous narrow triangle meshes. In order to eliminate the impact of the above factors, this paper presents a novel method for generating smooth and adaptive meshes from medical image datasets. Firstly, extracting the stack of contours by means of image segmentation and translating the contours into point clouds. The improved Multi-Level Partition of Unity (MPU) implicit functions are used to fit the point clouds for creating the implicit surface. Then, sampling implicit surface through dynamic particle systems based on Gaussian curvature, dense particles sampling in the high curvature region, sparse particles sampling in the low curvature region. Finally, generating triangle meshes based on particle distribution by using the Delaunay triangulation algorithm. Experimental results show that the proposed method can generate high-quality triangle meshes with distributed adaptively and have a nice gradation of triangle mesh density on the surface curvature. Keywords: Medical computed tomography, Point clouds, Multi-level partition of unity, Dynamic particle systems, Gaussian curvature | |
| Infusion Monitoring Communication Model of Smart Home Based on Coloured Petri Net | 239-252 |
| Xin-Liang Wang, Qing-Gai Huang | |
| doi: 10.7546/ijba.2018.22.3.239-252 | |
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| Xin-Liang Wang, Qing-Gai Huang (2018) Infusion Monitoring Communication Model of Smart Home Based on Coloured Petri Net, Int J Bioautomation, 22 (3), 239-252, doi: 10.7546/ijba.2018.22.3.239-252 | |
| Abstract: When patients need to be for infusion at home, there is no central control server in hospital, and it is not possible to add additional monitoring equipment; at the same time, there may not be a special person to care for patients. The infusion monitoring communication model of smart home based on coloured Petri net, which is proposed in this paper, can use smart mobile phone to construct an adaptive infusion monitoring system at home. The model can make infusion alarm module automatically search for smart mobile phone terminals in a WiFi network, complete the search, identification, monitoring and other functions. It will constitute a smart phone infusion monitoring network so that infusion online monitoring could effectively be completed at home without adding additional equipment. The simulation result shows that regardless of whether there is a packet loss, as long as there is a smart mobile phone terminal and the corresponding infusion alarm module in the network, the model can make the infusion alarm module to realize automatic search function and infusion monitoring function, and provide better medical service for the smart home. Keywords: Infusion monitoring, Coloured Petri net, Smart mobile phone, Smart home | |
| Effect of Proactive Mode of Processing on Event-related Oscillatory Brain Responses in Children | 253-262 |
| Plamenka Nanova, Vasil Kolev, Juliana Yordanova | |
| doi: 10.7546/ijba.2018.22.3.253-262 | |
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| Plamenka Nanova, Vasil Kolev, Juliana Yordanova (2018) Effect of Proactive Mode of Processing on Event-related Oscillatory Brain Responses in Children, Int J Bioautomation, 22 (3), 253-262, doi: 10.7546/ijba.2018.22.3.253-262 | |
| Abstract: Proactive cognition is characterized by the formation and active maintenance of an internal task representation. The aim of this study was to explore if the internal task representation might affect the processing of incoming stimuli. For that aim, the effects of proactive and reactive modes of processing on sensory and cognitive information processing were compared by using event-related oscillatory responses in a developmental model. Thirty six children aged 7-10 years were studied in a sensorimotor task with fixed stimulus sequences. Children were divided into two groups according to their proactive or reactive mode. Auditory event-related potentials were recorded and decomposed in the time-frequency domain to analyze amplitude and phase synchronization of oscillatory responses. Major results demonstrated that proactive mode of processing was characterized by enhanced pre-stimulus theta activity accompanied by a significant decrease of the temporal synchronization of event-related theta/alpha oscillations in the first 300 ms after stimulus. These results provide evidence that maintaining internal task representations in working memory engages oscillatory circuits, which can modulate the processing of incoming sensory information. Keywords: Time-frequency ERP components, Children, Cognition, Auditory modality | |
| Research on Exploring the Patients’ Hiding Disease Based on Symptom Weighted Clustering Technique | 263-274 |
| Yingying Peng, Gang Yi | |
| doi: 10.7546/ijba.2018.22.3.263-274 | |
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| Yingying Peng, Gang Yi (2018) Research on Exploring the Patients’ Hiding Disease Based on Symptom Weighted Clustering Technique, Int J Bioautomation, 22 (3), 263-274, doi: 10.7546/ijba.2018.22.3.263-274 | |
| Abstract: The research regards the diagnostic data of the patients’ disease as the mining data source. Each diagnostic data includes patients’ symptom and sickness. The paper regards a certain patient as the mining target, considering the symptom weighted situation, using the clustering method in the data mining to dig the tendency of patients’ disease. In addition, the paper combines a group center formed by the patients’ symptom and designs a symptom weighted clustering method to satisfy the diagnostic data of minimal symptom similarity which belongs to the clustering. Later, the disease item whose number is the maximum can be found out in the clustering and the tendency of patients’ sickness. The methods proposed in the paper design and build a diagnostic system of patients’ sickness. The mining results of system can offer some useful referent information for those people check the sickness tendency of patients’ disease or those medical staff whose clinical experience is not enough confirms the disease diagnosis. Keywords: Data mining, Clustering, Symptom weighted, Disease | |
| Locally-adaptive Myriad Filtration of One-dimensional Complex Signal | 275-296 |
| Nataliya Tulyakova, Tatyana Neycheva, Oleksandr Trofymchuk, Oleksandr Stryzhak | |
| doi: 10.7546/ijba.2018.22.3.275-296 | |
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| Nataliya Tulyakova, Tatyana Neycheva, Oleksandr Trofymchuk, Oleksandr Stryzhak (2018) Locally-adaptive Myriad Filtration of One-dimensional Complex Signal, Int J Bioautomation, 22 (3), 275-296, doi: 10.7546/ijba.2018.22.3.275-296 | |
| Abstract: Locally-adaptive algorithms of myriad filtering are proposed with adaptation of a sample myriad linearity parameter K, depending upon local estimates of a signal, and with “hard” switching of sliding window length settings and a coefficient which influences on the parameter K. Statistical estimates of the filters quality are obtained using a criterion of a minimum mean-square error for a model of one-dimensional complex signal that includes different elementary segments under conditions of additive Gaussian noise with zero mean and different variances and possible spikes presence. Improvement of integral and local performance indicators is shown in comparison to the highly effective non-linear locally-adaptive algorithms for the considered test signal. Having a complex signal of high efficiency, one of the proposed algorithms provides nearly optimal noise suppression at the segments of linear change of a signal; other algorithm provides higher quality of step edge preservation and the best noise suppression on a const signal. Better efficiency in cases of low and high noise levels is achieved by preliminary noise level estimation through comparison of locally-adaptive parameter and thresholds. It is shown that, in order to ensure better spikes removal, it is expedient to pre-process the signal by robust myriad filter with small window length. The considered adaptive nonlinear filters have possibility to be implemented in a real time mode. Keywords: Locally-adaptive myriad filtering, One-dimensional complex signals, Minimum mean square error criterion, Statistical estimates of filter efficiency |
Sponsored by National Science Fund of Bulgaria, Grant No DNP 06-18/2017
© 2018, BAS, Institute of Biophysics and Biomedical Engineering