• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1243-1248
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• 2008

As development in technology of bioinformatics recently mates it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. In this thesis, we used CDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer. It analyzed and compared performance of each of the experiment result using existing DT, NB, SVM and multi-perceptron neural network classifier combined the similar scale combination method after constructing class classification model by extracting significant gene list with a similar scale combination method proposed in this paper through normalization. Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) represented the accuracy of 98.84%, which show that it improve classification performance than case to experiment using other classifier.

• The Korean Journal of Cytopathology
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• v.14 no.1
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• pp.12-16
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• 2003

Ganglioneuroma is a well-differentiated, benign tumor of the sympathetic nervous system. These tumors belong to a family of neoplasm that exhibit a wide range of differentiation, with neuroblastoma at one end and ganglioneuroma at the other. Because it share morphologic features with other both benign and malignant neural tumors, accurate preoperative diagnosis is often difficult. Nonetheless, it is critical for proper management. Fine needle aspiration cytology (FNAC) in the diagnosis of the ganglioneuroma has been a little documented. We describe a case of mediastinal ganglioneuroma in a 33-month-old girl. The diagnosis was suggested on FNAC and was confirmed by histopathologic examination later.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.21 no.2
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• pp.75-79
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• 2017

This paper approaches the subject of consciousness and unconsciousness from a mathematical point of view. It sets up a hypothesis that when unconscious state becomes conscious state, high density energy is released. We argue that the process of transformation of unconsciousness into consciousness can be expressed using the infinite recursive Heaviside step function. We claim that differentiation of the potential of unconsciousness with respect to time is the process of being conscious in a world where only time exists, since the thinking process never have any concrete space. We try to attribute our unconsciousness to a special solution of the multi-dimensional advection partial differential equation which can be represented by the finite recursive Heaviside step function. Mathematical language explains how the infinitive neural process is perceived and understood by consciousness in a definitive time.

• 대한생식의학회:학술대회논문집
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• 2004.06a
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• pp.85-85
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• 2004

• Biomedical Science Letters
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• v.12 no.4
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• pp.343-348
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• 2006

Drosophila Sog and vertebrate Noggin play important roles during development. They function as antagonists against BMP4 signaling and induce neural ectoderm during embryogenesis. They are also engaged in appendage formation by inhibiting BMP4 signaling during late development. To understand further functions of Sog, Supersog, which is a more potent form of Sog, and Noggin BMP4 antagonists during development, I performed the molecular genetic analysis using Drosophila embryogenesis and wing formation as assay systems. In cellular blastoderm embryos, Sog inhibited Dpp signaling, Drosophila BMP4 signaling, whereas Supersog or Noggin did not block Dpp signaling. During wing formation, Sog inhibited Sax type I receptor of Dpp signaling whereas Noggin inhibited Tkv type I receptor of Dpp signaling. However, Supersog inhibited both Sax and Tkv type I receptors. These results suggest that functions of BMP4 antagonists are developmental stage dependent and indicate that each BMP4 antagonist inhibits BMP4 signaling by blocking different BMP4 receptors.

• Proceedings of the KSAR Conference
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• 2001.10a
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• pp.53-54
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• 2001

Expression of HAND genes in sympathetic adrenal lineage suggests that HAND genes may regulate Mash-I independent neuronal genes. HAND genes are also expressed in other cell types, e.g. Cardiac cells, trophoblasts, and decidua, suggesting that HAND genes are not cell fate determination factors. It is unclear how HAND genes function specifically in different types of cells. Combinational actions of HANDs with other cell-lineage specific transcription factor may determine each cell fate and differentiation processes. Identifying the transcription target genes of HANDs and Mash-I will be important to elucidate the function of these bHLH factors in SNS factors in SNS development. (omitted)

• Advances in pediatric surgery
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• v.14 no.1
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• pp.75-82
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• 2008

Neuroblastoma arises from the primitive neural crest cells, and is a common malignancy in childhood. The clinical features are characterized by biological heterogeneity. Neuronal degeneration and differentiation occur in some patients. However treatment in the high risk group accounting for approximately half, has not been satisfactory despite a multimodal approach. Therefore, effective treatment is determined by the risk group of prognostic factors, such as age at diagnosis, stage of disease, pathological finding and N-myc amplification. Neuroblastoma can be diagnosed prenatally, which suggests its origin during the normal embryogenesis. Recent knowledge of molecular biology, such as Trk genes, and the concept of cancer stem cells have given us some improved understanding on this disease. Currently, targeted therapies based on the molecular biology of neuroblastoma are under investigation and increasing survival rate and decreasing late complications could be appreciated.

• The Korean Journal of Zoology
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• v.37 no.1
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• pp.130-136
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• 1994

Although alteration in protein phosphorylation by specific protein kinases is of importance in transducing cellular signals in a variety of neural/endocrine systems, little is known about protein phosphorylation in the hvpothalamus. The present study aims to explore whether activation of the second messenger-dependent protein kinases affects phosphorylation of specific proteins using a cell free phosphorylation system followed by SDS-polvacrylamide gel electrophoresis. Cytoplasmic fractions derived from hvpothalami of immature rats were used as substrates and several activators and/or inhibitors of CAMP-, phosphatidylinositol- and Ca2+-calmodulin-dependent protein kinases were assessed. Many endogenous proteins were extensively phosphorylated and depending on the signal transduction pathways, phosphorvlation profiles were markedly different. The present data indicate that extracellular signals may affect cellular events through protein phosphorylation by second messengers-protein kinases in the rat hypothalamus.

• Journal of Korean Neurosurgical Society
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• v.62 no.3
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• pp.265-271
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• 2019

The expansion and folding of the cerebral cortex occur during brain development and are critical factors that influence cognitive ability and sensorimotor skills. The disruption of cortical growth and folding may cause neurological disorders, resulting in severe intellectual disability and intractable epilepsy in humans. Therefore, understanding the mechanism that regulates cortical growth and folding will be crucial in deciphering the key steps of brain development and finding new therapeutic targets for the congenital anomalies of the cerebral cortex. This review will start with a brief introduction describing the anatomy of the brain cortex, followed by a description of our understanding of the proliferation, differentiation, and migration of neural progenitors and important genes and molecules that are involved in these processes. Finally, various types of disorders that develop due to malformation of the cerebral cortex will be discussed.