Determining bank effects on economic growth: An artificial neural network analysis

OpenAIRE

Alex Senajon

2016-01-01

This study characterized the influence of the banking industry’s influence on the growth of the economy. A neural network using the Multilayer Perception was used to define functions of Universal Bank, Cooperative Bank, and Thrift Bank as predictors of Gross Domestic Product growth. Using data series from 2003- 2013, it was found that Universal banks have been growing tremendously taking huge shares of growth compared to the other two bank types. Meantime, the Gross Domestic Product was fo...

Weed Growth Stage Estimator Using Deep Convolutional Neural Networks

DEFF Research Database (Denmark)

Teimouri, Nima; Dyrmann, Mads; Nielsen, Per Rydahl

2018-01-01

This study outlines a new method of automatically estimating weed species and growth stages (from cotyledon until eight leaves are visible) of in situ images covering 18 weed species or families. Images of weeds growing within a variety of crops were gathered across variable environmental conditi...... in estimating the number of leaves and 96% accuracy when accepting a deviation of two leaves. These results show that this new method of using deep convolutional neural networks has a relatively high ability to estimate early growth stages across a wide variety of weed species....

AN ANALYSIS OF THE RAPID GROWTH FACTORS PRESENTED IN THE LITERATURE OF THE FIELD

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ALB MARIA

2015-03-01

Full Text Available This paper presents the main rapid growth factors, as encountered in literature and discusses the importance and contribution of these factors in achieving the rapid growth, respectively if this growth phenomenon may be achieved in the absence of the aforesaid factors. The paper examines the factors and subfactors considered or found by scholars to have an effect on or be in connection with the rapid growth. A comparative analysis was performed on several studies concerning the rapid growth companies. Among the main factors influencing the rapid growth are those related to the human resources management, the entrepreneur characteritics and the characteristics of the business. The paper also discusses several issues related to the will of the manager or the entrepreneur, repectively the need to understand the role of the factors that intervene when the growth is not wanted and still obtained or when the growth is targeted but not achieved. The conclusion is in agreement with other scholars’ findings reported in the literature. Certain factors correlated with the appropriate actions may lead to the rapid growth. The paper represents a starting point for the study of those management related aspects enabling companies to grow rapidly in the Romanian business environment.

Response of the sensorimotor cortex of cerebral palsy rats receiving transplantation of vascular endothelial growth factor 165-transfected neural stem cells

Institute of Scientific and Technical Information of China (English)

Jielu Tan; Xiangrong Zheng; Shanshan Zhang; Yujia Yang; Xia Wang; Xiaohe Yu; Le Zhong

2014-01-01

Neural stem cells are characterized by the ability to differentiate and stably express exogenous ge-nes. Vascular endothelial growth factor plays a role in protecting local blood vessels and neurons of newborn rats with hypoxic-ischemic encephalopathy. Transplantation of vascular endothelial growth factor-transfected neural stem cells may be neuroprotective in rats with cerebral palsy. In this study, 7-day-old Sprague-Dawley rats were divided into ifve groups: (1) sham operation (control), (2) cerebral palsy model alone or with (3) phosphate-buffered saline, (4) vascular en-dothelial growth factor 165 + neural stem cells, or (5) neural stem cells alone. hTe cerebral palsy model was established by ligating the letf common carotid artery followed by exposure to hypox-ia. Phosphate-buffered saline, vascular endothelial growth factor + neural stem cells, and neural stem cells alone were administered into the sensorimotor cortex using the stereotaxic instrument and microsyringe. Atfer transplantation, the radial-arm water maze test and holding test were performed. Immunohistochemistry for vascular endothelial growth factor and histology using hematoxylin-eosin were performed on cerebral cortex. Results revealed that the number of vas-cular endothelial growth factor-positive cells in cerebral palsy rats transplanted with vascular endothelial growth factor-transfected neural stem cells was increased, the time for ifnding water and the ifnding repetitions were reduced, the holding time was prolonged, and the degree of cell degeneration or necrosis was reduced. hTese ifndings indicate that the transplantation of vascu-lar endothelial growth factor-transfected neural stem cells alleviates brain damage and cognitive deifcits, and is neuroprotective in neonatal rats with hypoxia ischemic-mediated cerebral palsy.

Growth kinetics of borided layers: Artificial neural network and least square approaches

Science.gov (United States)

Campos, I.; Islas, M.; Ramírez, G.; VillaVelázquez, C.; Mota, C.

2007-05-01

The present study evaluates the growth kinetics of the boride layer Fe 2B in AISI 1045 steel, by means of neural networks and the least square techniques. The Fe 2B phase was formed at the material surface using the paste boriding process. The surface boron potential was modified considering different boron paste thicknesses, with exposure times of 2, 4 and 6 h, and treatment temperatures of 1193, 1223 and 1273 K. The neural network and the least square models were set by the layer thickness of Fe 2B phase, and assuming that the growth of the boride layer follows a parabolic law. The reliability of the techniques used is compared with a set of experiments at a temperature of 1223 K with 5 h of treatment time and boron potentials of 2, 3, 4 and 5 mm. The results of the Fe 2B layer thicknesses show a mean error of 5.31% for the neural network and 3.42% for the least square method.

Economic Growth of a Rapidly Developing Economy: Theoretical Formulation

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Oleg Sergeyevich Sukharev

2016-06-01

Full Text Available The subject matter of the article is the description of economic growth. Modern economy is characterized by a high rate of changes. These changes are the limiting parameters of modern development, which requires a modification of the basic models of growth, the substantiation of the expediency and necessity of a rapid development strategy. In a simple mathematical form, the statement of the problem of economic growth in the “green economy” is examined, in which the costs of environmental measures are not considered a priori as hampering economic development (as it is common for a number of modern neoclassical and neo-Keynesian growth models. The methodological basis of the article are the econometric approach and modelling method. The article has a theoretical character. The main hypothesis supposes that the rapid development strategy cannot make an adequate development strategy under certain conditions, but may be acceptable in other its specific conditions. In this sense, the important growth conditions are the availability of resources, the effectiveness of institutions and the current economic structure, the technological effectiveness of economy, as well as the conditions of technological development (“green economy” and the path of such development. In the article, on the theoretical level of analysis, the substantiation of the adequacy of the rapid development strategy for an economic system is given, whose goal is to achieve the standard of living of the countryleader. Based on the assumptions introduced, the period for which the rapid development strategy might be implemented and the economic lag of the country might be reduced from the country-leader is determined. The conditions that ensure the impact of innovations on the rate of economic development are summarized. The introduced range of dependencies and relations can be useful for the elaboration of the theory of innovation development and for the formation of a new

Hepatocyte growth factor/scatter factor-MET signaling in neural crest-derived melanocyte development.

Science.gov (United States)

Kos, L; Aronzon, A; Takayama, H; Maina, F; Ponzetto, C; Merlino, G; Pavan, W

1999-02-01

The mechanisms governing development of neural crest-derived melanocytes, and how alterations in these pathways lead to hypopigmentation disorders, are not completely understood. Hepatocyte growth factor/scatter factor (HGF/SF) signaling through the tyrosine-kinase receptor, MET, is capable of promoting the proliferation, increasing the motility, and maintaining high tyrosinase activity and melanin synthesis of melanocytes in vitro. In addition, transgenic mice that ubiquitously overexpress HGF/SF demonstrate hyperpigmentation in the skin and leptomenigenes and develop melanomas. To investigate whether HGF/ SF-MET signaling is involved in the development of neural crest-derived melanocytes, transgenic embryos, ubiquitously overexpressing HGF/SF, were analyzed. In HGF/SF transgenic embryos, the distribution of melanoblasts along the characteristic migratory pathway was not affected. However, additional ectopically localized melanoblasts were also observed in the dorsal root ganglia and neural tube, as early as 11.5 days post coitus (p.c.). We utilized an in vitro neural crest culture assay to further explore the role of HGF/SF-MET signaling in neural crest development. HGF/SF added to neural crest cultures increased melanoblast number, permitted differentiation into pigmented melanocytes, promoted melanoblast survival, and could replace mast-cell growth factor/Steel factor (MGF) in explant cultures. To examine whether HGF/SF-MET signaling is required for the proper development of melanocytes, embryos with a targeted Met null mutation (Met-/-) were analysed. In Met-/- embryos, melanoblast number and location were not overtly affected up to 14 days p.c. These results demonstrate that HGF/SF-MET signaling influences, but is not required for, the initial development of neural crest-derived melanocytes in vivo and in vitro.

Persistent Environmental Toxicants in Breast Milk and Rapid Infant Growth.

Science.gov (United States)

Criswell, Rachel; Lenters, Virissa; Mandal, Siddhartha; Stigum, Hein; Iszatt, Nina; Eggesbø, Merete

2017-01-01

Many environmental toxicants are passed to infants in utero and through breast milk. Exposure to toxicants during the perinatal period can alter growth patterns, impairing growth or increasing obesity risk. Previous studies have focused on only a few toxicants at a time, which may confound results. We investigated levels of 26 toxicants in breast milk and their associations with rapid infant growth, a risk factor for later obesity. We used data from the Norwegian HUMIS study, a multi-center cohort of 2,606 mothers and newborns enrolled between 2002 and 2008. Milk samples collected 1 month after delivery from a subset of 789 women oversampled by overweight were analyzed for toxicants including polychlorinated biphenyls (PCBs), heavy metals, and pesticides. Growth was defined as change in weight-for-age z-score between 0 and 6 months among the HUMIS population, and rapid growth was defined as change in z-score above 0.67. We used a Bayesian variable selection method to determine the exposures that most explained variation in the outcome. Identified toxicants were included in logistic and linear regression models to estimate associations with growth, adjusting for maternal age, smoking, education, pre-pregnancy body mass index (BMI), gestational weight gain, parity, child sex, cumulative breastfeeding, birth weight, gestational age, and preterm status. Of 789 infants, 19.2% displayed rapid growth. The median maternal age was 29.6 years, and the median pre-pregnancy BMI was 24.0 kg/m2, with 45.3% of mothers overweight or obese. Rapid growers were more likely to be firstborn. Hexachlorobenzene, β-hexachlorocyclohexane (β-HCH), and PCB-74 were identified in the variable selection method. An interquartile range (IQR) increase in β-HCH exposure was associated with a lower odds of rapid growth (OR 0.63, 95% CI 0.42-0.94). Newborns exposed to high levels of β-HCH showed reduced infant growth (β = -0.03, 95% CI -0.05 to -0.01 for IQR increase in breast milk concentration

NeuroMEMS: Neural Probe Microtechnologies

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Sam Musallam

2008-10-01

Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

Isolation and characterization of neural stem cells from human fetal striatum

International Nuclear Information System (INIS)

Li Xiaoxia; Xu Jinchong; Bai Yun; Wang Xuan; Dai Xin; Liu Yinan; Zhang Jun; Zou Junhua; Shen Li; Li Lingsong

2005-01-01

This paper described that neural stem cells (hsNSCs) were isolated and expanded rapidly from human fetal striatum in adherent culture. The population was serum- and growth factor-dependent and expressed neural stem cell markers. They were capable of multi-differentiation into neurons, astrocytes, and oligodendrocytes. When plated in the dopaminergic neuron inducing medium, human striatum neural stem cells could differentiate into tyrosine hydroxylase positive neurons. hsNSCs were morphologically homogeneous and possessed high proliferation ability. The population doubled every 44.28 h and until now it has divided for more than 82 generations in vitro. Normal human diploid karyotype was unchanged throughout the in vitro culture period. Together, this study has exploited a method for continuous and rapid expansion of human neural stem cells as pure population, which maintained the capacity to generate almost fifty percent neurons. The availability of such cells may hold great interest for basic and applied neuroscience

Structure of the gene encoding VGF, a nervous system-specific mRNA that is rapidly and selectively induced by nerve growth factor in PC12 cells.

Science.gov (United States)

Salton, S R; Fischberg, D J; Dong, K W

1991-05-01

Nerve growth factor (NGF) plays a critical role in the development and survival of neurons in the peripheral nervous system. Following treatment with NGF but not epidermal growth factor, rat pheochromocytoma (PC12) cells undergo neural differentiation. We have cloned a nervous system-specific mRNA, NGF33.1, that is rapidly and relatively selectively induced by treatment of PC12 cells with NGF and basic fibroblast growth factor in comparison with epidermal growth factor. Analysis of the nucleic acid and predicted amino acid sequences of the NGF33.1 cDNA clone suggested that this clone corresponded to the NGF-inducible mRNA called VGF (A. Levi, J. D. Eldridge, and B. M. Paterson, Science 229:393-395, 1985; R. Possenti, J. D. Eldridge, B. M. Paterson, A. Grasso, and A. Levi, EMBO J. 8:2217-2223, 1989). We have used the NGF33.1 cDNA clone to isolate and characterize the VGF gene, and in this paper we report the complete sequence of the VGF gene, including 853 bases of 5' flank revealed TATAA and CCAAT elements, several GC boxes, and a consensus cyclic AMP response element-binding protein binding site. The VGF promoter contains sequences homologous to other NGF-inducible, neuronal promoters. We further show that VGF mRNA is induced in PC12 cells to a greater extent by depolarization and by phorbol-12-myristate-13-acetate treatment than by 8-bromo-cyclic AMP treatment. By Northern (RNA) and RNase protection analysis, VGF mRNA is detectable in embryonic and postnatal central and peripheral nervous tissues but not in a number of nonneural tissues. In the cascade of events which ultimately leads to the neural differentiation of NGF-treated PC12 cells, the VGF gene encodes the most rapidly and selectively regulated, nervous-system specific mRNA yet identified.

Neural Stem Cell Differentiation Using Microfluidic Device-Generated Growth Factor Gradient.

Science.gov (United States)

Kim, Ji Hyeon; Sim, Jiyeon; Kim, Hyun-Jung

2018-04-11

Neural stem cells (NSCs) have the ability to self-renew and differentiate into multiple nervous system cell types. During embryonic development, the concentrations of soluble biological molecules have a critical role in controlling cell proliferation, migration, differentiation and apoptosis. In an effort to find optimal culture conditions for the generation of desired cell types in vitro , we used a microfluidic chip-generated growth factor gradient system. In the current study, NSCs in the microfluidic device remained healthy during the entire period of cell culture, and proliferated and differentiated in response to the concentration gradient of growth factors (epithermal growth factor and basic fibroblast growth factor). We also showed that overexpression of ASCL1 in NSCs increased neuronal differentiation depending on the concentration gradient of growth factors generated in the microfluidic gradient chip. The microfluidic system allowed us to study concentration-dependent effects of growth factors within a single device, while a traditional system requires multiple independent cultures using fixed growth factor concentrations. Our study suggests that the microfluidic gradient-generating chip is a powerful tool for determining the optimal culture conditions.

PREDICTION OF BULLS’ SLAUGHTER VALUE FROM GROWTH DATA USING ARTIFICIAL NEURAL NETWORK

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Krzysztof ADAMCZYK

2006-02-01

Full Text Available The objective of this research was to investigate the usefulness of artifi cial neural network (ANN in the prediction of slaughter value of young crossbred bulls based on growth data. The studies were carried out on 104 bulls fattened from 120 days of life until the weight of 500 kg. The bulls were group fed using mainly farm feeds. After slaughter the carcasses were dissected and meat was subjected to physico-chemical and organoleptic analyses. The obtained data were used for the development of an artifi cial neural network model of slaughter value prediction. It was found that some slaughter value traits (hot carcass, cold half-carcass, neck and round weights, bone content in dissected elements in half-carcass, meat pH, dry-matter and protein contents in meat and meat tenderness and juiciness can be predicted with a considerably high accuracy using the artifi cial neural network.

Covalent growth factor tethering to direct neural stem cell differentiation and self-organization.

Science.gov (United States)

Ham, Trevor R; Farrag, Mahmoud; Leipzig, Nic D

2017-04-15

Tethered growth factors offer exciting new possibilities for guiding stem cell behavior. However, many of the current methods present substantial drawbacks which can limit their application and confound results. In this work, we developed a new method for the site-specific covalent immobilization of azide-tagged growth factors and investigated its utility in a model system for guiding neural stem cell (NSC) behavior. An engineered interferon-γ (IFN-γ) fusion protein was tagged with an N-terminal azide group, and immobilized to two different dibenzocyclooctyne-functionalized biomimetic polysaccharides (chitosan and hyaluronan). We successfully immobilized azide-tagged IFN-γ under a wide variety of reaction conditions, both in solution and to bulk hydrogels. To understand the interplay between surface chemistry and protein immobilization, we cultured primary rat NSCs on both materials and showed pronounced biological effects. Expectedly, immobilized IFN-γ increased neuronal differentiation on both materials. Expression of other lineage markers varied depending on the material, suggesting that the interplay of surface chemistry and protein immobilization plays a large role in nuanced cell behavior. We also investigated the bioactivity of immobilized IFN-γ in a 3D environment in vivo and found that it sparked the robust formation of neural tube-like structures from encapsulated NSCs. These findings support a wide range of potential uses for this approach and provide further evidence that adult NSCs are capable of self-organization when exposed to the proper microenvironment. For stem cells to be used effectively in regenerative medicine applications, they must be provided with the appropriate cues and microenvironment so that they integrate with existing tissue. This study explores a new method for guiding stem cell behavior: covalent growth factor tethering. We found that adding an N-terminal azide-tag to interferon-γ enabled stable and robust Cu-free 'click

The rapid growth of OPEC′s domestic oil consumption

International Nuclear Information System (INIS)

Gately, Dermot; Al-Yousef, Nourah; Al-Sheikh, Hamad M.H.

2013-01-01

OPEC′s domestic oil consumption has increased seven-fold in 40 years, to 8.5 million barrels per day (mbd). They consume almost as much oil as China. This constitutes one-fourth of their production. Such rapid growth in consumption (5.1% annually, faster than their income growth of 3.1%) will challenge OPEC′s ability to increase their oil exports, which are relied upon in long-term world oil projections by the International Energy Agency (IEA), US Department of Energy (DOE/EIA) and British Petroleum (BP). However, these institutions assume unprecedented slowdowns in OPEC oil consumption – to less than 2% in the future – allowing them to project increases in OPEC oil exports with only modest increases in production. We analyze 1971–2010 data econometrically, with panel co-integration methods. We estimate that the income elasticity of consumption is about 1 for energy and oil. This means that OPEC′s energy and oil consumption will grow as rapidly as their income. Hence, continued high growth rates for domestic oil consumption are more likely than the unprecedented slowdowns projected by IEA, DOE/EIA and BP – adding an extra 6 mbd of OPEC consumption in 2030. This will have major implications for OPEC production and export levels, and for world oil prices. -- Highlights: •We analyze rapid growth of OPEC oil consumption (sevenfold since 1971: 5.1% annually). •Panel co-integration econometric estimate of income elasticity about 1.0. •Consensus projections (IEA, DOE/EIA) have consistently under projected OPEC consumption. •Future oil market implications if OPEC consumption grows as fast as income (as in past)

Armenia; The Road to Sustained Rapid Growth-Cross-Country Evidence

OpenAIRE

Garbis Iradian

2003-01-01

This study examines the growth determinants and the economic policy challenges that Armenia faces to sustain the rapid growth of the past two years. The paper also seeks to answer the following two questions: Why has Armenia performed relatively better than other transition economies? What are the roles of macroeconomic policies and the level of financial intermediation in explaining growth differences? The paper also draws upon past cross-country experiences by estimating panel regressions o...

[Rapid Identification of Epicarpium Citri Grandis via Infrared Spectroscopy and Fluorescence Spectrum Imaging Technology Combined with Neural Network].

Science.gov (United States)

Pan, Sha-sha; Huang, Fu-rong; Xiao, Chi; Xian, Rui-yi; Ma, Zhi-guo

2015-10-01

To explore rapid reliable methods for detection of Epicarpium citri grandis (ECG), the experiment using Fourier Transform Attenuated Total Reflection Infrared Spectroscopy (FTIR/ATR) and Fluorescence Spectrum Imaging Technology combined with Multilayer Perceptron (MLP) Neural Network pattern recognition, for the identification of ECG, and the two methods are compared. Infrared spectra and fluorescence spectral images of 118 samples, 81 ECG and 37 other kinds of ECG, are collected. According to the differences in tspectrum, the spectra data in the 550-1 800 cm(-1) wavenumber range and 400-720 nm wavelength are regarded as the study objects of discriminant analysis. Then principal component analysis (PCA) is applied to reduce the dimension of spectroscopic data of ECG and MLP Neural Network is used in combination to classify them. During the experiment were compared the effects of different methods of data preprocessing on the model: multiplicative scatter correction (MSC), standard normal variable correction (SNV), first-order derivative(FD), second-order derivative(SD) and Savitzky-Golay (SG). The results showed that: after the infrared spectra data via the Savitzky-Golay (SG) pretreatment through the MLP Neural Network with the hidden layer function as sigmoid, we can get the best discrimination of ECG, the correct percent of training set and testing set are both 100%. Using fluorescence spectral imaging technology, corrected by the multiple scattering (MSC) results in the pretreatment is the most ideal. After data preprocessing, the three layers of the MLP Neural Network of the hidden layer function as sigmoid function can get 100% correct percent of training set and 96.7% correct percent of testing set. It was shown that the FTIR/ATR and fluorescent spectral imaging technology combined with MLP Neural Network can be used for the identification study of ECG and has the advantages of rapid, reliable effect.

The effect of the neural activity on topological properties of growing neural networks.

Science.gov (United States)

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Laminin enhances the growth of human neural stem cells in defined culture media

Directory of Open Access Journals (Sweden)

Lathia Justin D

2008-07-01

Full Text Available Abstract Background Human neural stem cells (hNSC have the potential to provide novel cell-based therapies for neurodegenerative conditions such as multiple sclerosis and Parkinson's disease. In order to realise this goal, protocols need to be developed that allow for large quantities of hNSC to be cultured efficiently. As such, it is important to identify factors which enhance the growth of hNSC. In vivo, stem cells reside in distinct microenvironments or niches that are responsible for the maintenance of stem cell populations. A common feature of niches is the presence of the extracellular matrix molecule, laminin. Therefore, this study investigated the effect of exogenous laminin on hNSC growth. Results To measure hNSC growth, we established culture conditions using B27-supplemented medium that enable neurospheres to grow from human neural cells plated at clonal densities. Limiting dilution assays confirmed that neurospheres were derived from single cells at these densities. Laminin was found to increase hNSC numbers as measured by this neurosphere formation. The effect of laminin was to augment the proliferation/survival of the hNSC, rather than promoting the undifferentiated state. In agreement, apoptosis was reduced in dissociated neurospheres by laminin in an integrin β1-dependent manner. Conclusion The addition of laminin to the culture medium enhances the growth of hNSC, and may therefore aid their large-scale production.

Neural network and parton two fireball model for pseudo-rapidity distribution in proton-proton collision

International Nuclear Information System (INIS)

El-Bakry, M.Y.

2000-01-01

Pseudo-Rapidity distribution of created pions from proton-proton (p-p) interaction has been studied in the framework of artificial neural network (ANN) and the parton two fireball model (PTFM). The predicted distributions from the ANN based model and the parton two fireball model is compared with the corresponding experimental results. The ANN model has proved better matching for experimental data specially at high energies where the conventional two fireball model representation deteriorates

Rapid hydrogen hydrate growth from non-stoichiometric tuning mixtures during liquid nitrogen quenching.

Science.gov (United States)

Grim, R Gary; Kerkar, Prasad B; Sloan, E Dendy; Koh, Carolyn A; Sum, Amadeu K

2012-06-21

In this study the rapid growth of sII H(2) hydrate within 20 min of post formation quenching towards liquid nitrogen (LN(2)) temperature is presented. Initially at 72 MPa and 258 K, hydrate samples would cool to the conditions of ~60 MPa and ~90 K after quenching. Although within the stability region for H(2) hydrate, new hydrate growth only occurred under LN(2) quenching of the samples when preformed hydrate "seeds" of THF + H(2) were in the presence of unconverted ice. The characterization of hydrate seeds and the post-quenched samples was performed with confocal Raman spectroscopy. These results suggest that quenching to LN(2) temperature, a common preservation technique for ex situ hydrate analysis, can lead to rapid unintended hydrate growth. Specifically, guest such as H(2) that may otherwise need sufficiently long induction periods to nucleate, may still experience rapid growth through an increased kinetic effect from a preformed hydrate template.

Neural networks

International Nuclear Information System (INIS)

Denby, Bruce; Lindsey, Clark; Lyons, Louis

1992-01-01

The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

PLZF regulates fibroblast growth factor responsiveness and maintenance of neural progenitors.

Science.gov (United States)

Gaber, Zachary B; Butler, Samantha J; Novitch, Bennett G

2013-10-01

Distinct classes of neurons and glial cells in the developing spinal cord arise at specific times and in specific quantities from spatially discrete neural progenitor domains. Thus, adjacent domains can exhibit marked differences in their proliferative potential and timing of differentiation. However, remarkably little is known about the mechanisms that account for this regional control. Here, we show that the transcription factor Promyelocytic Leukemia Zinc Finger (PLZF) plays a critical role shaping patterns of neuronal differentiation by gating the expression of Fibroblast Growth Factor (FGF) Receptor 3 and responsiveness of progenitors to FGFs. PLZF elevation increases FGFR3 expression and STAT3 pathway activity, suppresses neurogenesis, and biases progenitors towards glial cell production. In contrast, PLZF loss reduces FGFR3 levels, leading to premature neuronal differentiation. Together, these findings reveal a novel transcriptional strategy for spatially tuning the responsiveness of distinct neural progenitor groups to broadly distributed mitogenic signals in the embryonic environment.

Pre-treatment growth and IGF-I deficiency as main predictors of response to growth hormone therapy in neural models

Directory of Open Access Journals (Sweden)

Urszula Smyczyn´ska

2018-01-01

Full Text Available Mathematical models have been applied in prediction of growth hormone treatment effectiveness in children since the end of 1990s. Usually they were multiple linear regression models; however, there are also examples derived by empirical non-linear methods. Proposed solution consists in application of machine learning technique – artificial neural networks – to analyse this problem. This new methodology, contrary to previous ones, allows detection of both linear and non-linear dependencies without assuming their character a priori. The aims of this work included: development of models predicting separately growth during 1st year of treatment and final height as well as identification of important predictors and in-depth analysis of their influence on treatment’s effectiveness. The models were derived on the basis of clinical data of 272 patients treated for at least 1 year, 133 of whom have already attained final height. Starting from models containing 17 and 20 potential predictors, respectively for 1st year and final height model, we were able to reduce their number to 9 and 10. Basing on the final models, IGF-I concentration and earlier growth were indicated as belonging to most important predictors of response to GH therapy, while results of GH secretion tests were automatically excluded as insignificant. Moreover, majority of the dependencies were observed to be non-linear, thus using neural networks seems to be reasonable approach despite it being more complex than previously applied methods.

Rapid Growth of Uropathogenic Escherichia coli during Human Urinary Tract Infection

Directory of Open Access Journals (Sweden)

Valerie S. Forsyth

2018-03-01

Full Text Available Uropathogenic Escherichia coli (UPEC strains cause most uncomplicated urinary tract infections (UTIs. These strains are a subgroup of extraintestinal pathogenic E. coli (ExPEC strains that infect extraintestinal sites, including urinary tract, meninges, bloodstream, lungs, and surgical sites. Here, we hypothesize that UPEC isolates adapt to and grow more rapidly within the urinary tract than other E. coli isolates and survive in that niche. To date, there has not been a reliable method available to measure their growth rate in vivo. Here we used two methods: segregation of nonreplicating plasmid pGTR902, and peak-to-trough ratio (PTR, a sequencing-based method that enumerates bacterial chromosomal replication forks present during cell division. In the murine model of UTI, UPEC strain growth was robust in vivo, matching or exceeding in vitro growth rates and only slowing after reaching high CFU counts at 24 and 30 h postinoculation (hpi. In contrast, asymptomatic bacteriuria (ABU strains tended to maintain high growth rates in vivo at 6, 24, and 30 hpi, and population densities did not increase, suggesting that host responses or elimination limited population growth. Fecal strains displayed moderate growth rates at 6 hpi but did not survive to later times. By PTR, E. coli in urine of human patients with UTIs displayed extraordinarily rapid growth during active infection, with a mean doubling time of 22.4 min. Thus, in addition to traditional virulence determinants, including adhesins, toxins, iron acquisition, and motility, very high growth rates in vivo and resistance to the innate immune response appear to be critical phenotypes of UPEC strains.

Neural stem cell-encoded temporal patterning delineates an early window of malignant susceptibility in Drosophila.

Science.gov (United States)

Narbonne-Reveau, Karine; Lanet, Elodie; Dillard, Caroline; Foppolo, Sophie; Chen, Ching-Huan; Parrinello, Hugues; Rialle, Stéphanie; Sokol, Nicholas S; Maurange, Cédric

2016-06-14

Pediatric neural tumors are often initiated during early development and can undergo very rapid transformation. However, the molecular basis of this early malignant susceptibility remains unknown. During Drosophila development, neural stem cells (NSCs) divide asymmetrically and generate intermediate progenitors that rapidly differentiate in neurons. Upon gene inactivation, these progeny can dedifferentiate and generate malignant tumors. Here, we find that intermediate progenitors are prone to malignancy only when born during an early window of development while expressing the transcription factor Chinmo, and the mRNA-binding proteins Imp/IGF2BP and Lin-28. These genes compose an oncogenic module that is coopted upon dedifferentiation of early-born intermediate progenitors to drive unlimited tumor growth. In late larvae, temporal transcription factor progression in NSCs silences the module, thereby limiting mitotic potential and terminating the window of malignant susceptibility. Thus, this study identifies the gene regulatory network that confers malignant potential to neural tumors with early developmental origins.

Improved Neural Signal Classification in a Rapid Serial Visual Presentation Task Using Active Learning.

Science.gov (United States)

Marathe, Amar R; Lawhern, Vernon J; Wu, Dongrui; Slayback, David; Lance, Brent J

2016-03-01

The application space for brain-computer interface (BCI) technologies is rapidly expanding with improvements in technology. However, most real-time BCIs require extensive individualized calibration prior to use, and systems often have to be recalibrated to account for changes in the neural signals due to a variety of factors including changes in human state, the surrounding environment, and task conditions. Novel approaches to reduce calibration time or effort will dramatically improve the usability of BCI systems. Active Learning (AL) is an iterative semi-supervised learning technique for learning in situations in which data may be abundant, but labels for the data are difficult or expensive to obtain. In this paper, we apply AL to a simulated BCI system for target identification using data from a rapid serial visual presentation (RSVP) paradigm to minimize the amount of training samples needed to initially calibrate a neural classifier. Our results show AL can produce similar overall classification accuracy with significantly less labeled data (in some cases less than 20%) when compared to alternative calibration approaches. In fact, AL classification performance matches performance of 10-fold cross-validation (CV) in over 70% of subjects when training with less than 50% of the data. To our knowledge, this is the first work to demonstrate the use of AL for offline electroencephalography (EEG) calibration in a simulated BCI paradigm. While AL itself is not often amenable for use in real-time systems, this work opens the door to alternative AL-like systems that are more amenable for BCI applications and thus enables future efforts for developing highly adaptive BCI systems.

Application of artificial neural network with extreme learning machine for economic growth estimation

Science.gov (United States)

Milačić, Ljubiša; Jović, Srđan; Vujović, Tanja; Miljković, Jovica

2017-01-01

The purpose of this research is to develop and apply the artificial neural network (ANN) with extreme learning machine (ELM) to forecast gross domestic product (GDP) growth rate. The economic growth forecasting was analyzed based on agriculture, manufacturing, industry and services value added in GDP. The results were compared with ANN with back propagation (BP) learning approach since BP could be considered as conventional learning methodology. The reliability of the computational models was accessed based on simulation results and using several statistical indicators. Based on results, it was shown that ANN with ELM learning methodology can be applied effectively in applications of GDP forecasting.

Rapid growth and childhood obesity are strongly associated with lysoPC(14:0).

Science.gov (United States)

Rzehak, Peter; Hellmuth, Christian; Uhl, Olaf; Kirchberg, Franca F; Peissner, Wolfgang; Harder, Ulrike; Grote, Veit; Weber, Martina; Xhonneux, Annick; Langhendries, Jean-Paul; Ferre, Natalia; Closa-Monasterolo, Ricardo; Verduci, Elvira; Riva, Enrica; Socha, Piotr; Gruszfeld, Dariusz; Koletzko, Berthold

2014-01-01

Despite the growing interest in the early-origins-of-later-disease hypothesis, little is known about the metabolic underpinnings linking infant weight gain and childhood obesity. To discover biomarkers reflective of weight change in the first 6 months and overweight/obesity at age 6 years via a targeted metabolomics approach. This analysis comprised 726 infants from a European multicenter randomized trial (Childhood Obesity Programme, CHOP) for whom plasma blood samples at age 6 months and anthropometric data up to the age of 6 years were available. 'Rapid growth' was defined as a positive difference in weight within the first 6 months of life standardized to WHO growth standards. Weight change was regressed on each of 168 metabolites (acylcarnitines, lysophosphatidylcholines, sphingomyelins, and amino acids). Metabolites significant after Bonferroni's correction were tested as predictors of later overweight/obesity. Among the overall 19 significant metabolites, 4 were associated with rapid growth and 15 were associated with a less-than-ideal weight change. After adjusting for feeding group, only the lysophosphatidylcholine LPCaC14:0 remained significantly associated with rapid weight gain (β = 0.18). Only LPCaC14:0 at age 6 months was predictive of overweight/obesity at age 6 years (OR 1.33; 95% CI 1.04-1.69). LPCa14:0 is strongly related to rapid growth in infancy and childhood overweight/obesity. This suggests that LPCaC14:0 levels may represent a metabolically programmed effect of infant weight gain on the later obesity risk. However, these results require confirmation by independent cohorts. © 2014 S. Karger AG, Basel.

Rapid growth, maturity, current problems, future prospects of NAA

International Nuclear Information System (INIS)

Guinn, V.P.

2000-01-01

The early rapid growth, the attainment of maturity, current problems, and future prospects of NAA (neutron activation analysis) are discussed, each in reasonable detail. In particular, the nature and causes of its current problems are examined, and suggestions are presented for the solution of these problems. The author believes that vigorous action in suggested areas of concentration can reinvigorate the status of NAA as an important method of elemental analysis. (author)

Layers and Multilayers of Self-Assembled Polymers: Tunable Engineered Extracellular Matrix Coatings for Neural Cell Growth.

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Landry, Michael J; Rollet, Frédéric-Guillaume; Kennedy, Timothy E; Barrett, Christopher J

2018-03-12

Growing primary cells and tissue in long-term cultures, such as primary neural cell culture, presents many challenges. A critical component of any environment that supports neural cell growth in vivo is an appropriate 2-D surface or 3-D scaffold, typically in the form of a thin polymer layer that coats an underlying plastic or glass substrate and aims to mimic critical aspects of the extracellular matrix. A fundamental challenge to mimicking a hydrophilic, soft natural cell environment is that materials with these properties are typically fragile and are difficult to adhere to and stabilize on an underlying plastic or glass cell culture substrate. In this review, we highlight the current state of the art and overview recent developments of new artificial extracellular matrix (ECM) surfaces for in vitro neural cell culture. Notably, these materials aim to strike a balance between being hydrophilic and soft while also being thick, stable, robust, and bound well to the underlying surface to provide an effective surface to support long-term cell growth. We focus on improved surface and scaffold coating systems that can mimic the natural physicochemical properties that enhance neuronal survival and growth, applied as soft hydrophilic polymer coatings for both in vitro cell culture and for implantable neural probes and 3-D matrixes that aim to enhance stability and longevity to promote neural biocompatibility in vivo. With respect to future developments, we outline four emerging principles that serve to guide the development of polymer assemblies that function well as artificial ECMs: (a) design inspired by biological systems and (b) the employment of principles of aqueous soft bonding and self-assembly to achieve (c) a high-water-content gel-like coating that is stable over time in a biological environment and possesses (d) a low modulus to more closely mimic soft, compliant real biological tissue. We then highlight two emerging classes of thick material coatings that

Governing Rapid Growth in Asia: State-led Development in Historical Perspective

NARCIS (Netherlands)

T-W. Ngo (Tak-Wing)

2009-01-01

textabstractRapid growth in Asia has often been explained in terms of effective policies pursued by a “developmental state”. In particular, countries in East Asia are said to be characterized by the presence of a strong state with technocratic capacity and social embeddedness. This inaugural address

Polygenic Risk, Rapid Childhood Growth, and the Development of Obesity

Science.gov (United States)

Belsky, Daniel W.; Moffitt, Terrie E.; Houts, Renate; Bennett, Gary G.; Biddle, Andrea K.; Blumenthal, James A.; Evans, James P.; Harrington, HonaLee; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Caspi, Avshalom

2012-01-01

Objective To test how genomic loci identified in genome-wide association studies influence the development of obesity. Design A 38-year prospective longitudinal study of a representative birth cohort. Setting The Dunedin Multidisciplinary Health and Development Study, Dunedin, New Zealand. Participants One thousand thirty-seven male and female study members. Main Exposures We assessed genetic risk with a multilocus genetic risk score. The genetic risk score was composed of single-nucleotide polymorphisms identified in genome-wide association studies of obesity-related phenotypes. We assessed family history from parent body mass index data collected when study members were 11 years of age. Main Outcome Measures Body mass index growth curves, developmental phenotypes of obesity, and adult obesity outcomes were defined from anthropometric assessments at birth and at 12 subsequent in-person interviews through 38 years of age. Results Individuals with higher genetic risk scores were more likely to be chronically obese in adulthood. Genetic risk first manifested as rapid growth during early childhood. Genetic risk was unrelated to birth weight. After birth, children at higher genetic risk gained weight more rapidly and reached adiposity rebound earlier and at a higher body mass index. In turn, these developmental phenotypes predicted adult obesity, mediating about half the genetic effect on adult obesity risk. Genetic associations with growth and obesity risk were independent of family history, indicating that the genetic risk score could provide novel information to clinicians. Conclusions Genetic variation linked with obesity risk operates, in part, through accelerating growth in the early childhood years after birth. Etiological research and prevention strategies should target early childhood to address the obesity epidemic. PMID:22665028

Neural mechanisms of rapid sensitivity to syntactic anomaly

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Albert E. Kim

2013-03-01

Full Text Available Recent psycholinguistic models hypothesize that anticipatory processing can speed the response to linguistic input during language comprehension by pre-activating representations necessary for word recognition. We investigated the neurocognitive mechanisms of anticipatory processing by recording event-related brain responses (ERPs to syntactically anomalous (The thief was caught by for police and well-formed (e.g., The thief was caught by the police sentences. One group of participants saw anomalies elicited by the same word in every instance (e.g., for; low-variability stimuli, providing high affordances for predictions about the word-form appearing in the critical position. A second group saw anomalies elicited by seven different prepositions (at, of, on, for, from, over, with; high-variability stimuli across the study, creating a more difficult prediction task. Syntactic category anomalies enhanced the occipital-temporal N170 component of the ERP, indicating rapid sensitivity—within 200 ms of word onset—to syntactic anomaly. For low-variability but not the high-variability stimuli, syntactic anomaly also enhanced the earlier occipital-temporal P1 component, around 130 ms after word-onset, indicating that affordances for prediction engendered earlier sensitivity to syntactic anomaly. Independent components analysis revealed three sources within the ERP signal whose functional dynamics were consistent with predictive processing and early responses to syntactic anomaly. Distributed neural source modeling (sLORETA of these early-active sources produced a candidate network for early responses to words during reading in the right posterior-occipital, left occipital-temporal, and medial parietal cortex.

All-trans retinoic acid promotes neural lineage entry by pluripotent embryonic stem cells via multiple pathways

Directory of Open Access Journals (Sweden)

Fang Bo

2009-07-01

Full Text Available Abstract Background All-trans retinoic acid (RA is one of the most important morphogens with pleiotropic actions. Its embryonic distribution correlates with neural differentiation in the developing central nervous system. To explore the precise effects of RA on neural differentiation of mouse embryonic stem cells (ESCs, we detected expression of RA nuclear receptors and RA-metabolizing enzymes in mouse ESCs and investigated the roles of RA in adherent monolayer culture. Results Upon addition of RA, cell differentiation was directed rapidly and exclusively into the neural lineage. Conversely, pharmacological interference with RA signaling suppressed this neural differentiation. Inhibition of fibroblast growth factor (FGF signaling did not suppress significantly neural differentiation in RA-treated cultures. Pharmacological interference with extracellular signal-regulated kinase (ERK pathway or activation of Wnt pathway effectively blocked the RA-promoted neural specification. ERK phosphorylation was enhanced in RA-treated cultures at the early stage of differentiation. Conclusion RA can promote neural lineage entry by ESCs in adherent monolayer culture systems. This effect depends on RA signaling and its crosstalk with the ERK and Wnt pathways.

Rapid identification and classification of Listeria spp. and serotype assignment of Listeria monocytogenes using fourier transform-infrared spectroscopy and artificial neural network analysis

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The use of Fourier Transform-Infrared Spectroscopy (FT-IR) in conjunction with Artificial Neural Network software, NeuroDeveloper™ was examined for the rapid identification and classification of Listeria species and serotyping of Listeria monocytogenes. A spectral library was created for 245 strains...

Rapid fluctuations in extracellular brain glucose levels induced by natural arousing stimuli and intravenous cocaine: fueling the brain during neural activation

Science.gov (United States)

Lenoir, Magalie

2012-01-01

Glucose, a primary energetic substrate for neural activity, is continuously influenced by two opposing forces that tend to either decrease its extracellular levels due to enhanced utilization in neural cells or increase its levels due to entry from peripheral circulation via enhanced cerebral blood flow. How this balance is maintained under physiological conditions and changed during neural activation remains unclear. To clarify this issue, enzyme-based glucose sensors coupled with high-speed amperometry were used in freely moving rats to evaluate fluctuations in extracellular glucose levels induced by brief audio stimulus, tail pinch (TP), social interaction with another rat (SI), and intravenous cocaine (1 mg/kg). Measurements were performed in nucleus accumbens (NAcc) and substantia nigra pars reticulata (SNr), which drastically differ in neuronal activity. In NAcc, where most cells are powerfully excited after salient stimulation, glucose levels rapidly (latency 2–6 s) increased (30–70 μM or 6–14% over baseline) by all stimuli; the increase differed in magnitude and duration for each stimulus. In SNr, where most cells are transiently inhibited by salient stimuli, TP, SI, and cocaine induced a biphasic glucose response, with the initial decrease (−20–40 μM or 5–10% below baseline) followed by a reboundlike increase. The critical role of neuronal activity in mediating the initial glucose response was confirmed by monitoring glucose currents after local microinjections of glutamate (GLU) or procaine (PRO). While intra-NAcc injection of GLU transiently increased glucose levels in this structure, intra-SNr PRO injection resulted in rapid, transient decreases in SNr glucose. Therefore, extracellular glucose levels in the brain change very rapidly after physiological and pharmacological stimulation, the response is structure specific, and the pattern of neuronal activity appears to be a critical factor determining direction and magnitude of physiological

Photopolymerized materials and patterning for improved performance of neural prosthetics

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Tuft, Bradley William

Neural prosthetics are used to replace or substantially augment remaining motor and sensory functions of neural pathways that were lost or damaged due to physical trauma, disease, or genetics. However, due to poor spatial signal resolution, neural prostheses fail to recapitulate the intimate, precise interactions inherent to neural networks. Designing materials and interfaces that direct de novo nerve growth to spatially specific stimulating elements is, therefore, a promising method to enhance signal specificity and performance of prostheses such as the successful cochlear implant (CI) and the developing retinal implant. In this work, the spatial and temporal reaction control inherent to photopolymerization was used to develop methods to generate micro and nanopatterned materials that direct neurite growth from prosthesis relevant neurons. In particular, neurite growth and directionality has been investigated in response to physical, mechanical, and chemical cues on photopolymerized surfaces. Spiral ganglion neurons (SGNs) serve as the primary neuronal model as they are the principal target for CI stimulation. The objective of the research is to rationally design materials that spatially direct neurite growth and to translate fundamental understanding of nerve cell-material interactions into methods of nerve regeneration that improve neural prosthetic performance. A rapid, single-step photopolymerization method was developed to fabricate micro and nanopatterned physical cues on methacrylate surfaces by selectively blocking light with photomasks. Feature height is readily tuned by modulating parameters of the photopolymerizaiton including initiator concentration and species, light intensity, separation distance from the photomask, and radiation exposure time. Alignment of neural elements increases significantly with increasing feature amplitude and constant periodicity, as well as with decreasing periodicity and constant amplitude. SGN neurite alignment strongly

Neural evidence reveals the rapid effects of reward history on selective attention.

Science.gov (United States)

MacLean, Mary H; Giesbrecht, Barry

2015-05-05

Selective attention is often framed as being primarily driven by two factors: task-relevance and physical salience. However, factors like selection and reward history, which are neither currently task-relevant nor physically salient, can reliably and persistently influence visual selective attention. The current study investigated the nature of the persistent effects of irrelevant, physically non-salient, reward-associated features. These features affected one of the earliest reliable neural indicators of visual selective attention in humans, the P1 event-related potential, measured one week after the reward associations were learned. However, the effects of reward history were moderated by current task demands. The modulation of visually evoked activity supports the hypothesis that reward history influences the innate salience of reward associated features, such that even when no longer relevant, nor physically salient, these features have a rapid, persistent, and robust effect on early visual selective attention. Copyright © 2015 Elsevier B.V. All rights reserved.

The performance studies of DKDP crystals grown by a rapid horizontal growth method

Science.gov (United States)

Xie, Xiaoyi; Qi, Hongji; Wang, Bin; Wang, Hu; Chen, Duanyang; Shao, Jianda

2018-04-01

A deuterated potassium dihydrogen phosphate (DKDP) crystal with about 70% deuterium level was grown by a rapid horizontal growth method with independent design equipment, which includes a continuous filtration system. The cooling program during crystal growth was designed according to a self-developed software to catch the size of growing crystal in real time. The crystal structure, optical performance and laser induced damage threshold (LIDT) of this DKDP crystal were investigated in this paper. The deuterium concentration of the crystal was confirmed by the neutron diffraction technique, which was effective and available in determining a complete range of deuteration level. The dielectric property was measured to evaluate the perfection of the lattice. The transmittance and LIDT were carried out further to evaluate the optical and functional properties of this DKDP crystal grown in the rapid horizontal growth technique. All of the detailed characterization for DKDP figured out that the 70% deuterated KDP crystal grown in this way had relatively good qualities.

Neural changes underlying early stages of L2 vocabulary acquisition.

Science.gov (United States)

Pu, He; Holcomb, Phillip J; Midgley, Katherine J

2016-11-01

Research has shown neural changes following second language (L2) acquisition after weeks or months of instruction. But are such changes detectable even earlier than previously shown? The present study examines the electrophysiological changes underlying the earliest stages of second language vocabulary acquisition by recording event-related potentials (ERPs) within the first week of learning. Adult native English speakers with no previous Spanish experience completed less than four hours of Spanish vocabulary training, with pre- and post-training ERPs recorded to a backward translation task. Results indicate that beginning L2 learners show rapid neural changes following learning, manifested in changes to the N400 - an ERP component sensitive to lexicosemantic processing and degree of L2 proficiency. Specifically, learners in early stages of L2 acquisition show growth in N400 amplitude to L2 words following learning as well as a backward translation N400 priming effect that was absent pre-training. These results were shown within days of minimal L2 training, suggesting that the neural changes captured during adult second language acquisition are more rapid than previously shown. Such findings are consistent with models of early stages of bilingualism in adult learners of L2 ( e.g. Kroll and Stewart's RHM) and reinforce the use of ERP measures to assess L2 learning.

Water hammer due to rapid bubble growth at a severe accident

International Nuclear Information System (INIS)

Aya, Izuo; Adachi, Masaki; Shiozaki, Koki; Inasaka, Fujio

2000-01-01

On a severe accident of the light water reactor (LWR), by steam explosion and so forth due to hydrogen formation by water-metal reaction and direct contact of molted core with water, it is presumed that a lot of vapor forms for a short time in water at reactor vessel and under part of containment vessel. This study aims at and carries out, under reference of the conventional study results, experimental elucidation on coherence of water block motion due to rapid bubble growth, proposal on reduction method of water hammering, development of water hammer estimating method in an actual reactor, and proposal for upgrading of reliability on severe accident evaluation. In 1998 fiscal year, an 'Experimental apparatus on water hammering elements on sever accident' simulated rapid bubble growth due to steam explosion by injecting high pressure air into water was produced to carry out its function test. As a result of the carried out function tests, extreme water hammering phenomena were observed, by which validity of establishment on the study objects could be confirmed. (G.K.)

Growth perturbations in a phenotype with rapid fetal growth preceding preterm labor and term birth.

Science.gov (United States)

Lampl, Michelle; Kusanovic, Juan Pedro; Erez, Offer; Gotsch, Francesca; Espinoza, Jimmy; Goncalves, Luis; Lee, Wesley; Gomez, Ricardo; Nien, Jyh Kae; Frongillo, Edward A; Romero, Roberto

2009-01-01

The variability in fetal growth rates and gestation duration in humans is not well understood. Of interest are women presenting with an episode of preterm labor and subsequently delivering a term neonate, who is small relative to peers of similar gestational age. To further understand these relationships, fetal growth patterns predating an episode of preterm labor were investigated. Retrospective analysis of fetal biometry assessed by serial ultrasound in a prospectively studied sample of pregnancies in Santiago, Chile, tested the hypothesis that fetal growth patterns among uncomplicated pregnancies (n = 3,706) and those with an episode of preterm labor followed by term delivery (n = 184) were identical across the time intervals 16-22 weeks, 22-28 weeks, and 28-34 weeks in a multilevel mixed-effects regression. The hypothesis was not supported. Fetal weight growth rate was faster from 16 weeks among pregnancies with an episode of preterm labor (P < 0.05), declined across midgestation (22-28 weeks, P < 0.05), and rebounded between 28 and 34 weeks (P = 0.06). This was associated with perturbations in abdominal circumference growth and proportionately larger biparietal diameter from 22 gestational weeks (P = 0.03), greater femur (P = 0.01), biparietal diameter (P = 0.001) and head circumference (P = 0.02) dimensions relative to abdominal circumference across midgestation (22-28 weeks), followed by proportionately smaller femur diaphyseal length (P = 0.02) and biparietal diameter (P = 0.03) subsequently. A distinctive rapid growth phenotype characterized fetal growth preceding an episode of preterm labor among this sample of term-delivered neonates. Perturbations in abdominal circumference growth and patterns of proportionality suggest an altered growth strategy pre-dating the preterm labor episode.

Rapid growth of the US wildland-urban interface raises wildfire risk.

Science.gov (United States)

Radeloff, Volker C; Helmers, David P; Kramer, H Anu; Mockrin, Miranda H; Alexandre, Patricia M; Bar-Massada, Avi; Butsic, Van; Hawbaker, Todd J; Martinuzzi, Sebastián; Syphard, Alexandra D; Stewart, Susan I

2018-03-27

The wildland-urban interface (WUI) is the area where houses and wildland vegetation meet or intermingle, and where wildfire problems are most pronounced. Here we report that the WUI in the United States grew rapidly from 1990 to 2010 in terms of both number of new houses (from 30.8 to 43.4 million; 41% growth) and land area (from 581,000 to 770,000 km 2 ; 33% growth), making it the fastest-growing land use type in the conterminous United States. The vast majority of new WUI areas were the result of new housing (97%), not related to an increase in wildland vegetation. Within the perimeter of recent wildfires (1990-2015), there were 286,000 houses in 2010, compared with 177,000 in 1990. Furthermore, WUI growth often results in more wildfire ignitions, putting more lives and houses at risk. Wildfire problems will not abate if recent housing growth trends continue.

Roles of neural stem cells in the repair of peripheral nerve injury.

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Wang, Chong; Lu, Chang-Feng; Peng, Jiang; Hu, Cheng-Dong; Wang, Yu

2017-12-01

Currently, researchers are using neural stem cell transplantation to promote regeneration after peripheral nerve injury, as neural stem cells play an important role in peripheral nerve injury repair. This article reviews recent research progress of the role of neural stem cells in the repair of peripheral nerve injury. Neural stem cells can not only differentiate into neurons, astrocytes and oligodendrocytes, but can also differentiate into Schwann-like cells, which promote neurite outgrowth around the injury. Transplanted neural stem cells can differentiate into motor neurons that innervate muscles and promote the recovery of neurological function. To promote the repair of peripheral nerve injury, neural stem cells secrete various neurotrophic factors, including brain-derived neurotrophic factor, fibroblast growth factor, nerve growth factor, insulin-like growth factor and hepatocyte growth factor. In addition, neural stem cells also promote regeneration of the axonal myelin sheath, angiogenesis, and immune regulation. It can be concluded that neural stem cells promote the repair of peripheral nerve injury through a variety of ways.

Rapid Urban Growth and Land Use Patterns in Doha, Qatar: Opportunities for Sustainability?

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Vivek Shandas

2017-06-01

Full Text Available Amidst chaotic growth of Asian cities, the expansion of urban infrastructure in the Middle East's Gulf region is arguably outpacing any other region on the planet. Yet we have a limited understanding of the types of urban form or the extent to which this rapid urbanization is giving rise to sustainable patterns of growth. We ask, what is the pace and character of urban growth in one Middle East city, Doha, Qatar. By using remotely sensed imagery from 1987 to 2013, we examined the pace, quality, and characteristics of urban growth. We further use the results to create a typology of urban growth that integrates historical and spatial dimensions for describing the qualitative aspects of growth and its implications on regional landscapes. Our results suggest that Doha is creating development patterns similar to many Western cities, and that planners may need to consider whether the emerging urban form offers opportunities for more sustainable growth in the future.

Ethanol-induced impairment of polyamine homeostasis – A potential cause of neural tube defect and intrauterine growth restriction in fetal alcohol syndrome

International Nuclear Information System (INIS)

Haghighi Poodeh, Saeid; Alhonen, Leena; Salonurmi, Tuire; Savolainen, Markku J.

2014-01-01

Highlights: • Polyamine pools in embryonic and extraembryonic tissues are developmentally regulated. • Alcohol administration perturbs polyamine levels in the tissues with various patterns. • Total absence of polyamines in the embryo head at 9.5 dpc is critical for development. • The deficiency is associated with reduction in endothelial cell sprouting in the head. • Retarded migration of neural crest cells may cause development of neural tube defect. - Abstract: Introduction: Polyamines play a fundamental role during embryogenesis by regulating cell growth and proliferation and by interacting with RNA, DNA and protein. The polyamine pools are regulated by metabolism and uptake from exogenous sources. The use of certain inhibitors of polyamine synthesis causes similar defects to those seen in alcohol exposure e.g. retarded embryo growth and endothelial cell sprouting. Methods: CD-1 mice received two intraperitoneal injections of 3 g/kg ethanol at 4 h intervals 8.75 days post coitum (dpc). The fetal head, trunk, yolk sac and placenta were collected at 9.5 and 12.5 dpc and polyamine concentrations were determined. Results: No measurable quantity of polyamines could be detected in the embryo head at 9.5 dpc, 12 h after ethanol exposure. Putrescine was not detectable in the trunk of the embryo at that time, whereas polyamines in yolk sac and placenta were at control level. Polyamine deficiency was associated with slow cell growth, reduction in endothelial cell sprouting, an altered pattern of blood vessel network formation and consequently retarded migration of neural crest cells and growth restriction. Discussion: Our results indicate that the polyamine pools in embryonic and extraembryonic tissues are developmentally regulated. Alcohol administration, at the critical stage, perturbs polyamine levels with various patterns, depending on the tissue and its developmental stage. The total absence of polyamines in the embryo head at 9.5 dpc may explain why this

Ethanol-induced impairment of polyamine homeostasis – A potential cause of neural tube defect and intrauterine growth restriction in fetal alcohol syndrome

Energy Technology Data Exchange (ETDEWEB)

Haghighi Poodeh, Saeid, E-mail: saeid.haghighi@oulu.fi [Institute of Clinical Medicine, Department of Internal Medicine, and Biocenter Oulu, University of Oulu, Oulu (Finland); Medical Research Center, Oulu University Hospital, Oulu (Finland); Alhonen, Leena [Department of Biotechnology and Molecular Medicine, A.I. Virtanen Institute for Molecular Sciences, Kuopio (Finland); School of Pharmacy, Biocenter Kuopio, University of Eastern Finland, Kuopio (Finland); Salonurmi, Tuire; Savolainen, Markku J. [Institute of Clinical Medicine, Department of Internal Medicine, and Biocenter Oulu, University of Oulu, Oulu (Finland); Medical Research Center, Oulu University Hospital, Oulu (Finland)

2014-03-28

Highlights: • Polyamine pools in embryonic and extraembryonic tissues are developmentally regulated. • Alcohol administration perturbs polyamine levels in the tissues with various patterns. • Total absence of polyamines in the embryo head at 9.5 dpc is critical for development. • The deficiency is associated with reduction in endothelial cell sprouting in the head. • Retarded migration of neural crest cells may cause development of neural tube defect. - Abstract: Introduction: Polyamines play a fundamental role during embryogenesis by regulating cell growth and proliferation and by interacting with RNA, DNA and protein. The polyamine pools are regulated by metabolism and uptake from exogenous sources. The use of certain inhibitors of polyamine synthesis causes similar defects to those seen in alcohol exposure e.g. retarded embryo growth and endothelial cell sprouting. Methods: CD-1 mice received two intraperitoneal injections of 3 g/kg ethanol at 4 h intervals 8.75 days post coitum (dpc). The fetal head, trunk, yolk sac and placenta were collected at 9.5 and 12.5 dpc and polyamine concentrations were determined. Results: No measurable quantity of polyamines could be detected in the embryo head at 9.5 dpc, 12 h after ethanol exposure. Putrescine was not detectable in the trunk of the embryo at that time, whereas polyamines in yolk sac and placenta were at control level. Polyamine deficiency was associated with slow cell growth, reduction in endothelial cell sprouting, an altered pattern of blood vessel network formation and consequently retarded migration of neural crest cells and growth restriction. Discussion: Our results indicate that the polyamine pools in embryonic and extraembryonic tissues are developmentally regulated. Alcohol administration, at the critical stage, perturbs polyamine levels with various patterns, depending on the tissue and its developmental stage. The total absence of polyamines in the embryo head at 9.5 dpc may explain why this

Low-Temperature and Rapid Growth of Large Single-Crystalline Graphene with Ethane.

Science.gov (United States)

Sun, Xiao; Lin, Li; Sun, Luzhao; Zhang, Jincan; Rui, Dingran; Li, Jiayu; Wang, Mingzhan; Tan, Congwei; Kang, Ning; Wei, Di; Xu, H Q; Peng, Hailin; Liu, Zhongfan

2018-01-01

Future applications of graphene rely highly on the production of large-area high-quality graphene, especially large single-crystalline graphene, due to the reduction of defects caused by grain boundaries. However, current large single-crystalline graphene growing methodologies are suffering from low growth rate and as a result, industrial graphene production is always confronted by high energy consumption, which is primarily caused by high growth temperature and long growth time. Herein, a new growth condition achieved via ethane being the carbon feedstock to achieve low-temperature yet rapid growth of large single-crystalline graphene is reported. Ethane condition gives a growth rate about four times faster than methane, achieving about 420 µm min -1 for the growth of sub-centimeter graphene single crystals at temperature about 1000 °C. In addition, the temperature threshold to obtain graphene using ethane can be reduced to 750 °C, lower than the general growth temperature threshold (about 1000 °C) with methane on copper foil. Meanwhile ethane always keeps higher graphene growth rate than methane under the same growth temperature. This study demonstrates that ethane is indeed a potential carbon source for efficient growth of large single-crystalline graphene, thus paves the way for graphene in high-end electronical and optoelectronical applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid growth of the US wildland-urban interface raises wildfire risk

Science.gov (United States)

Volker C. Radeloff; David P. Helmers; H. Anu Kramer; Miranda H. Mockrin; Patricia M. Alexandre; Avi Bar-Massada; Van Butsic; Todd J. Hawbaker; Sebastián Martinuzzi; Alexandra D. Syphard; Susan I. Stewart

2018-01-01

The wildland-urban interface (WUI) is the area where houses and wildland vegetation meet or intermingle, and where wildfire problems are most pronounced. Here we report that the WUI in the United States grew rapidly from 1990 to 2010 in terms of both number of new houses (from 30.8 to 43.4 million; 41% growth) and land area (from 581,000 to 770,000 km2...

Rapid growth in nitrogen dioxide pollution over Western China, 2005-2013

Science.gov (United States)

Cui, Yuanzheng; Lin, Jintai; Song, Chunqiao; Liu, Mengyao; Yan, Yingying; Xu, Yuan; Huang, Bo

2016-05-01

Western China has experienced rapid industrialization and urbanization since the implementation of the National Western Development Strategies (the "Go West" movement) in 1999. This transition has affected the spatial and temporal characteristics of nitrogen dioxide (NO2) pollution. In this study, we analyze the trends and variability of tropospheric NO2 vertical column densities (VCDs) from 2005 to 2013 over Western China, based on a wavelet analysis on monthly mean NO2 data derived from the Ozone Monitoring Instrument (OMI) measurements. We focus on the anthropogenic NO2 by subtracting region-specific "background" values dominated by natural sources. After removing the background influences, we find significant anthropogenic NO2 growth over Western China between 2005 and 2013 (8.6 ± 0.9 % yr-1 on average, relative to 2005), with the largest increments (15 % yr-1 or more) over parts of several city clusters. The NO2 pollution in most provincial-level regions rose rapidly from 2005 to 2011 but stabilized or declined afterwards. The NO2 trends were driven mainly by changes in anthropogenic emissions, as confirmed by a nested GEOS-Chem model simulation and a comparison with Chinese official emission statistics. The rate of NO2 growth during 2005-2013 reaches 11.3 ± 1.0 % yr-1 over Northwestern China, exceeding the rates over Southwestern China (5.9 ± 0.6 % yr-1) and the three well-known polluted regions in the east (5.3 ± 0.8 % yr-1 over Beijing-Tianjin-Hebei, 4.0 ± 0.6 % yr-1 over the Yangtze River Delta, and -3.3 ± 0.3 % yr-1 over the Pearl River Delta). Subsequent socioeconomic analyses suggest that the rapid NO2 growth over Northwestern China is likely related to the fast developing resource- and pollution-intensive industries along with the "Go West" movement as well as relatively weak emission controls. Further efforts should be made to alleviate NOx pollution to achieve sustainable development in Western China.

Rapid growth in nitrogen dioxide pollution over Western China, 2005-2013

Science.gov (United States)

Cui, Y.-Z.; Lin, J.-T.; Song, C.; Liu, M.-Y.; Yan, Y.-Y.; Xu, Y.; Huang, B.

2015-12-01

Western China has experienced rapid industrialization and urbanization since the implementation of the National Western Development Strategies (the "Go West" movement) in 1999. This transition has affected the spatial and temporal characteristics of nitrogen dioxide (NO2) pollution. In this study, we analyze the trends and variability of tropospheric NO2 vertical column densities (VCDs) from 2005 to 2013 over Western China, based on a wavelet analysis on monthly mean NO2 data derived from the Ozone Monitoring Instrument (OMI) measurements. We focus on the anthropogenic NO2 by subtracting region-specific "background" values dominated by natural sources. We find significant NO2 growth over Western China between 2005 and 2013 (8.6 ± 0.9 % yr-1 on average, relative to 2005), with the largest increments (15 % yr-1 or more) over parts of several city clusters. The NO2 pollution in most provincial regions rose rapidly from 2005 to 2011 but stabilized or declined afterwards. The NO2 trends were driven mainly by changes in anthropogenic emissions, as confirmed by a nested GEOS-Chem model simulation and a comparison with Chinese official emission statistics. The rate of NO2 growth during 2005-2013 reaches 11.3 ± 1.0 % yr-1 over Northwestern China, exceeding the rates over Southwestern China (5.9 ± 0.6 % yr-1) and the three well-known polluted regions in the east (5.3 ± 0.8 % yr-1 over Beijing-Tianjin-Hebei, 4.0 ± 0.6 % yr-1} over the Yangtze River Delta, and -3.3 ± 0.3 % yr-1 over the Pearl River Delta). Additional socioeconomic analyses suggest that the rapid NO2 growth in Northwestern China is likely related to the fast developing resource- and pollution-intensive industries along with the "Go West" movement as well as relatively weak emission controls. Further efforts should be made to alleviate NOx pollution to achieve sustainable development in Western China.

Applying the sequential neural-network approximation and orthogonal array algorithm to optimize the axial-flow cooling system for rapid thermal processes

International Nuclear Information System (INIS)

Hung, Shih-Yu; Shen, Ming-Ho; Chang, Ying-Pin

2009-01-01

The sequential neural-network approximation and orthogonal array (SNAOA) were used to shorten the cooling time for the rapid cooling process such that the normalized maximum resolved stress in silicon wafer was always below one in this study. An orthogonal array was first conducted to obtain the initial solution set. The initial solution set was treated as the initial training sample. Next, a back-propagation sequential neural network was trained to simulate the feasible domain to obtain the optimal parameter setting. The size of the training sample was greatly reduced due to the use of the orthogonal array. In addition, a restart strategy was also incorporated into the SNAOA so that the searching process may have a better opportunity to reach a near global optimum. In this work, we considered three different cooling control schemes during the rapid thermal process: (1) downward axial gas flow cooling scheme; (2) upward axial gas flow cooling scheme; (3) dual axial gas flow cooling scheme. Based on the maximum shear stress failure criterion, the other control factors such as flow rate, inlet diameter, outlet width, chamber height and chamber diameter were also examined with respect to cooling time. The results showed that the cooling time could be significantly reduced using the SNAOA approach

Multiple gingival pregnancy tumors with rapid growth

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Wei-Lian Sun

2014-09-01

Full Text Available Pregnancy gingivitis is an acute form of gingivitis that affects pregnant women, with a prevalence of 30%, possibly ranging up to 100%. Sometimes, pregnancy gingivitis shows a tendency toward a localized hyperplasia called gingival pyogenic granuloma. Pregnancy tumor is a benign gingival hyperplasia with the gingiva as the most commonly involved site, but rarely it involves almost the entire gingiva. A 22-year-old woman was referred to our clinic with a chief complaint of gingival swelling that had lasted for 2 days. The lesions progressed rapidly and extensively, and almost all the gingiva was involved a week later. Generalized erythema, edema, hyperplasia, a hemorrhagic tendency, and several typical hemangiomatous masses were noted. Pregnancy was denied by the patient at the first and second visits, but was confirmed 2 weeks after the primary visit. The patient was given oral hygiene instructions. She recovered well, and the mass gradually regressed and had disappeared completely at the end of 12 weeks of pregnancy, without recurrence. The gingival lesions were finally diagnosed as multiple gingival pregnancy tumors. The patient delivered a healthy infant. An extensive and rapid growth of gingival pregnancy tumors during the early first month of pregnancy is a rare occurrence that is not familiar to dentists, gynecologists, and obstetricians. Those practitioners engaged in oral medicine and periodontology, primary care obstetrics, and gynecology should be aware of such gingival lesions to avoid misdiagnosis and overtreatment.

The Great Transformations of Tibet and Xinjiang: a comparative analysis of rapid labour transitions in times of rapid growth in two contested minority regions of China

NARCIS (Netherlands)

A.M. Fischer (Andrew Martín)

2011-01-01

textabstractRapid growth since the mid-1990s in the Tibetan and Uyghur areas in Western China has been associated with the rapid transition of the local (mostly Tibetan and Uyghur) labour forces out of the primary sector (mostly farming and herding) and into the tertiary sector (services). The TAR,

Rapid growth, early maturation and short generation time in African annual fishes

Czech Academy of Sciences Publication Activity Database

Blažek, Radim; Polačik, Matej; Reichard, Martin

2013-01-01

Roč. 4, č. 24 (2013), s. 24 ISSN 2041-9139 R&D Projects: GA ČR(CZ) GAP506/11/0112 Institutional support: RVO:68081766 Keywords : extreme life history * annual fish * explosive growth * rapid maturation * generation time * killifish * diapause * vertebrate * reaction norm * Savanna Subject RIV: EG - Zoology Impact factor: 3.104, year: 2013 http://www.evodevojournal.com/content/4/1/24

The rapid growth of domestic oil consumption in Saudi Arabia and the opportunity cost of oil exports foregone

International Nuclear Information System (INIS)

Gately, Dermot; Al-Yousef, Nourah; Al-Sheikh, Hamad M.H.

2012-01-01

We analyze the rapid growth of Saudi Arabia's domestic oil consumption, a nine-fold increase in 40 years, to nearly 3 million barrels per day, about one-fourth of production. Such rapid growth in consumption – 5.7% annually, which is 37% faster than its income growth of 4.2% – will challenge Saudi Arabia's ability to increase its oil exports, which are relied upon in long-term world oil projections by the International Energy Agency (IEA), US Department of Energy (DOE) and British Petroleum (BP). However, these institutions assume unprecedented slowdowns in Saudi oil consumption – from 5.7% annual growth historically to less than 2% in the future – allowing them to project increases in Saudi oil exports. Using 1971–2010 data, we estimate that the income responsiveness (elasticity) of oil consumption is at least 1.5—using both Ordinary Least Squares regression and Cointegration methods. We believe that continued high growth rates for domestic oil consumption are more likely than the dramatic slowdowns projected by IEA, DOE and BP. This will have major implications for Saudi production and export levels. - Highlights: ► We analyze the rapid growth of Saudi Arabia's domestic oil consumption, now one-fourth of production. ► Estimated income elasticity of oil demand at least 1.5, using OLS and Co-integration. ► Yet IEA, DOE and BP project unprecedented slowdowns, from 5.7% historically to below 2%, half the rate of income growth. ► Continued high growth rates are more likely, with major implications for Saudi production and export levels.

Vascular Endothelial Growth Factor Receptor 3 Controls Neural Stem Cell Activation in Mice and Humans

Directory of Open Access Journals (Sweden)

Jinah Han

2015-02-01

Full Text Available Neural stem cells (NSCs continuously produce new neurons within the adult mammalian hippocampus. NSCs are typically quiescent but activated to self-renew or differentiate into neural progenitor cells. The molecular mechanisms of NSC activation remain poorly understood. Here, we show that adult hippocampal NSCs express vascular endothelial growth factor receptor (VEGFR 3 and its ligand VEGF-C, which activates quiescent NSCs to enter the cell cycle and generate progenitor cells. Hippocampal NSC activation and neurogenesis are impaired by conditional deletion of Vegfr3 in NSCs. Functionally, this is associated with compromised NSC activation in response to VEGF-C and physical activity. In NSCs derived from human embryonic stem cells (hESCs, VEGF-C/VEGFR3 mediates intracellular activation of AKT and ERK pathways that control cell fate and proliferation. These findings identify VEGF-C/VEGFR3 signaling as a specific regulator of NSC activation and neurogenesis in mammals.

Product unit neural network models for predicting the growth limits of Listeria monocytogenes.

Science.gov (United States)

Valero, A; Hervás, C; García-Gimeno, R M; Zurera, G

2007-08-01

A new approach to predict the growth/no growth interface of Listeria monocytogenes as a function of storage temperature, pH, citric acid (CA) and ascorbic acid (AA) is presented. A linear logistic regression procedure was performed and a non-linear model was obtained by adding new variables by means of a Neural Network model based on Product Units (PUNN). The classification efficiency of the training data set and the generalization data of the new Logistic Regression PUNN model (LRPU) were compared with Linear Logistic Regression (LLR) and Polynomial Logistic Regression (PLR) models. 92% of the total cases from the LRPU model were correctly classified, an improvement on the percentage obtained using the PLR model (90%) and significantly higher than the results obtained with the LLR model, 80%. On the other hand predictions of LRPU were closer to data observed which permits to design proper formulations in minimally processed foods. This novel methodology can be applied to predictive microbiology for describing growth/no growth interface of food-borne microorganisms such as L. monocytogenes. The optimal balance is trying to find models with an acceptable interpretation capacity and with good ability to fit the data on the boundaries of variable range. The results obtained conclude that these kinds of models might well be very a valuable tool for mathematical modeling.

Canonical Wnt signaling transiently stimulates proliferation and enhances neurogenesis in neonatal neural progenitor cultures

International Nuclear Information System (INIS)

Hirsch, Cordula; Campano, Louise M.; Woehrle, Simon; Hecht, Andreas

2007-01-01

Canonical Wnt signaling triggers the formation of heterodimeric transcription factor complexes consisting of β-catenin and T cell factors, and thereby controls the execution of specific genetic programs. During the expansion and neurogenic phases of embryonic neural development canonical Wnt signaling initially controls proliferation of neural progenitor cells, and later neuronal differentiation. Whether Wnt growth factors affect neural progenitor cells postnatally is not known. Therefore, we have analyzed the impact of Wnt signaling on neural progenitors isolated from cerebral cortices of newborn mice. Expression profiling of pathway components revealed that these cells are fully equipped to respond to Wnt signals. However, Wnt pathway activation affected only a subset of neonatal progenitors and elicited a limited increase in proliferation and neuronal differentiation in distinct subsets of cells. Moreover, Wnt pathway activation only transiently stimulated S-phase entry but did not support long-term proliferation of progenitor cultures. The dampened nature of the Wnt response correlates with the predominant expression of inhibitory pathway components and the rapid actuation of negative feedback mechanisms. Interestingly, in differentiating cell cultures activation of canonical Wnt signaling reduced Hes1 and Hes5 expression suggesting that during postnatal neural development, Wnt/β-catenin signaling enhances neurogenesis from progenitor cells by interfering with Notch pathway activity

A comparison of test statistics for the recovery of rapid growth-based enumeration tests

NARCIS (Netherlands)

van den Heuvel, Edwin R.; IJzerman-Boon, Pieta C.

This paper considers five test statistics for comparing the recovery of a rapid growth-based enumeration test with respect to the compendial microbiological method using a specific nonserial dilution experiment. The finite sample distributions of these test statistics are unknown, because they are

Prenatal exposure to traffic pollution: associations with reduced fetal growth and rapid infant weight gain.

Science.gov (United States)

Fleisch, Abby F; Rifas-Shiman, Sheryl L; Koutrakis, Petros; Schwartz, Joel D; Kloog, Itai; Melly, Steven; Coull, Brent A; Zanobetti, Antonella; Gillman, Matthew W; Gold, Diane R; Oken, Emily

2015-01-01

Prenatal air pollution exposure inhibits fetal growth, but implications for postnatal growth are unknown. We assessed weights and lengths of US infants in the Project Viva cohort at birth and 6 months. We estimated 3rd-trimester residential air pollution exposures using spatiotemporal models. We estimated neighborhood traffic density and roadway proximity at birth address using geographic information systems. We performed linear and logistic regression adjusted for sociodemographic variables, fetal growth, and gestational age at birth. Mean birth weight-for-gestational age z-score (fetal growth) was 0.17 (standard deviation [SD] = 0.97; n = 2,114), 0- to 6-month weight-for-length gain was 0.23 z-units (SD = 1.11; n = 689), and 17% had weight-for-length ≥95th percentile at 6 months of age. Infants exposed to the highest (vs. lowest) quartile of neighborhood traffic density had lower fetal growth (-0.13 units [95% confidence interval (CI) = -0.25 to -0.01]), more rapid 0- to 6-month weight-for-length gain (0.25 units [95% CI = 0.01 to 0.49]), and higher odds of weight-for-length ≥95th percentile at 6 months (1.84 [95% CI = 1.11 to 3.05]). Neighborhood traffic density was additionally associated with an infant being in both the lowest quartile of fetal growth and the highest quartile of 0- to 6-month weight-for-length gain (Q4 vs. Q1, odds ratio = 3.01 [95% CI = 1.08 to 8.44]). Roadway proximity and 3rd-trimester black carbon exposure were similarly associated with growth outcomes. For 3rd-trimester particulate matter (PM2.5), effect estimates were in the same direction, but smaller and imprecise. Infants exposed to higher traffic-related pollution in early life may exhibit more rapid postnatal weight gain in addition to reduced fetal growth.

Large plasma-membrane depolarization precedes rapid blue-light-induced growth inhibition in cucumber

Science.gov (United States)

Spalding, E. P.; Cosgrove, D. J.

1989-01-01

Blue-light (BL)-induced suppression of elongation of etiolated Cucumis sativus L. hypocotyls began after a 30-s lag time, which was halved by increasing the fluence rate from 10 to 100 micromoles m-2 s-1. Prior to the growth suppression, the plasma-membrane of the irradiated cells depolarized by as much as 100 mV, then returned within 2-3 min to near its initial value. The potential difference measured with surface electrodes changed with an identical time course but opposite polarity. The lag time for the change in surface potential showed an inverse dependence on fluence rate, similar to the lag for the growth inhibition. Green light and red light caused neither the electrical response nor the rapid inhibition of growth. The depolarization by BL did not propagate to nonirradiated regions and exhibited a refractory period of about 10 min following a BL pulse. Fluence-response relationships for the electrical and growth responses provide correlational evidence that the plasma-membrane depolarization reflects an event in the transduction chain of this light-growth response.

Neural stem cell regulation, fibroblast growth factors, and the developmental origins of neuropsychiatric disorders

Directory of Open Access Journals (Sweden)

Hanna E Stevens

2010-09-01

Full Text Available There is increasing appreciation for the neurodevelopmental underpinnings of many psychiatric disorders. Disorders that begin in childhood such as autism, language disorders or mental retardation as well as adult-onset mental disorders may have origins early in neurodevelopment. Neural stem cells (NSCs can be defined as self-renewing, multipotent cells that are present in both the embryonic and adult brain. Several recent research findings demonstrate that psychiatric illness may begin with abnormal specification, growth, expansion and differentiation of embryonic NSCs. For example, candidate susceptibility genes for schizophrenia, autism and major depression include the signaling molecule Disrupted In Schizophrenia-1 (DISC-1, the homeodomain gene engrailed-2 (EN-2, and several receptor tyrosine kinases (RTKs, including MET, brain-derived growth factor (BDNF and fibroblast growth factors (FGF, all of which have been shown to play important roles in NSCs or neuronal precursors. We will discuss here stem cell biology, signaling factors that affect these cells, and the potential contribution of these processes to the etiology of neuropsychiatric disorders. Hypotheses about how some of these factors relate to psychiatric disorders will be reviewed.

Urban Heat Island Growth Modeling Using Artificial Neural Networks and Support Vector Regression: A case study of Tehran, Iran

Science.gov (United States)

Sherafati, Sh. A.; Saradjian, M. R.; Niazmardi, S.

2013-09-01

Numerous investigations on Urban Heat Island (UHI) show that land cover change is the main factor of increasing Land Surface Temperature (LST) in urban areas. Therefore, to achieve a model which is able to simulate UHI growth, urban expansion should be concerned first. Considerable researches on urban expansion modeling have been done based on cellular automata. Accordingly the objective of this paper is to implement CA method for trend detection of Tehran UHI spatiotemporal growth based on urban sprawl parameters (such as Distance to nearest road, Digital Elevation Model (DEM), Slope and Aspect ratios). It should be mentioned that UHI growth modeling may have more complexities in comparison with urban expansion, since the amount of each pixel's temperature should be investigated instead of its state (urban and non-urban areas). The most challenging part of CA model is the definition of Transfer Rules. Here, two methods have used to find appropriate transfer Rules which are Artificial Neural Networks (ANN) and Support Vector Regression (SVR). The reason of choosing these approaches is that artificial neural networks and support vector regression have significant abilities to handle the complications of such a spatial analysis in comparison with other methods like Genetic or Swarm intelligence. In this paper, UHI change trend has discussed between 1984 and 2007. For this purpose, urban sprawl parameters in 1984 have calculated and added to the retrieved LST of this year. In order to achieve LST, Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) night-time images have exploited. The reason of implementing night-time images is that UHI phenomenon is more obvious during night hours. After that multilayer feed-forward neural networks and support vector regression have used separately to find the relationship between this data and the retrieved LST in 2007. Since the transfer rules might not be the same in different regions, the satellite image of the city has

Enrichment of skin-derived neural precursor cells from dermal cell populations by altering culture conditions.

Science.gov (United States)

Bayati, Vahid; Gazor, Rohoullah; Nejatbakhsh, Reza; Negad Dehbashi, Fereshteh

2016-01-01

As stem cells play a critical role in tissue repair, their manipulation for being applied in regenerative medicine is of great importance. Skin-derived precursors (SKPs) may be good candidates for use in cell-based therapy as the only neural stem cells which can be isolated from an accessible tissue, skin. Herein, we presented a simple protocol to enrich neural SKPs by monolayer adherent cultivation to prove the efficacy of this method. To enrich neural SKPs from dermal cell populations, we have found that a monolayer adherent cultivation helps to increase the numbers of neural precursor cells. Indeed, we have cultured dermal cells as monolayer under serum-supplemented (control) and serum-supplemented culture, followed by serum free cultivation (test) and compared. Finally, protein markers of SKPs were assessed and compared in both experimental groups and differentiation potential was evaluated in enriched culture. The cells of enriched culture concurrently expressed fibronectin, vimentin and nestin, an intermediate filament protein expressed in neural and skeletal muscle precursors as compared to control culture. In addition, they possessed a multipotential capacity to differentiate into neurogenic, glial, adipogenic, osteogenic and skeletal myogenic cell lineages. It was concluded that serum-free adherent culture reinforced by growth factors have been shown to be effective on proliferation of skin-derived neural precursor cells (skin-NPCs) and drive their selective and rapid expansion.

Complex-valued neural networks advances and applications

CERN Document Server

Hirose, Akira

2013-01-01

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and

Urban Growth Modeling Using AN Artificial Neural Network a Case Study of Sanandaj City, Iran

Science.gov (United States)

Mohammady, S.; Delavar, M. R.; Pahlavani, P.

2014-10-01

Land use activity is a major issue and challenge for town and country planners. Modelling and managing urban growth is a complex problem. Cities are now recognized as complex, non-linear and dynamic process systems. The design of a system that can handle these complexities is a challenging prospect. Local governments that implement urban growth models need to estimate the amount of urban land required in the future given anticipated growth of housing, business, recreation and other urban uses within the boundary. There are so many negative implications related with the type of inappropriate urban development such as increased traffic and demand for mobility, reduced landscape attractively, land use fragmentation, loss of biodiversity and alterations of the hydrological cycle. The aim of this study is to use the Artificial Neural Network (ANN) to make a powerful tool for simulating urban growth patterns. Our study area is Sanandaj city located in the west of Iran. Landsat imageries acquired at 2000 and 2006 are used. Dataset were used include distance to principle roads, distance to residential areas, elevation, slope, distance to green spaces and distance to region centers. In this study an appropriate methodology for urban growth modelling using satellite remotely sensed data is presented and evaluated. Percent Correct Match (PCM) and Figure of Merit were used to evaluate ANN results.

URBAN GROWTH MODELING USING AN ARTIFICIAL NEURAL NETWORK A CASE STUDY OF SANANDAJ CITY, IRAN

Directory of Open Access Journals (Sweden)

S. Mohammady

2014-10-01

Full Text Available Land use activity is a major issue and challenge for town and country planners. Modelling and managing urban growth is a complex problem. Cities are now recognized as complex, non-linear and dynamic process systems. The design of a system that can handle these complexities is a challenging prospect. Local governments that implement urban growth models need to estimate the amount of urban land required in the future given anticipated growth of housing, business, recreation and other urban uses within the boundary. There are so many negative implications related with the type of inappropriate urban development such as increased traffic and demand for mobility, reduced landscape attractively, land use fragmentation, loss of biodiversity and alterations of the hydrological cycle. The aim of this study is to use the Artificial Neural Network (ANN to make a powerful tool for simulating urban growth patterns. Our study area is Sanandaj city located in the west of Iran. Landsat imageries acquired at 2000 and 2006 are used. Dataset were used include distance to principle roads, distance to residential areas, elevation, slope, distance to green spaces and distance to region centers. In this study an appropriate methodology for urban growth modelling using satellite remotely sensed data is presented and evaluated. Percent Correct Match (PCM and Figure of Merit were used to evaluate ANN results.

Growth medium for the rapid isolation and identification of anthrax

Science.gov (United States)

Kiel, Johnathan L.; Parker, Jill E.; Grubbs, Teri R.; Alls, John L.

2000-07-01

Anthrax has been recognized as a highly likely biological warfare or terrorist agent. The purpose of this work was to design a culture technique to rapidly isolate and identify `live' anthrax. In liquid or solid media form, 3AT medium (3-amino-L-tyrosine, the main ingredient) accelerated germination and growth of anthrax spores in 5 to 6 hours to a point expected at 18 to 24 hours with ordinary medium. During accelerated growth, standard definitive diagnostic tests such as sensitivity to lysis by penicillin or bacteriophage can be run. During this time, the bacteria synthesized a fluorescent and thermochemiluminescent polymer. Bacteria captured by specific antibody are, therefore, already labeled. Because living bacteria are required to generate the polymer, the test converts immunoassays for anthrax into viability assays. Furthermore, the polymer formation leads to the death of the vegetative form and non-viability of the spores produced in the medium. By altering the formulation of the medium, other microbes and even animal and human cells can be grown in it and labeled (including viruses grown in the animal or human cells).

An Inquiry into the Rapid Growth of the Garment Industry in Bangladesh

OpenAIRE

MOTTALEB, Khondoker Abdul; SONOBE, Tetsushi

2011-01-01

The export-oriented garment industry in Bangladesh has grown rapidly for the last three decades and now ranks among the largest garment exporters in the world. While its early success is attributed to the initial technology transfer from South Korea, such a one-time infusion of knowledge alone is insufficient to explain the sustained growth for three decades. This paper uses primary data collected from knitwear manufacturers and garment traders to explore the process of the continuous learnin...

The impact of rapid economic growth and globalization on zinc nutrition in South Korea.

Science.gov (United States)

Kwun, In-Sook; Do, Mi-Sook; Chung, Hae-Rang; Kim, Yang Ha; Beattie, John H

2009-08-01

Zn deficiency may be widespread in Asian countries such as South Korea. However, dietary habits have changed in response to rapid economic growth and globalization. Zn nutrition in South Koreans has therefore been assessed during a period (1969-1998) of unprecedented economic growth. Cross-sectional food consumption data from the Korean National Nutrition Survey Reports (KNNSR) of South Korea at four separate time points (1969, 1978, 1988 and 1998) were used to calculate Zn, Ca and phytate intakes using various food composition tables, databases and literature values. Nutrient values in local foods were cited from their analysed values. Average Zn intake was 5.8, 4.8 and 5.3 mg/d for 1969, 1978 and 1988 respectively, increasing to 7.3 mg/d in 1998 (73 % of the Korean Dietary Reference Intake). The phytate:Zn molar ratio decreased from 21 to 8 during the study period. Dietary Zn depletion due to marked decreases in cereal consumption, particularly barley which has a low Zn bioavailability, was counterbalanced by marked increases in the consumption of meat and fish, which are also Zn-rich foods. Reduced phytate consumption coincident with increased Zn intake suggests that Zn bioavailability also improved, particularly by 1998. Although total Zn intake was not greatly affected over the initial period of economic growth in South Korea (1969-1988), Zn contributions from different food sources changed markedly and both Zn intake and potential bioavailability were improved by 1998. The study may have implications for Zn nutrition in other Asian countries currently experiencing rapid economic growth.

Hydrothermal vents in Lake Tanganyika harbor spore-forming thermophiles with extremely rapid growth

DEFF Research Database (Denmark)

Elsgaard, Lars; Prieur, Daniel

2010-01-01

A thermophilic anaerobic bacterium was isolated from a sublacustrine hydrothermal vent site in Lake Tanganyika (East Africa) with recorded fluid temperatures of 66–103 °C and pH values of 7.7–8.9. The bacterium (strain TR10) was rod-shaped, about 1 by 5 μm in size, and readily formed distal...... and peptone. The optimum temperature for growth was 60 °C, while minimum and maximum temperatures were 40 and 75 °C. The pH response was alkalitolerant with optimum pH at 7.4 and 8.5 depending on the growth medium. The distinct feature of rapid proliferation and endospore formation may allow the novel...

Rapid generation of OPC-like cells from human pluripotent stem cells for treating spinal cord injury.

Science.gov (United States)

Kim, Dae-Sung; Jung, Se Jung; Lee, Jae Souk; Lim, Bo Young; Kim, Hyun Ah; Yoo, Jeong-Eun; Kim, Dong-Wook; Leem, Joong Woo

2017-07-28

Remyelination via the transplantation of oligodendrocyte precursor cells (OPCs) has been considered as a strategy to improve the locomotor deficits caused by traumatic spinal cord injury (SCI). To date, enormous efforts have been made to derive OPCs from human pluripotent stem cells (hPSCs), and significant progress in the transplantation of such cells in SCI animal models has been reported. The current methods generally require a long period of time (>2 months) to obtain transplantable OPCs, which hampers their clinical utility for patients with SCI. Here we demonstrate a rapid and efficient method to differentiate hPSCs into neural progenitors that retain the features of OPCs (referred to as OPC-like cells). We used cell sorting to select A2B5-positive cells from hPSC-derived neural rosettes and cultured the selected cells in the presence of signaling cues, including sonic hedgehog, PDGF and insulin-like growth factor-1. This method robustly generated neural cells positive for platelet-derived growth factor receptor-α (PDGFRα) and NG2 (~90%) after 4 weeks of differentiation. Behavioral tests revealed that the transplantation of the OPC-like cells into the spinal cords of rats with contusive SCI at the thoracic level significantly improved hindlimb locomotor function. Electrophysiological assessment revealed enhanced neural conduction through the injury site. Histological examination showed increased numbers of axon with myelination at the injury site and graft-derived myelin formation with no evidence of tumor formation. Our method provides a cell source from hPSCs that has the potential to recover motor function following SCI.

Oxidation phase growth diagram of vanadium oxides film fabricated by rapid thermal annealing

Institute of Scientific and Technical Information of China (English)

Tamura KOZO; Zheng-cao LI; Yu-quan WANG; Jie NI; Yin HU; Zheng-jun ZHANG

2009-01-01

Thermal evaporation deposited vanadium oxide films were annealed in air by rapid thermal annealing (RTP). By adjusting the annealing temperature and time, a series of vanadium oxide films with various oxidation phases and surface morphologies were fabricated, and an oxidation phase growth diagram was established. It was observed that different oxidation phases appear at a limited and continuous annealing condition range, and the morphologic changes are related to the oxidation process.

Tyrosine requirement during the rapid catch-up growth phase of recovery from severe childhood undernutrition

Science.gov (United States)

The requirement for aromatic amino acids, during the rapid catch-up in weight phase of recovery from severe childhood under nutrition (SCU) is not clearly established. As a first step, the present study aimed to estimate the tyrosine requirement of children with SCU during the catch-up growth phase ...

Urban Growth Modelling with Artificial Neural Network and Logistic Regression. Case Study: Sanandaj City, Iran

Directory of Open Access Journals (Sweden)

SASSAN MOHAMMADY

2013-01-01

Full Text Available Cities have shown remarkable growth due to attraction, economic, social and facilities centralization in the past few decades. Population and urban expansion especially in developing countries, led to lack of resources, land use change from appropriate agricultural land to urban land use and marginalization. Under these circumstances, land use activity is a major issue and challenge for town and country planners. Different approaches have been attempted in urban expansion modelling. Artificial Neural network (ANN models are among knowledge-based models which have been used for urban growth modelling. ANNs are powerful tools that use a machine learning approach to quantify and model complex behaviour and patterns. In this research, ANN and logistic regression have been employed for interpreting urban growth modelling. Our case study is Sanandaj city and we used Landsat TM and ETM+ imageries acquired at 2000 and 2006. The dataset used includes distance to main roads, distance to the residence region, elevation, slope, and distance to green space. Percent Area Match (PAM obtained from modelling of these changes with ANN is equal to 90.47% and the accuracy achieved for urban growth modelling with Logistic Regression (LR is equal to 88.91%. Percent Correct Match (PCM and Figure of Merit for ANN method were 91.33% and 59.07% and then for LR were 90.84% and 57.07%, respectively.

Podocalyxin Is a Novel Polysialylated Neural Adhesion Protein with Multiple Roles in Neural Development and Synapse Formation

Science.gov (United States)

Vitureira, Nathalia; Andrés, Rosa; Pérez-Martínez, Esther; Martínez, Albert; Bribián, Ana; Blasi, Juan; Chelliah, Shierley; López-Doménech, Guillermo; De Castro, Fernando; Burgaya, Ferran; McNagny, Kelly; Soriano, Eduardo

2010-01-01

Neural development and plasticity are regulated by neural adhesion proteins, including the polysialylated form of NCAM (PSA-NCAM). Podocalyxin (PC) is a renal PSA-containing protein that has been reported to function as an anti-adhesin in kidney podocytes. Here we show that PC is widely expressed in neurons during neural development. Neural PC interacts with the ERM protein family, and with NHERF1/2 and RhoA/G. Experiments in vitro and phenotypic analyses of podxl-deficient mice indicate that PC is involved in neurite growth, branching and axonal fasciculation, and that PC loss-of-function reduces the number of synapses in the CNS and in the neuromuscular system. We also show that whereas some of the brain PC functions require PSA, others depend on PC per se. Our results show that PC, the second highly sialylated neural adhesion protein, plays multiple roles in neural development. PMID:20706633

Learning text representation using recurrent convolutional neural network with highway layers

OpenAIRE

Wen, Ying; Zhang, Weinan; Luo, Rui; Wang, Jun

2016-01-01

Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers. The highway network module is incorporated in the middle takes the output of the bi-directional Recurrent Neural Network (Bi-RNN) module in the first stage and provides the Convolutional Neural Network (CNN) module in the last stage with the i...

Electromagnetic induction heating for single crystal graphene growth: morphology control by rapid heating and quenching

Science.gov (United States)

Wu, Chaoxing; Li, Fushan; Chen, Wei; Veeramalai, Chandrasekar Perumal; Ooi, Poh Choon; Guo, Tailiang

2015-03-01

The direct observation of single crystal graphene growth and its shape evolution is of fundamental importance to the understanding of graphene growth physicochemical mechanisms and the achievement of wafer-scale single crystalline graphene. Here we demonstrate the controlled formation of single crystal graphene with varying shapes, and directly observe the shape evolution of single crystal graphene by developing a localized-heating and rapid-quenching chemical vapor deposition (CVD) system based on electromagnetic induction heating. Importantly, rational control of circular, hexagonal, and dendritic single crystalline graphene domains can be readily obtained for the first time by changing the growth condition. Systematic studies suggest that the graphene nucleation only occurs during the initial stage, while the domain density is independent of the growth temperatures due to the surface-limiting effect. In addition, the direct observation of graphene domain shape evolution is employed for the identification of competing growth mechanisms including diffusion-limited, attachment-limited, and detachment-limited processes. Our study not only provides a novel method for morphology-controlled graphene synthesis, but also offers fundamental insights into the kinetics of single crystal graphene growth.

Rapid solidification growth mode transitions in Al-Si alloys by dynamic transmission electron microscopy

International Nuclear Information System (INIS)

Roehling, John D.; Coughlin, Daniel R.; Gibbs, John W.; Baldwin, J. Kevin; Mertens, James C.E.; Campbell, Geoffrey H.; Clarke, Amy J.; McKeown, Joseph T.

2017-01-01

In situ dynamic transmission electron microscope (DTEM) imaging of Al-Si thin-film alloys was performed to investigate rapid solidification behavior. Solidification of alloys with compositions from 1 to 15 atomic percent Si was imaged during pulsed laser melting and subsequent solidification. Solely α-Al solidification was observed in Al-1Si and Al-3Si alloys, and solely kinetically modified eutectic growth was observed in Al-6Si and Al-9Si alloys. A transition in the solidification mode in eutectic and hypereutectic alloys (Al-12Si and Al-15Si) from nucleated α-Al dendrites at lower solidification velocities to planar eutectic growth at higher solidification velocities was observed, departing from trends previously seen in laser-track melting experiments. Comparisons of the growth modes and corresponding velocities are compared with previous solidification models, and implications regarding the models are discussed.

Safety dose of three commercially used growth promoters: nuricell- aqua, hepaprotect-aqua and rapid-grow on growth and survival of Thai pangas (Pangasianodon hypophthalmus

Directory of Open Access Journals (Sweden)

Md. Ariful Islam

2014-02-01

Full Text Available Objective: To optimize the dose of 3 commonly used growth promoters, viz., Nuricell-Aqua (composition: glucomannan complex and mannose polymer, Hepaprotect-Aqua (composition: β-glucan, mannose polymer and essential oil and Rapid-Grow (composition: organic acid and their salt, β-glucan, mannose oligosaccharide and essential oil, using Thai pangas (Pangasiandon hypophthalmus as cultured species. Methods: Thai pangas fingerlings with an average length and weight of 11 cm and 10 g were reared under laboratory condition and growth promoters were fed after incorporating them with a test diet at a ratio of 10% of their body weight for a period of 28 d. Estimation of data on growth such as weight gain (g, specific growth rate, survivability (% test in each aquarium were conducted and data were analyzed using statistical software. Results: After 28 d of feeding with Nutricell-Aqua, 10 mg/(20 g feed·day, which was the dose recommended by the manufacturer, was found better. When Hepaprotect-Aqua and Rapid-Grow were employed, performance was found to be better with the dose of 60 mg/(20 g feed·day which was 1.5 times higher than the dose recommended by the corresponding manufacturer. Conclusions: These results suggest that chemicals and feed additives marketed in Bangladesh Fish Feed Market need further testing under Bangladesh climatic condition before being marketed.

Driving forces of rapid CO2 emissions growth: A case of Korea

International Nuclear Information System (INIS)

Kim, Yong-Gun; Yoo, Jonghyun; Oh, Wankeun

2015-01-01

This study aims to investigate Korea's final demand structure and its impacts on CO 2 emissions in order to reduce CO 2 emissions and develop environmental policy directions. Based on the environmentally extended input–output model, this study adopts a two-step approach: (1) to estimate the embodied emissions and their intensities for 393 sectors induced by final demand; and (2) to calculate the driving factors of emission growth between 2003 and 2011 and then evaluate the result by using Structural Decomposition Analysis (SDA). The findings of this study demonstrate that the impact of composition change in export with less embodied emission intensities tends to offset the increase in CO 2 emission by the export scale growth. The relatively low residential electricity price has resulted in the rapid growth of household electricity consumption and significantly contributed to emissions growth. The result of SDA indicates that Korea's final demand behavior yielded high carbonization over the same period. The findings suggest that Korean government should promote exports in industries with less embedded CO 2 in order to protect environments. In addition, emission information of each product and service should be provided for consumers to change their purchase patterns towards contributing to low carbon emissions as active players. -- Highlights: •We investigate Korea's final demand structure and its contribution to CO 2 emissions. •Using SDA, we evaluate the driving factors of emission growth from 2003 to 2011. •Exports play a critical role in Korea's CO 2 emissions growth. •The relatively low residential electricity price has contributed to emission growth. •Korea's final demand behavior yielded high carbonization over the same period

Rapid and Controlled In Situ Growth of Noble Metal Nanostructures within Halloysite Clay Nanotubes.

Science.gov (United States)

Rostamzadeh, Taha; Islam Khan, Md Shahidul; Riche', Kyle; Lvov, Yuri M; Stavitskaya, Anna V; Wiley, John B

2017-11-14

A rapid (≤2 min) and high-yield low-temperature synthesis has been developed for the in situ growth of gold nanoparticles (NPs) with controlled sizes in the interior of halloysite nanotubes (HNTs). A combination of HAuCl 4 in ethanol/toluene, oleic acid, and oleylamine surfactants and ascorbic acid reducing agent with mild heating (55 °C) readily lead to the growth of targeted nanostructures. The sizes of Au NPs are tuned mainly by adjusting nucleation and growth rates. Further modification of the process, through an increase in ascorbic acid, allows for the formation of nanorods (NRs)/nanowires within the HNTs. This approach is not limited to gold-a modified version of this synthetic strategy can also be applied to the formation of Ag NPs and NRs within the clay nanotubes. The ability to readily grow such core-shell nanosystems is important to their further development as nanoreactors and active catalysts. NPs within the tube interior can further be manipulated by the electron beam. Growth of Au and Ag could be achieved under a converged electron beam suggesting that both Au@HNT and Ag@HNT systems can be used for the fundamental studies of NP growth/attachment.

Small leucine rich proteoglycan family regulates multiple signalling pathways in neural development and maintenance.

Science.gov (United States)

Dellett, Margaret; Hu, Wanzhou; Papadaki, Vasiliki; Ohnuma, Shin-ichi

2012-04-01

The small leucine-rich repeat proteoglycan (SLRPs) family of proteins currently consists of five classes, based on their structural composition and chromosomal location. As biologically active components of the extracellular matrix (ECM), SLRPs were known to bind to various collagens, having a role in regulating fibril assembly, organization and degradation. More recently, as a function of their diverse proteins cores and glycosaminoglycan side chains, SLRPs have been shown to be able to bind various cell surface receptors, growth factors, cytokines and other ECM components resulting in the ability to influence various cellular functions. Their involvement in several signaling pathways such as Wnt, transforming growth factor-β and epidermal growth factor receptor also highlights their role as matricellular proteins. SLRP family members are expressed during neural development and in adult neural tissues, including ocular tissues. This review focuses on describing SLRP family members involvement in neural development with a brief summary of their role in non-neural ocular tissues and in response to neural injury. © 2012 The Authors Development, Growth & Differentiation © 2012 Japanese Society of Developmental Biologists.

Bioelectrochemical control of neural cell development on conducting polymers.

Science.gov (United States)

Collazos-Castro, Jorge E; Polo, José L; Hernández-Labrado, Gabriel R; Padial-Cañete, Vanesa; García-Rama, Concepción

2010-12-01

Electrically conducting polymers hold promise for developing advanced neuroprostheses, bionic systems and neural repair devices. Among them, poly(3, 4-ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS) exhibits superior physicochemical properties but biocompatibility issues have limited its use. We describe combinations of electrochemical and molecule self-assembling methods to consistently control neural cell development on PEDOT:PSS while maintaining very low interfacial impedance. Electro-adsorbed polylysine enabled long-term neuronal survival and growth on the nanostructured polymer. Neurite extension was strongly inhibited by an additional layer of PSS or heparin, which in turn could be either removed electrically or further coated with spermine to activate cell growth. Binding basic fibroblast growth factor (bFGF) to the heparin layer inhibited neurons but promoted proliferation and migration of precursor cells. This methodology may orchestrate neural cell behavior on electroactive polymers, thus improving cell/electrode communication in prosthetic devices and providing a platform for tissue repair strategies. Copyright © 2010 Elsevier Ltd. All rights reserved.

China urges rapid growth

International Nuclear Information System (INIS)

Hendry, S.

1993-01-01

This time last year China's paramount leader, Deng Xiaoping, launched the country on another bout of fast-paced economic growth and restructuring. After three years of riding out political and economic clampdown, foreign chemical companies were jerked awake by major changes in China's chemical industry. As the state becomes less involved with managing the economy, unleashing 12% gross national product growth, closer involvement with domestic factories has become attractive and essential. MCI officials say government funds will now be channeled toward clearing energy and transport bottlenecks, and chemical enterprises will be given more chance to turn a profit. They will be allowed to issue shares, seek foreign investment partners themselves, and bypass trading companies like China National Import-Export Corp. (Sinochem), the former state monopoly. Foreign analysts question whether China's finances and oil resources can support expansion. Even if they can, Cai estimates that ethylene imports will remain around the present level of 1 million tons. To further guarantee chemical supplies, China has invested in urea and polypropylene plants in the US and polystyrene plant in Hong Kong

The fibroblast growth factor receptor (FGFR) agonist FGF1 and the neural cell adhesion molecule-derived peptide FGL activate FGFR substrate 2alpha differently

DEFF Research Database (Denmark)

Chen, Yongshuo; Li, Shizhong; Berezin, Vladimir

2010-01-01

Activation of fibroblast growth factor (FGF) receptors (FGFRs) both by FGFs and by the neural cell adhesion molecule (NCAM) is crucial in the development and function of the nervous system. We found that FGFR substrate 2alpha (FRS2alpha), Src homologous and collagen A (ShcA), and phospholipase-Cg...

Investment Valuation Analysis with Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Hüseyin İNCE

2017-07-01

Full Text Available This paper shows that discounted cash flow and net present value, which are traditional investment valuation models, can be combined with artificial neural network model forecasting. The main inputs for the valuation models, such as revenue, costs, capital expenditure, and their growth rates, are heavily related to sector dynamics and macroeconomics. The growth rates of those inputs are related to inflation and exchange rates. Therefore, predicting inflation and exchange rates is a critical issue for the valuation output. In this paper, the Turkish economy’s inflation rate and the exchange rate of USD/TRY are forecast by artificial neural networks and implemented to the discounted cash flow model. Finally, the results are benchmarked with conventional practices.

Baseline Levels of Rapid Eye Movement Sleep May Protect Against Excessive Activity in Fear-Related Neural Circuitry.

Science.gov (United States)

Lerner, Itamar; Lupkin, Shira M; Sinha, Neha; Tsai, Alan; Gluck, Mark A

2017-11-15

Sleep, and particularly rapid eye movement sleep (REM), has been implicated in the modulation of neural activity following fear conditioning and extinction in both human and animal studies. It has long been presumed that such effects play a role in the formation and persistence of posttraumatic stress disorder, of which sleep impairments are a core feature. However, to date, few studies have thoroughly examined the potential effects of sleep prior to conditioning on subsequent acquisition of fear learning in humans. Furthermore, these studies have been restricted to analyzing the effects of a single night of sleep-thus assuming a state-like relationship between the two. In the current study, we used long-term mobile sleep monitoring and functional neuroimaging (fMRI) to explore whether trait-like variations in sleep patterns, measured in advance in both male and female participants, predict subsequent patterns of neural activity during fear learning. Our results indicate that higher baseline levels of REM sleep predict reduced fear-related activity in, and connectivity between, the hippocampus, amygdala and ventromedial PFC during conditioning. Additionally, skin conductance responses (SCRs) were weakly correlated to the activity in the amygdala. Conversely, there was no direct correlation between REM sleep and SCRs, indicating that REM may only modulate fear acquisition indirectly. In a follow-up experiment, we show that these results are replicable, though to a lesser extent, when measuring sleep over a single night just before conditioning. As such, baseline sleep parameters may be able to serve as biomarkers for resilience, or lack thereof, to trauma. SIGNIFICANCE STATEMENT Numerous studies over the past two decades have established a clear role of sleep in fear-learning processes. However, previous work has focused on the effects of sleep following fear acquisition, thus neglecting the potential effects of baseline sleep levels on the acquisition itself. The

Selective neuronal differentiation of neural stem cells induced by nanosecond microplasma agitation.

Science.gov (United States)

Xiong, Z; Zhao, S; Mao, X; Lu, X; He, G; Yang, G; Chen, M; Ishaq, M; Ostrikov, K

2014-03-01

An essential step for therapeutic and research applications of stem cells is their ability to differentiate into specific cell types. Neuronal cells are of great interest for medical treatment of neurodegenerative diseases and traumatic injuries of central nervous system (CNS), but efforts to produce these cells have been met with only modest success. In an attempt of finding new approaches, atmospheric-pressure room-temperature microplasma jets (MPJs) are shown to effectively direct in vitro differentiation of neural stem cells (NSCs) predominantly into neuronal lineage. Murine neural stem cells (C17.2-NSCs) treated with MPJs exhibit rapid proliferation and differentiation with longer neurites and cell bodies eventually forming neuronal networks. MPJs regulate ~75% of NSCs to differentiate into neurons, which is a higher efficiency compared to common protein- and growth factors-based differentiation. NSCs exposure to quantized and transient (~150 ns) micro-plasma bullets up-regulates expression of different cell lineage markers as β-Tubulin III (for neurons) and O4 (for oligodendrocytes), while the expression of GFAP (for astrocytes) remains unchanged, as evidenced by quantitative PCR, immunofluorescence microscopy and Western Blot assay. It is shown that the plasma-increased nitric oxide (NO) production is a factor in the fate choice and differentiation of NSCs followed by axonal growth. The differentiated NSC cells matured and produced mostly cholinergic and motor neuronal progeny. It is also demonstrated that exposure of primary rat NSCs to the microplasma leads to quite similar differentiation effects. This suggests that the observed effect may potentially be generic and applicable to other types of neural progenitor cells. The application of this new in vitro strategy to selectively differentiate NSCs into neurons represents a step towards reproducible and efficient production of the desired NSC derivatives. Published by Elsevier B.V.

Selective neuronal differentiation of neural stem cells induced by nanosecond microplasma agitation

Directory of Open Access Journals (Sweden)

Z. Xiong

2014-03-01

Full Text Available An essential step for therapeutic and research applications of stem cells is their ability to differentiate into specific cell types. Neuronal cells are of great interest for medical treatment of neurodegenerative diseases and traumatic injuries of central nervous system (CNS, but efforts to produce these cells have been met with only modest success. In an attempt of finding new approaches, atmospheric-pressure room-temperature microplasma jets (MPJs are shown to effectively direct in vitro differentiation of neural stem cells (NSCs predominantly into neuronal lineage. Murine neural stem cells (C17.2-NSCs treated with MPJs exhibit rapid proliferation and differentiation with longer neurites and cell bodies eventually forming neuronal networks. MPJs regulate ~75% of NSCs to differentiate into neurons, which is a higher efficiency compared to common protein- and growth factors-based differentiation. NSCs exposure to quantized and transient (~150 ns micro-plasma bullets up-regulates expression of different cell lineage markers as β-Tubulin III (for neurons and O4 (for oligodendrocytes, while the expression of GFAP (for astrocytes remains unchanged, as evidenced by quantitative PCR, immunofluorescence microscopy and Western Blot assay. It is shown that the plasma-increased nitric oxide (NO production is a factor in the fate choice and differentiation of NSCs followed by axonal growth. The differentiated NSC cells matured and produced mostly cholinergic and motor neuronal progeny. It is also demonstrated that exposure of primary rat NSCs to the microplasma leads to quite similar differentiation effects. This suggests that the observed effect may potentially be generic and applicable to other types of neural progenitor cells. The application of this new in vitro strategy to selectively differentiate NSCs into neurons represents a step towards reproducible and efficient production of the desired NSC derivatives.

Brain Injury Expands the Numbers of Neural Stem Cells and Progenitors in the SVZ by Enhancing Their Responsiveness to EGF

Directory of Open Access Journals (Sweden)

Dhivyaa Alagappan

2009-04-01

Full Text Available There is an increase in the numbers of neural precursors in the SVZ (subventricular zone after moderate ischaemic injuries, but the extent of stem cell expansion and the resultant cell regeneration is modest. Therefore our studies have focused on understanding the signals that regulate these processes towards achieving a more robust amplification of the stem/progenitor cell pool. The goal of the present study was to evaluate the role of the EGFR [EGF (epidermal growth factor receptor] in the regenerative response of the neonatal SVZ to hypoxic/ischaemic injury. We show that injury recruits quiescent cells in the SVZ to proliferate, that they divide more rapidly and that there is increased EGFR expression on both putative stem cells and progenitors. With the amplification of the precursors in the SVZ after injury there is enhanced sensitivity to EGF, but not to FGF (fibroblast growth factor-2. EGF-dependent SVZ precursor expansion, as measured using the neurosphere assay, is lost when the EGFR is pharmacologically inhibited, and forced expression of a constitutively active EGFR is sufficient to recapitulate the exaggerated proliferation of the neural stem/progenitors that is induced by hypoxic/ischaemic brain injury. Cumulatively, our results reveal that increased EGFR signalling precedes that increase in the abundance of the putative neural stem cells and our studies implicate the EGFR as a key regulator of the expansion of SVZ precursors in response to brain injury. Thus modulating EGFR signalling represents a potential target for therapies to enhance brain repair from endogenous neural precursors following hypoxic/ischaemic and other brain injuries.

Is rapid growth in Internet usage environmentally sustainable for Australia? An empirical investigation.

Science.gov (United States)

Salahuddin, Mohammad; Alam, Khorshed; Ozturk, Ilhan

2016-03-01

This study estimates the short- and long-run effects of Internet usage and economic growth on carbon dioxide (CO2) emissions using annual time series macro data for Australia for the period 1985-2012. Autoregressive distributive lag (ARDL) bounds and Gregory-Hansen structural break cointegration tests are applied. ARDL estimates indicate no significant long-run relationship between Internet usage and CO2 emissions, which implies that the rapid growth in Internet usage is still not an environmental threat for Australia. The study further indicates that higher level of economic growth is associated with lower level of CO2 emissions; however, Internet usage and economic growth have no significant short-run relationship with CO2 emissions. Financial development has both short-run and long-run significant positive association with CO2 emissions. The findings offer support in favor of energy efficiency gains and a reduction in energy intensity in Australia. However, impulse response and variance decomposition analysis suggest that Internet usage, economic growth and financial development will continue to impact CO2 emissions in the future, and as such, this study recommends that in addition to the existing measures to combat CO2 emissions, Australia needs to exploit the potential of the Internet not only to reduce its own carbon footprint but also to utilize information and communication technology (ICT)-enabled emissions abatement potential to reduce emissions in various other sectors across the economy, such as, power, renewable energy especially in solar and wind energy, agriculture, transport and service.

Crystal surface analysis using matrix textural features classified by a Probabilistic Neural Network

International Nuclear Information System (INIS)

Sawyer, C.R.; Quach, V.T.; Nason, D.; van den Berg, L.

1991-01-01

A system is under development in which surface quality of a growing bulk mercuric iodide crystal is monitored by video camera at regular intervals for early detection of growth irregularities. Mercuric iodide single crystals are employed in radiation detectors. A microcomputer system is used for image capture and processing. The digitized image is divided into multiple overlappings subimage and features are extracted from each subimage based on statistical measures of the gray tone distribution, according to the method of Haralick [1]. Twenty parameters are derived from each subimage and presented to a Probabilistic Neural Network (PNN) [2] for classification. This number of parameters was found to be optimal for the system. The PNN is a hierarchical, feed-forward network that can be rapidly reconfigured as additional training data become available. Training data is gathered by reviewing digital images of many crystals during their growth cycle and compiling two sets of images, those with and without irregularities. 6 refs., 4 figs

Aligned nanowire growth using lithography-assisted bonding of a polycarbonate template for neural probe electrodes

International Nuclear Information System (INIS)

Yoon, Hargsoon; Deshpande, Devesh C; Ramachandran, Vasuda; Varadan, Vijay K

2008-01-01

This research presents a fabrication method of vertically aligned nanowires on substrates using lithography-assisted template bonding (LATB) towards developing highly efficient electrodes for biomedical applications at low cost. A polycarbonate template containing cylindrical nanopores is attached to a substrate and the nanopores are selectively opened with a modified lithography process. Vertically aligned nanowires are grown by electrochemical deposition through these open pores on polyimide film and silicon substrates. The process of opening the nanopores is optimized to yield uniform growth of nanowires. The morphological, crystalline, and electrochemical properties of the resulting vertically aligned nanowires are discussed using scanning electron microscopy (SEM), x-ray diffraction (XRD), and electrochemical analysis tools. The potential application of this simple and inexpensive fabrication technology is discussed in the development of neural probe electrodes

Catch-up growth following fetal growth restriction promotes rapid restoration of fat mass but without metabolic consequences at one year of age.

Directory of Open Access Journals (Sweden)

Jacques Beltrand

Full Text Available BACKGROUND: Fetal growth restriction (FGR followed by rapid weight gain during early life has been suggested to be the initial sequence promoting central adiposity and insulin resistance. However, the link between fetal and early postnatal growth and the associated anthropometric and metabolic changes have been poorly studied. METHODOLOGY/PRINCIPAL FINDINGS: Over the first year of post-natal life, changes in body mass index, skinfold thickness and hormonal concentrations were prospectively monitored in 94 infants in whom the fetal growth velocity had previously been measured using a repeated standardized procedure of ultrasound fetal measurements. 45 infants, thinner at birth, had experienced previous FGR (FGR+ regardless of birth weight. Growth pattern in the first four months of life was characterized by greater change in BMI z-score in FGR+ (+1.26+/-1.2 vs +0.58 +/-1.17 SD in FGR- resulting in the restoration of BMI and of fat mass to values similar to FGR-, independently of caloric intakes. Growth velocity after 4 months was similar and BMI z-score and fat mass remained similar at 12 months of age. At both time-points, fetal growth velocity was an independent predictor of fat mass in FGR+. At one year, fasting insulin levels were not different but leptin was significantly higher in the FGR+ (4.43+/-1.41 vs 2.63+/-1 ng/ml in FGR-. CONCLUSION: Early catch-up growth is related to the fetal growth pattern itself, irrespective of birth weight, and is associated with higher insulin sensitivity and lower leptin levels after birth. Catch-up growth promotes the restoration of body size and fat stores without detrimental consequences at one year of age on body composition or metabolic profile. The higher leptin concentration at one year may reflect a positive energy balance in children who previously faced fetal growth restriction.

Envisaging the Regulation of Alkaloid Biosynthesis and Associated Growth Kinetics in Hairy Roots of Vinca minor Through the Function of Artificial Neural Network.

Science.gov (United States)

Verma, Priyanka; Anjum, Shahin; Khan, Shamshad Ahmad; Roy, Sudeep; Odstrcilik, Jan; Mathur, Ajay Kumar

2016-03-01

Artificial neural network based modeling is a generic approach to understand and correlate different complex parameters of biological systems for improving the desired output. In addition, some new inferences can also be predicted in a shorter time with less cost and labor. As terpenoid indole alkaloid pathway in Vinca minor is very less investigated or elucidated, a strategy of elicitation with hydroxylase and acetyltransferase along with incorporation of various precursors from primary shikimate and secoiridoid pools via simultaneous employment of cyclooxygenase inhibitor was performed in the hairy roots of V. minor. This led to the increment in biomass accumulation, total alkaloid concentration, and vincamine production in selected treatments. The resultant experimental values were correlated with algorithm approaches of artificial neural network that assisted in finding the yield of vincamine, alkaloids, and growth kinetics using number of elicits. The inputs were the hydroxylase/acetyltransferase elicitors and cyclooxygenase inhibitor along with various precursors from shikimate and secoiridoid pools and the outputs were growth index (GI), alkaloids, and vincamine. The approach incorporates two MATLAB codes; GRNN and FFBPNN. Growth kinetic studies revealed that shikimate and tryptophan supplementation triggers biomass accumulation (GI = 440.2 to 540.5); while maximum alkaloid (3.7 % dry wt.) and vincamine production (0.017 ± 0.001 % dry wt.) was obtained on supplementation of secologanin along with tryptophan, naproxen, hydrogen peroxide, and acetic anhydride. The study shows that experimental and predicted values strongly correlate each other. The correlation coefficient for growth index (GI), alkaloids, and vincamine was found to be 0.9997, 0.9980, 0.9511 in GRNN and 0.9725, 0.9444, 0.9422 in FFBPNN, respectively. GRNN provided greater similarity between the target and predicted dataset in comparison to FFBPNN. The findings can provide future

Polygenic risk, rapid childhood growth, and the development of obesity: evidence from a 4-decade longitudinal study.

Science.gov (United States)

Belsky, Daniel W; Moffitt, Terrie E; Houts, Renate; Bennett, Gary G; Biddle, Andrea K; Blumenthal, James A; Evans, James P; Harrington, Honalee; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Caspi, Avshalom

2012-06-01

To test how genomic loci identified in genome-wide association studies influence the development of obesity. A 38-year prospective longitudinal study of a representative birth cohort. The Dunedin Multidisciplinary Health and Development Study, Dunedin, New Zealand. One thousand thirty-seven male and female study members. We assessed genetic risk with a multilocus genetic risk score. The genetic risk score was composed of single-nucleotide polymorphisms identified in genome-wide association studies of obesity-related phenotypes. We assessed family history from parent body mass index data collected when study members were 11 years of age. Body mass index growth curves, developmental phenotypes of obesity, and adult obesity outcomes were defined from anthropometric assessments at birth and at 12 subsequent in-person interviews through 38 years of age. Individuals with higher genetic risk scores were more likely to be chronically obese in adulthood. Genetic risk first manifested as rapid growth during early childhood. Genetic risk was unrelated to birth weight. After birth, children at higher genetic risk gained weight more rapidly and reached adiposity rebound earlier and at a higher body mass index. In turn, these developmental phenotypes predicted adult obesity, mediating about half the genetic effect on adult obesity risk. Genetic associations with growth and obesity risk were independent of family history, indicating that the genetic risk score could provide novel information to clinicians. Genetic variation linked with obesity risk operates, in part, through accelerating growth in the early childhood years after birth. Etiological research and prevention strategies should target early childhood to address the obesity epidemic.

Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design

Science.gov (United States)

Schaffer, J. David

2015-06-01

Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.

Growth and structure of rapid thermal silicon oxides and nitroxides studied by spectroellipsometry and Auger electron spectroscopy

Science.gov (United States)

Gonon, N.; Gagnaire, A.; Barbier, D.; Glachant, A.

1994-11-01

Rapid thermal oxidation of Czochralski-grown silicon in either O2 or N2O atmospheres have been studied using spectroellipsometry and Auger electron spectroscopy. Multiwavelength ellipsometric data were processed in order to separately derive the thickness and refractive indexes of rapid thermal dielectrics. Results revealed a significant increase of the mean refractive index as the film thickness falls below 20 nm for both O2 or N2O oxidant species. A multilayer structure including an about 0.3-nm-thick interfacial region of either SiO(x) or nitroxide in the case of O2 and N2O growth, respectively, followed by a densified SiO2 layer, was found to accurately fit the experimental data. The interfacial region together with the densified state of SiO2 close to the interface suggest a dielectric structure in agreement with the continuous random network model proposed for classical thermal oxides. Auger electron spectroscopy analysis confirmed the presence of noncrystalline Si-Si bonds in the interfacial region, mostly in the case of thin oxides grown in O2. It was speculated that the initial fast growth regime was due to a transient oxygen supersaturation in the interfacial region. Besides, the self-limiting growth in N2O was confirmed and explained in agreement with several recently published data, by the early formation of a very thin nitride or oxynitride membrane in the highly densified oxide beneath the interface. The beneficial effect of direct nitrogen incorporation by rapid thermal oxidation in N2O instead of O2 for the electrical behavior of metal-oxide-semiconductor capacitors is likely a better SiO2/Si lattice accommodation through the reduction of stresses and Si-Si bonds in the interfacial region of the dielectric.

Growth in Rapid Automatized Naming from Grades K to 8 in Children with Math or Reading Disabilities

Science.gov (United States)

Mazzocco, Michèle M. M.; Grimm, Kevin J.

2013-01-01

Rapid automatized naming (RAN) is widely used to identify reading disabilities (RD) and has recently been considered a potential predictor of risk for mathematics learning disabilities (MLD). Here we longitudinally examine RAN performance from Grades K to 8, to view how growth on RAN response time differs for children with RD versus MLD. Across…

Research on water hammer forces caused by rapid growth of bubbles at severe accidents of water cooled reactors

International Nuclear Information System (INIS)

Inasaka, Fujio; Adachi, Masaki; Aya, Izuo

2004-01-01

At severe accidents of Water Cooled Reactors a great deal of gas is expected to be produced in a short time within the water of lower part of nuclear pressure vessel and containment vessel caused by hydrogen production with a metal water reaction and steam explosions with direct contact of melting core and water. Water hammer forces caused by rapid growth of bubbles shall work on the wall of containment vessel and affect its integrity. Coherency of water block movement is not clear, whether simultaneous or in the same direction. Water block behavior and water hammer forces caused by rapid growth of bubbles have been tested using a modified scale model and analyzed to obtain experimental correlated equation to estimate water block's rising distance and velocity from water hammer data. Numerical analysis using RELAP5-3D (Reactor Excursion and Leak Analysis Program) has been conducted to evaluate water hammer forces and makes clear its modifications needed. (T. Tanaka)

Nonequilibrium landscape theory of neural networks

Science.gov (United States)

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-01-01

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

Nonequilibrium landscape theory of neural networks.

Science.gov (United States)

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-11-05

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

Coral reef growth in an era of rapidly rising sea level: predictions and suggestions for long-term research

Energy Technology Data Exchange (ETDEWEB)

Buddemeier, R W; Smith, S V

1988-01-01

Coral reef growth is intimately linked to sea level. It has been postulated that over the next century, sea level will rise at a probable average rate of 15 mm/year, in response to fossil fuel emissions, heating, and melting of the Antarctic ice cap. This predicted rate of sea level rise is five times the present modal rate of vertical accretion on coral reef flats and 50% greater than the maximum vertical accretion rates apparently attained by coral reefs. We use these predictions and observations to offer the following hypothesis for reef growth over the next century. The vertical accretion rates of protected reef flats will accelerate from the present modal rate up to the maximum rate, in response to the more rapidly rising sea level. This more rapid vertical accretion rate will be insufficient to keep up with sea level rise, if present predictions prove to be correct. Less protected reef flats will slow their rate of growth as they become inundated and subjected to erosion by progressively larger waves. This projected sea level rise and postulated reef response will provide an opportunity for long- term studies of the response of coral reef systems to a predictable and measurable forcing function.

A cell junction pathology of neural stem cells leads to abnormal neurogenesis and hydrocephalus

NARCIS (Netherlands)

Rodríguez, Esteban M; Guerra, María M; Vío, Karin; González, César; Ortloff, Alexander; Bátiz, Luis F; Rodríguez, Sara; Jara, María C; Muñoz, Rosa I; Ortega, Eduardo; Jaque, Jaime; Guerra, Francisco; Sival, Deborah A; den Dunnen, Wilfred F A; Jiménez, Antonio J; Domínguez-Pinos, María D; Pérez-Fígares, José M; McAllister, James P; Johanson, Conrad

2012-01-01

Most cells of the developing mammalian brain derive from the ventricular (VZ) and the subventricular (SVZ) zones. The VZ is formed by the multipotent radial glia/neural stem cells (NSCs) while the SVZ harbors the rapidly proliferative neural precursor cells (NPCs). Evidence from human and animal

A decade of rapid change: Biocultural influences on child growth in highland Peru.

Science.gov (United States)

Oths, Kathryn S; Smith, Hannah N; Stein, Max J; Lazo Landivar, Rodrigo J

2018-03-01

In the past decade many areas of Peru have been undergoing extreme environmental, economic, and cultural change. In the highland hamlet of Chugurpampa, La Libertad, climate change has ruined harvests and led to frequent periods of migration to the coast in search of livelihood. This biocultural research examines how the changes could be affecting the growth of children who maintain residence in the highlands. Clinical records from the early 2000s were compared to those from the early 2010s. Charts were randomly selected to record anthropometric data, netting a sample of 75 children ages 0-60 months of age. Analysis of covariance was run to compare mean stature, weight, and BMI between cohorts. Percentage of children who fall below the -2 threshold for z-scores for height and weight were compared by age and cohort. A significant secular trend in growth was found, with children born more recently larger than those born a decade before. The effect is most notable in the first year of life, with the growth advantage attenuated by the age of 3 for height and age 4 for weight. While children were unlikely to be stunted from 0 to 3 years of age, 44% of the later cohort were stunted and 11% were underweight from 4 to 5 years of age. Three possible explanations for the rapid shift are entertained: more time spent on the coast during gestation and early childhood, which may attenuate the effect of hypoxia on child growth; dietary change; and increased use of biomedicine. © 2017 Wiley Periodicals, Inc.

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

Science.gov (United States)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1997-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Rapid consolidation of new knowledge in adulthood via fast mapping.

Science.gov (United States)

Coutanche, Marc N; Thompson-Schill, Sharon L

2015-09-01

Rapid word learning, where words are 'fast mapped' onto new concepts, may help build vocabulary during childhood. Recent evidence has suggested that fast mapping might help to rapidly integrate information into memory networks of the adult neocortex. The neural basis for this learning by fast mapping determines key properties of the learned information. Copyright © 2015 Elsevier Ltd. All rights reserved.

A review of organic and inorganic biomaterials for neural interfaces.

Science.gov (United States)

Fattahi, Pouria; Yang, Guang; Kim, Gloria; Abidian, Mohammad Reza

2014-03-26

Recent advances in nanotechnology have generated wide interest in applying nanomaterials for neural prostheses. An ideal neural interface should create seamless integration into the nervous system and performs reliably for long periods of time. As a result, many nanoscale materials not originally developed for neural interfaces become attractive candidates to detect neural signals and stimulate neurons. In this comprehensive review, an overview of state-of-the-art microelectrode technologies provided fi rst, with focus on the material properties of these microdevices. The advancements in electro active nanomaterials are then reviewed, including conducting polymers, carbon nanotubes, graphene, silicon nanowires, and hybrid organic-inorganic nanomaterials, for neural recording, stimulation, and growth. Finally, technical and scientific challenges are discussed regarding biocompatibility, mechanical mismatch, and electrical properties faced by these nanomaterials for the development of long-lasting functional neural interfaces.

Rapid Population Growth and Human Carrying Capacity: Two Perspectives. World Bank Staff Working Papers No. 690 and Population and Development Series No. 15.

Science.gov (United States)

Mahar, Dennis J., Ed.; And Others

Two perspectives on carrying capacity and population growth are examined. The first perspective, "Carrying Capacity and Rapid Population Growth: Definition, Cases, and Consequences" (Robert Muscat), explores the possible meanings of the idea of carrying capacity under developing country conditions, looks at historical and present-day cases of…

JINR rapid communications

International Nuclear Information System (INIS)

1996-01-01

The present collection of rapid communications from JINR, Dubna, contains five separate reports on analytic QCD running coupling with finite IR behaviour and universal α bar s (0) value, quark condensate in the interacting pion- nucleon medium at finite temperature and baryon number density, γ-π 0 discrimination with a shower maximum detector using neural networks for the solenoidal tracker at RHIC, off-specular neutron reflection from magnetic media with nondiagonal reflectivity matrices and molecular cytogenetics of radiation-induced gene mutations in Drosophila melanogaster. 21 fig., 1 tab

The neural basis of speech sound discrimination from infancy to adulthood

OpenAIRE

Partanen, Eino

2013-01-01

Rapid processing of speech is facilitated by neural representations of native language phonemes. However, some disorders and developmental conditions, such as developmental dyslexia, can hamper the development of these neural memory traces, leading to language delays and poor academic achievement. While the early identification of such deficits is paramount so that interventions can be started as early as possible, there is currently no systematically used ecologically valid paradigm for the ...

A New Controller to Enhance PV System Performance Based on Neural Network

Directory of Open Access Journals (Sweden)

Roshdy A AbdelRassoul

2017-06-01

Full Text Available In recent years, a radical increase of photovoltaic (PV power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system. Neural controller is optimized using particle swarm optimization (PSO   leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become 0.00001% and 0.1798 seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.In recent years, a radical increase of photovoltaic (PV power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system. Neural controller is optimized using particle swarm optimization (PSO   leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become 0.00001% and 0.1798 seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.

Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using Response Surface Methodology and Artificial Neural Network

Directory of Open Access Journals (Sweden)

Mohamad, R.

2013-01-01

Full Text Available Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorganisms. Methodology and Results: In this study, response surface methodology (RSM and artificial neural network (ANN were employed to optimize the carbon and nitrogen sources in order to improve growth rate of Monascus purpureus FTC5391,a new local isolate. The best models for optimization of growth rate were a multilayer full feed-forward incremental back propagation network, and a modified response surface model using backward elimination. The optimum condition for cell mass production was: sucrose 2.5%, yeast extract 0.045%, casamino acid 0.275%, sodium nitrate 0.48%, potato starch 0.045%, dextrose 1%, potassium nitrate 0.57%. The experimental cell mass production using this optimal condition was 21 mg/plate/12days, which was 2.2-fold higher than the standard condition (sucrose 5%, yeast extract 0.15%, casamino acid 0.25%, sodium nitrate 0.3%, potato starch 0.2%, dextrose 1%, potassium nitrate 0.3%. Conclusion, significance and impact of study: The results of RSM and ANN showed that all carbon and nitrogen sources tested had significant effect on growth rate (P-value < 0.05. In addition the use of RSM and ANN alongside each other provided a proper growth prediction model.

Artificial Neural Networks and the Mass Appraisal of Real Estate

Directory of Open Access Journals (Sweden)

Gang Zhou

2018-03-01

Full Text Available With the rapid development of computer, artificial intelligence and big data technology, artificial neural networks have become one of the most powerful machine learning algorithms. In the practice, most of the applications of artificial neural networks use back propagation neural network and its variation. Besides the back propagation neural network, various neural networks have been developing in order to improve the performance of standard models. Though neural networks are well known method in the research of real estate, there is enormous space for future research in order to enhance their function. Some scholars combine genetic algorithm, geospatial information, support vector machine model, particle swarm optimization with artificial neural networks to appraise the real estate, which is helpful for the existing appraisal technology. The mass appraisal of real estate in this paper includes the real estate valuation in the transaction and the tax base valuation in the real estate holding. In this study we focus on the theoretical development of artificial neural networks and mass appraisal of real estate, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, and review the existing literature about artificial neural networks and mass appraisal of real estate. Finally, we provide some suggestions for the mass appraisal of China's real estate.

Novel paths towards neural cellular products for neurological disorders.

Science.gov (United States)

Daadi, Marcel M

2011-11-01

The prospect of using neural cells derived from stem cells or from reprogrammed adult somatic cells provides a unique opportunity in cell therapy and drug discovery for developing novel strategies for brain repair. Cell-based therapeutic approaches for treating CNS afflictions caused by disease or injury aim to promote structural repair of the injured or diseased neural tissue, an outcome currently not achieved by drug therapy. Preclinical research in animal models of various diseases or injuries report that grafts of neural cells enhance endogenous repair, provide neurotrophic support to neurons undergoing degeneration and replace lost neural cells. In recent years, the sources of neural cells for treating neurological disorders have been rapidly expanding and in addition to offering therapeutic potential, neural cell products hold promise for disease modeling and drug discovery use. Specific neural cell types have been derived from adult or fetal brain, from human embryonic stem cells, from induced pluripotent stem cells and directly transdifferentiated from adult somatic cells, such as skin cells. It is yet to be determined if the latter approach will evolve into a paradigm shift in the fields of stem cell research and regenerative medicine. These multiple sources of neural cells cover a wide spectrum of safety that needs to be balanced with efficacy to determine the viability of the cellular product. In this article, we will review novel sources of neural cells and discuss current obstacles to developing them into viable cellular products for treating neurological disorders.

Rapid growth within India

International Nuclear Information System (INIS)

Hayes, D.

2000-01-01

The Indian government has published (in Hydrocarbon Vision 2025) its ideas for a long term strategy for its oil industry which is currently growing at an unprecedented rate. Increasing domestic production and investment in oil exploration and production overseas figure strongly in the plan. At present, India has a refining surplus but with an annual growth of 8-10%, this will disappear in the next 2-3 years. The report recommends that India should maintain 90% self-sufficiency in refining. The report sees development of the domestic oil industry as globally competitive and helping safeguard India's assets. The capability of India's refineries, current upgrading, the newer refineries and plans for new projects are all mentioned

Capacity of Human Dental Follicle Cells to Differentiate into Neural Cells In Vitro

Directory of Open Access Journals (Sweden)

Shingo Kanao

2017-01-01

Full Text Available The dental follicle is an ectomesenchymal tissue surrounding the developing tooth germ. Human dental follicle cells (hDFCs have the capacity to commit to differentiation into multiple cell types. Here we investigated the capacity of hDFCs to differentiate into neural cells and the efficiency of a two-step strategy involving floating neurosphere-like bodies for neural differentiation. Undifferentiated hDFCs showed a spindle-like morphology and were positive for neural markers such as nestin, β-III-tubulin, and S100β. The cellular morphology of several cells was neuronal-like including branched dendrite-like processes and neurites. Next, hDFCs were used for neurosphere formation in serum-free medium containing basic fibroblast growth factor, epidermal growth factor, and B27 supplement. The number of cells with neuronal-like morphology and that were strongly positive for neural markers increased with sphere formation. Gene expression of neural markers also increased in hDFCs with sphere formation. Next, gene expression of neural markers was examined in hDFCs during neuronal differentiation after sphere formation. Expression of Musashi-1 and Musashi-2, MAP2, GFAP, MBP, and SOX10 was upregulated in hDFCs undergoing neuronal differentiation via neurospheres, whereas expression of nestin and β-III-tubulin was downregulated. In conclusion, hDFCs may be another optimal source of neural/glial cells for cell-based therapies to treat neurological diseases.

Analysis of Neural Stem Cells from Human Cortical Brain Structures In Vitro.

Science.gov (United States)

Aleksandrova, M A; Poltavtseva, R A; Marei, M V; Sukhikh, G T

2016-05-01

Comparative immunohistochemical analysis of the neocortex from human fetuses showed that neural stem and progenitor cells are present in the brain throughout the gestation period, at least from week 8 through 26. At the same time, neural stem cells from the first and second trimester fetuses differed by the distribution, morphology, growth, and quantity. Immunocytochemical analysis of neural stem cells derived from fetuses at different gestation terms and cultured under different conditions showed their differentiation capacity. Detailed analysis of neural stem cell populations derived from fetuses on gestation weeks 8-9, 18-20, and 26 expressing Lex/SSEA1 was performed.

Speaker diarization system using HXLPS and deep neural network

Directory of Open Access Journals (Sweden)

V. Subba Ramaiah

2018-03-01

Full Text Available In general, speaker diarization is defined as the process of segmenting the input speech signal and grouped the homogenous regions with regard to the speaker identity. The main idea behind this system is that it is able to discriminate the speaker signal by assigning the label of the each speaker signal. Due to rapid growth of broadcasting and meeting, the speaker diarization is burdensome to enhance the readability of the speech transcription. In order to solve this issue, Holoentropy with the eXtended Linear Prediction using autocorrelation Snapshot (HXLPS and deep neural network (DNN is proposed for the speaker diarization system. The HXLPS extraction method is newly developed by incorporating the Holoentropy with the XLPS. Once we attain the features, the speech and non-speech signals are detected by the Voice Activity Detection (VAD method. Then, i-vector representation of every segmented signal is obtained using Universal Background Model (UBM model. Consequently, DNN is utilized to assign the label for the speaker signal which is then clustered according to the speaker label. The performance is analysed using the evaluation metrics, such as tracking distance, false alarm rate and diarization error rate. The outcome of the proposed method ensures the better diarization performance by achieving the lower DER of 1.36% based on lambda value and DER of 2.23% depends on the frame length. Keywords: Speaker diarization, HXLPS feature extraction, Voice activity detection, Deep neural network, Speaker clustering, Diarization Error Rate (DER

Rapid population growth and fragile environments: the sub-Saharan African and south Asian experience.

Science.gov (United States)

Caldwell, J C; Caldwell, P

1994-02-18

Case studies of the world's two poorest regions, sub-Saharan Africa and South Asia, were used to illustrate the compromised standard of living of the poor and environmental damage due to continued rapid population growth. The conclusion was that the livelihoods of the poor should not be endangered for preserving the living standards of richer people. Nations must not ignore the challenges of reducing population growth as fast as can be achieved. The transitional period over the next 50 years is the main concern, because population growth rates will be slowing. Rural population growth is expected to decline from 60% of total population growth in South Asia to 7% between 2000 and 2025; similarly the decline in sub-Saharan Africa would be from 50% to 15%. Over the past 30 years, food production in South Asia has kept pace with population growth. Sub-Saharan Africa has adopted food importation to meet demand. African problems are a low resource base, faster population growth, and the fact that governments and individuals are too poor to maintain soil fertility. Long-term studies of how much soil depletion will occur are not available for these regions, and local area studies are not as pessimistic. Transition policies are needed to put "people first in terms of engineered or directed population and ecological change." The six main issues are the following: 1) the Brundtland Commission appropriately identified poverty as the main cause and effect of environmental degradation because of the threat to survival; 2) the verdict is still out about whether food production will keep pace with population growth through economic growth and investment in agriculture; 3) empirical research is needed to examine local social and regulatory institutions and the possibility of reinforcing these mechanisms rather than instituting central controls; 4) central coercion or modernizing economic policies can destroy local level controls; 5) famine is a complex ecological phenomenon and the

The Rapid Urban Growth Triad: A New Conceptual Framework for Examining the Urban Transition in Developing Countries

Directory of Open Access Journals (Sweden)

Kyle Farrell

2017-08-01

Full Text Available Although the urban transition is a universal event that unfolds in all countries, the determinants, patterns, and outcomes do not necessarily follow a uniform process. With the urban transition being basically completed in developed countries around the turn of the 21st century, the growth of cities today is almost entirely confined to developing countries. Still, much of our conceptual understanding of this process is derived from earlier accounts, with definitions rooted in a historical context. This has resulted in common misconceptions such as a tendency to view the growth of cities primarily as an outcome of rural to urban migration, neglecting the growing contributions of urban natural population increase and reclassification of rural areas. A tendency to treat the components of urban growth in isolation has created a rift within the urban studies discourse, preventing any real theorization of their combined impacts and the interplay among them. Applying a systems thinking approach, this paper introduces a multidisciplinary framework for conceptualizing rapid urban growth in developing countries. The framework offers explanatory power to previously neglected components of urban growth and serves as a diagnostic for examining the urban transition—ultimately revealing new policy levers for managing it in a sustainable way.

A simple miniature device for wireless stimulation of neural circuits in small behaving animals.

Science.gov (United States)

Zhang, Yisi; Langford, Bruce; Kozhevnikov, Alexay

2011-10-30

The use of wireless neural stimulation devices offers significant advantages for neural stimulation experiments in behaving animals. We demonstrate a simple, low-cost and extremely lightweight wireless neural stimulation device which is made from off-the-shelf components. The device has low power consumption and does not require a high-power RF preamplifier. Neural stimulation can be carried out in either a voltage source mode or a current source mode. Using the device, we carry out wireless stimulation in the premotor brain area HVC of a songbird and demonstrate that such stimulation causes rapid perturbations of the acoustic structure of the song. Published by Elsevier B.V.

A neural cell adhesion molecule-derived fibroblast growth factor receptor agonist, the FGL-peptide, promotes early postnatal sensorimotor development and enhances social memory retention

DEFF Research Database (Denmark)

Secher, Thomas; Novitskaia, V; Berezin, Vladimir

2006-01-01

of coordination skills. In adult animals s.c. administration of FGL resulted in a prolonged retention of social memory. We found that FGL rapidly penetrated into the blood and cerebrospinal fluid after both intranasal and s.c. administration and remained detectable in the fluids for up to 5 hours.......The neural cell adhesion molecule (NCAM) belongs to the immunoglobulin (Ig) superfamily and is composed extracellularly of five Ig-like and two fibronectin type III (F3) modules. It plays a pivotal role in neuronal development and synaptic plasticity. NCAM signals via a direct interaction...

Higher-order neural network software for distortion invariant object recognition

Science.gov (United States)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Toward automatic time-series forecasting using neural networks.

Science.gov (United States)

Yan, Weizhong

2012-07-01

Over the past few decades, application of artificial neural networks (ANN) to time-series forecasting (TSF) has been growing rapidly due to several unique features of ANN models. However, to date, a consistent ANN performance over different studies has not been achieved. Many factors contribute to the inconsistency in the performance of neural network models. One such factor is that ANN modeling involves determining a large number of design parameters, and the current design practice is essentially heuristic and ad hoc, this does not exploit the full potential of neural networks. Systematic ANN modeling processes and strategies for TSF are, therefore, greatly needed. Motivated by this need, this paper attempts to develop an automatic ANN modeling scheme. It is based on the generalized regression neural network (GRNN), a special type of neural network. By taking advantage of several GRNN properties (i.e., a single design parameter and fast learning) and by incorporating several design strategies (e.g., fusing multiple GRNNs), we have been able to make the proposed modeling scheme to be effective for modeling large-scale business time series. The initial model was entered into the NN3 time-series competition. It was awarded the best prediction on the reduced dataset among approximately 60 different models submitted by scholars worldwide.

Plant Growth and Development: An Outline for a Unit Structured Around the Life Cycle of Rapid-Cycling Brassica Rapa.

Science.gov (United States)

Becker, Wayne M.

This outline is intended for use in a unit of 10-12 lectures on plant growth and development at the introductory undergraduate level as part of a course on organismal biology. The series of lecture outlines is structured around the life cycle of rapid-cycling Brassica rapa (RCBr). The unit begins with three introductory lectures on general plant…

Development of target-tracking algorithms using neural network

Energy Technology Data Exchange (ETDEWEB)

Park, Dong Sun; Lee, Joon Whaoan; Yoon, Sook; Baek, Seong Hyun; Lee, Myung Jae [Chonbuk National University, Chonjoo (Korea)

1998-04-01

The utilization of remote-control robot system in atomic power plants or nuclear-related facilities grows rapidly, to protect workers form high radiation environments. Such applications require complete stability of the robot system, so that precisely tracking the robot is essential for the whole system. This research is to accomplish the goal by developing appropriate algorithms for remote-control robot systems. A neural network tracking system is designed and experimented to trace a robot Endpoint. This model is aimed to utilized the excellent capabilities of neural networks; nonlinear mapping between inputs and outputs, learning capability, and generalization capability. The neural tracker consists of two networks for position detection and prediction. Tracking algorithms are developed and experimented for the two models. Results of the experiments show that both models are promising as real-time target-tracking systems for remote-control robot systems. (author). 10 refs., 47 figs.

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity.

Science.gov (United States)

Kafi, Md Abdul; Cho, Hyeon-Yeol; Choi, Jeong Woo

2015-07-02

Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD) or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C), C(RGD)₄ ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot) or three dimensional (rod or pillar) like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD), graphene oxide (GO) and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies.

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity

Directory of Open Access Journals (Sweden)

Md. Abdul Kafi

2015-07-01

Full Text Available Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C, C(RGD4 ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot or three dimensional (rod or pillar like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD, graphene oxide (GO and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies.

Neural regulation of glucagon-like peptide-1 secretion in pigs

DEFF Research Database (Denmark)

Hansen, Lene; Lampert, Sarah; Mineo, Hitoshi

2004-01-01

Glucagon-like peptide (GLP)-1 is secreted rapidly from the intestine postprandially. We therefore investigated its possible neural regulation. With the use of isolated perfused porcine ileum, GLP-1 secretion was measured in response to electrical stimulation of the mixed, perivascular nerve supply...

Function of FEZF1 during early neural differentiation of human embryonic stem cells.

Science.gov (United States)

Liu, Xin; Su, Pei; Lu, Lisha; Feng, Zicen; Wang, Hongtao; Zhou, Jiaxi

2018-01-01

The understanding of the mechanism underlying human neural development has been hampered due to lack of a cellular system and complicated ethical issues. Human embryonic stem cells (hESCs) provide an invaluable model for dissecting human development because of unlimited self-renewal and the capacity to differentiate into nearly all cell types in the human body. In this study, using a chemical defined neural induction protocol and molecular profiling, we identified Fez family zinc finger 1 (FEZF1) as a potential regulator of early human neural development. FEZF1 is rapidly up-regulated during neural differentiation in hESCs and expressed before PAX6, a well-established marker of early human neural induction. We generated FEZF1-knockout H1 hESC lines using CRISPR-CAS9 technology and found that depletion of FEZF1 abrogates neural differentiation of hESCs. Moreover, loss of FEZF1 impairs the pluripotency exit of hESCs during neural specification, which partially explains the neural induction defect caused by FEZF1 deletion. However, enforced expression of FEZF1 itself fails to drive neural differentiation in hESCs, suggesting that FEZF1 is necessary but not sufficient for neural differentiation from hESCs. Taken together, our findings identify one of the earliest regulators expressed upon neural induction and provide insight into early neural development in human.

Neural network approaches to tracer identification as related to PIV research

International Nuclear Information System (INIS)

Seeley, C.H. Jr.

1992-12-01

Neural networks have become very powerful tools in many fields of interest. This thesis examines the application of neural networks to another rapidly growing field flow visualization. Flow visualization research is used to experimentally determine how fluids behave and to verify computational results obtained analytically. A form of flow visualization, particle image velocimetry (PIV). determines the flow movement by tracking neutrally buoyant particles suspended in the fluid. PIV research has begun to improve rapidly with the advent of digital imagers, which can quickly digitize an image into arrays of grey levels. These grey level arrays are analyzed to determine the location of the tracer particles. Once the particles positions have been determined across multiple image frames, it is possible to track their movements, and hence, the flow of the fluid. This thesis explores the potential of several different neural networks to identify the positions of the tracer particles. Among these networks are Backpropagation, Kohonen (counter-propagation), and Cellular. Each of these algorithms were employed in their basic form, and training and testing were performed on a synthetic grey level array. Modifications were then made to them in attempts to improve the results

Neural network approaches to tracer identification as related to PIV research

Energy Technology Data Exchange (ETDEWEB)

Seeley, C.H. Jr.

1992-12-01

Neural networks have become very powerful tools in many fields of interest. This thesis examines the application of neural networks to another rapidly growing field flow visualization. Flow visualization research is used to experimentally determine how fluids behave and to verify computational results obtained analytically. A form of flow visualization, particle image velocimetry (PIV). determines the flow movement by tracking neutrally buoyant particles suspended in the fluid. PIV research has begun to improve rapidly with the advent of digital imagers, which can quickly digitize an image into arrays of grey levels. These grey level arrays are analyzed to determine the location of the tracer particles. Once the particles positions have been determined across multiple image frames, it is possible to track their movements, and hence, the flow of the fluid. This thesis explores the potential of several different neural networks to identify the positions of the tracer particles. Among these networks are Backpropagation, Kohonen (counter-propagation), and Cellular. Each of these algorithms were employed in their basic form, and training and testing were performed on a synthetic grey level array. Modifications were then made to them in attempts to improve the results.

The Seneca effect why growth is slow but collapse is rapid

CERN Document Server

Bardi, Ugo

2017-01-01

The essence of this book can be found in a line written by the ancient Roman Stoic Philosopher Lucius Annaeus Seneca: "Fortune is of sluggish growth, but ruin is rapid". This sentence summarizes the features of the phenomenon that we call "collapse," which is typically sudden and often unexpected, like the proverbial "house of cards." But why are such collapses so common, and what generates them? Several books have been published on the subject, including the well-known "Collapse" by Jared Diamond (2005), "The collapse of complex societies" by Joseph Tainter (1998) and "The Tipping Point," by Malcom Gladwell (2000). Why The Seneca Effect? This book is an ambitious attempt to pull these various strands together by describing collapse from a multi-disciplinary viewpoint. The reader will discover how collapse is a collective phenomenon that occurs in what we call today "complex systems," with a special emphasis on system dynamics and t he concept of "feedback." From this foundation, Bardi applies the...

Efficient and Rapid Derivation of Primitive Neural Stem Cells and Generation of Brain Subtype Neurons From Human Pluripotent Stem Cells

OpenAIRE

Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C.

2013-01-01

This study developed a highly efficient serum-free pluripotent stem cell (PSC) neural induction medium that can induce human PSCs into primitive neural stem cells (NSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. This method of primitive NSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

Three-dimensional hydrogel cell culture systems for modeling neural tissue

Science.gov (United States)

Frampton, John

Two-dimensional (2-D) neural cell culture systems have served as physiological models for understanding the cellular and molecular events that underlie responses to physical and chemical stimuli, control sensory and motor function, and lead to the development of neurological diseases. However, the development of three-dimensional (3-D) cell culture systems will be essential for the advancement of experimental research in a variety of fields including tissue engineering, chemical transport and delivery, cell growth, and cell-cell communication. In 3-D cell culture, cells are provided with an environment similar to tissue, in which they are surrounded on all sides by other cells, structural molecules and adhesion ligands. Cells grown in 3-D culture systems display morphologies and functions more similar to those observed in vivo, and can be cultured in such a way as to recapitulate the structural organization and biological properties of tissue. This thesis describes a hydrogel-based culture system, capable of supporting the growth and function of several neural cell types in 3-D. Alginate hydrogels were characterized in terms of their biomechanical and biochemical properties and were functionalized by covalent attachment of whole proteins and peptide epitopes. Methods were developed for rapid cross-linking of alginate hydrogels, thus permitting the incorporation of cells into 3-D scaffolds without adversely affecting cell viability or function. A variety of neural cell types were tested including astrocytes, microglia, and neurons. Cells remained viable and functional for longer than two weeks in culture and displayed process outgrowth in 3-D. Cell constructs were created that varied in cell density, type and organization, providing experimental flexibility for studying cell interactions and behavior. In one set of experiments, 3-D glial-endothelial cell co-cultures were used to model blood-brain barrier (BBB) structure and function. This co-culture system was

Artificial neural network-based model for the prediction of optimal growth and culture conditions for maximum biomass accumulation in multiple shoot cultures of Centella asiatica.

Science.gov (United States)

Prasad, Archana; Prakash, Om; Mehrotra, Shakti; Khan, Feroz; Mathur, Ajay Kumar; Mathur, Archana

2017-01-01

An artificial neural network (ANN)-based modelling approach is used to determine the synergistic effect of five major components of growth medium (Mg, Cu, Zn, nitrate and sucrose) on improved in vitro biomass yield in multiple shoot cultures of Centella asiatica. The back propagation neural network (BPNN) was employed to predict optimal biomass accumulation in terms of growth index over a defined culture duration of 35 days. The four variable concentrations of five media components, i.e. MgSO 4 (0, 0.75, 1.5, 3.0 mM), ZnSO 4 (0, 15, 30, 60 μM), CuSO 4 (0, 0.05, 0.1, 0.2 μM), NO 3 (20, 30, 40, 60 mM) and sucrose (1, 3, 5, 7 %, w/v) were taken as inputs for the ANN model. The designed model was evaluated by performing three different sets of validation experiments that indicated a greater similarity between the target and predicted dataset. The results of the modelling experiment suggested that 1.5 mM Mg, 30 μM Zn, 0.1 μM Cu, 40 mM NO 3 and 6 % (w/v) sucrose were the respective optimal concentrations of the tested medium components for achieving maximum growth index of 1654.46 with high centelloside yield (62.37 mg DW/culture) in the cultured multiple shoots. This study can facilitate the generation of higher biomass of uniform, clean, good quality C. asiatica herb that can efficiently be utilized by pharmaceutical industries.

Neural decoding of collective wisdom with multi-brain computing.

Science.gov (United States)

Eckstein, Miguel P; Das, Koel; Pham, Binh T; Peterson, Matthew F; Abbey, Craig K; Sy, Jocelyn L; Giesbrecht, Barry

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally

The Neural Correlates of Humor Creativity

OpenAIRE

Amir, Ori; Biederman, Irving

2016-01-01

Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur “improv” comedians and controls viewed New Yorker cartoon drawings while being ...

Rapid growth of single-layer graphene on the insulating substrates by thermal CVD

Energy Technology Data Exchange (ETDEWEB)

Chen, C.Y. [Faculty of Materials Science and Engineering, Kunming University of Science and Technology, Kunming 650093 (China); Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Dai, D.; Chen, G.X.; Yu, J.H. [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Nishimura, K. [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Advanced Nano-processing Engineering Lab, Mechanical Systems Engineering, Kogakuin University (Japan); Lin, C.-T. [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Jiang, N., E-mail: jiangnan@nimte.ac.cn [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Zhan, Z.L., E-mail: zl_zhan@sohu.com [Faculty of Materials Science and Engineering, Kunming University of Science and Technology, Kunming 650093 (China)

2015-08-15

Highlights: • A rapid thermal CVD process has been developed to directly grow graphene on the insulating substrates. • The treating time consumed is ≈25% compared to conventional CVD procedure. • Single-layer and few-layer graphene can be formed on quartz and SiO{sub 2}/Si substrates, respectively. • The formation of thinner graphene at the interface is due to the fast precipitation rate of carbon atoms during cooling. - Abstract: The advance of CVD technique to directly grow graphene on the insulating substrates is particularly significant for further device fabrication. As graphene is catalytically grown on metal foils, the degradation of the sample properties is unavoidable during transfer of graphene on the dielectric layer. Moreover, shortening the treatment time as possible, while achieving single-layer growth of graphene, is worthy to be investigated for promoting the efficiency of mass production. Here we performed a rapid heating/cooling process to grow graphene films directly on the insulating substrates by thermal CVD. The treating time consumed is ≈25% compared to conventional CVD procedure. In addition, we found that high-quality, single-layer graphene can be formed on quartz, but on SiO{sub 2}/Si substrate only few-layer graphene can be obtained. The pronounced substrate effect is attributed to the different dewetting behavior of Ni films on the both substrates at 950 °C.

Evidence of Rapid Modulation by Social Information of Subjective, Physiological, and Neural Responses to Emotional Expressions.

Science.gov (United States)

Mermillod, Martial; Grynberg, Delphine; Pio-Lopez, Léo; Rychlowska, Magdalena; Beffara, Brice; Harquel, Sylvain; Vermeulen, Nicolas; Niedenthal, Paula M; Dutheil, Frédéric; Droit-Volet, Sylvie

2017-01-01

Recent research suggests that conceptual or emotional factors could influence the perceptual processing of stimuli. In this article, we aimed to evaluate the effect of social information (positive, negative, or no information related to the character of the target) on subjective (perceived and felt valence and arousal), physiological (facial mimicry) as well as on neural (P100 and N170) responses to dynamic emotional facial expressions (EFE) that varied from neutral to one of the six basic emotions. Across three studies, the results showed reduced ratings of valence and arousal of EFE associated with incongruent social information (Study 1), increased electromyographical responses (Study 2), and significant modulation of P100 and N170 components (Study 3) when EFE were associated with social (positive and negative) information (vs. no information). These studies revealed that positive or negative social information reduces subjective responses to incongruent EFE and produces a similar neural and physiological boost of the early perceptual processing of EFE irrespective of their congruency. In conclusion, the article suggests that the presence of positive or negative social context modulates early physiological and neural activity preceding subsequent behavior.

Evidence of Rapid Modulation by Social Information of Subjective, Physiological, and Neural Responses to Emotional Expressions

Directory of Open Access Journals (Sweden)

Martial Mermillod

2018-01-01

Full Text Available Recent research suggests that conceptual or emotional factors could influence the perceptual processing of stimuli. In this article, we aimed to evaluate the effect of social information (positive, negative, or no information related to the character of the target on subjective (perceived and felt valence and arousal, physiological (facial mimicry as well as on neural (P100 and N170 responses to dynamic emotional facial expressions (EFE that varied from neutral to one of the six basic emotions. Across three studies, the results showed reduced ratings of valence and arousal of EFE associated with incongruent social information (Study 1, increased electromyographical responses (Study 2, and significant modulation of P100 and N170 components (Study 3 when EFE were associated with social (positive and negative information (vs. no information. These studies revealed that positive or negative social information reduces subjective responses to incongruent EFE and produces a similar neural and physiological boost of the early perceptual processing of EFE irrespective of their congruency. In conclusion, the article suggests that the presence of positive or negative social context modulates early physiological and neural activity preceding subsequent behavior.

Rapid growth in early childhood associated with young adult overweight and obesity--evidence from a community based cohort study.

Science.gov (United States)

Sutharsan, Ratneswary; O'Callaghan, Michael J; Williams, Gail; Najman, Jake M; Mamun, Abdullah A

2015-08-08

Rapid weight gain in early life may increase the risk of overweight and obesity in adulthood. We investigated the association between the rate of growth during early childhood and the development of overweight and obesity in young adults. We used a prospective cohort study of 2077 young adults who were born between 1981 and 1984 in Brisbane, Australia and had anthropometry measurements available at birth, 6 months, 5 years, 14 years and 21 years of age. The associations of rate of early growth with body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) and their categories at 21 years were studied using multivariate analysis. We found that rapid weight gain [> + 0.67 standard deviation score (SDS)] in the first 5 years of life was associated with young adults' overweight status (BMI: adjusted OR = 2.35, 95% CI, 1.82-3.03; WC: adjusted OR = 2.20, 95% CI, 1.65-2.95). We also observed that slow weight gain in the first 5 years of age (young adulthood, in contrast slow weight gain was inversely associated with weight status at 21 years.

Microfluidic engineered high cell density three-dimensional neural cultures

Science.gov (United States)

Cullen, D. Kacy; Vukasinovic, Jelena; Glezer, Ari; La Placa, Michelle C.

2007-06-01

Three-dimensional (3D) neural cultures with cells distributed throughout a thick, bioactive protein scaffold may better represent neurobiological phenomena than planar correlates lacking matrix support. Neural cells in vivo interact within a complex, multicellular environment with tightly coupled 3D cell-cell/cell-matrix interactions; however, thick 3D neural cultures at cell densities approaching that of brain rapidly decay, presumably due to diffusion limited interstitial mass transport. To address this issue, we have developed a novel perfusion platform that utilizes forced intercellular convection to enhance mass transport. First, we demonstrated that in thick (>500 µm) 3D neural cultures supported by passive diffusion, cell densities =104 cells mm-3), continuous medium perfusion at 2.0-11.0 µL min-1 improved viability compared to non-perfused cultures (p death and matrix degradation. In perfused cultures, survival was dependent on proximity to the perfusion source at 2.00-6.25 µL min-1 (p 90% viability in both neuronal cultures and neuronal-astrocytic co-cultures. This work demonstrates the utility of forced interstitial convection in improving the survival of high cell density 3D engineered neural constructs and may aid in the development of novel tissue-engineered systems reconstituting 3D cell-cell/cell-matrix interactions.

Rapid Population Growth-Cause or Result of Global Problems?

Science.gov (United States)

Schwartz, Richard H.

Explosive population growth is a symptom of the world's unjust and inequitable social, political, and economic conditions. The current rate of growth is staggering, particularly in the cities of the underdeveloped countries. While some progress has been made in slowing population growth, several factors still contribute to its momentum. One of…

Association of malignancy with rapid growth in early lesions induced by irradiation of rat skin

International Nuclear Information System (INIS)

McGregor, J.F.

1979-01-01

Epithelial lesions induced by irradiation of rat skin were studied to determine (a) the relationship of malignancy to dose, (b) the types of lesions and circumstances leading to overt malignancy, and (c) the growth rates of lesions progressing to malignancy versus those of lesions remaining benign. High doses of radiation were shown to be associated with the production of epidermal cancers, the maximum yield being obtained at 6,400 rads. Conversely, a peak yield of noncancerous lesions was obtained at 1,600 rads. This association between malignancy and high dose was consistent for cancers evolving from warts, cysts, and chronic ulcers. Although the proportion of warts among the induced lesions was much higher than that of the cysts or chronic ulcers (76, 14, and 10%, respectively), the likelihood of warts becoming cancerous was substantially lower (14, 23, and 21%). The combined data for all doses showed that the latency period of the epidermal cancers was significantly (P = 0.015) shorter than that of the benign tumors. Rapid growth rates were observed for warts, cysts, and chronic ulcers progressing to overt cancer, and these did not overlap at any point on the growth scale with rates for benign tumors. This finding suggested that the potential for malignant development had been established early in the carcinogenic process, very likely at induction

Determination of crystal growth rates during rapid solidification of polycrystalline aluminum by nano-scale spatio-temporal resolution in situ transmission electron microscopy

Energy Technology Data Exchange (ETDEWEB)

Zweiacker, K., E-mail: Kai@zweiacker.org; Liu, C.; Wiezorek, J. M. K. [Department of Mechanical Engineering and Materials Science, University of Pittsburgh, 648 Benedum Hall, 3700 OHara Street, Pittsburgh, Pennsylvania 15261 (United States); McKeown, J. T.; LaGrange, T.; Reed, B. W.; Campbell, G. H. [Materials Science Division, Physical and Life Science Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94551 (United States)

2016-08-07

In situ investigations of rapid solidification in polycrystalline Al thin films were conducted using nano-scale spatio-temporal resolution dynamic transmission electron microscopy. Differences in crystal growth rates and asymmetries in melt pool development were observed as the heat extraction geometry was varied by controlling the proximity of the laser-pulse irradiation and the associated induced melt pools to the edge of the transmission electron microscopy support grid, which acts as a large heat sink. Experimental parameters have been established to maximize the reproducibility of the material response to the laser-pulse-related heating and to ensure that observations of the dynamical behavior of the metal are free from artifacts, leading to accurate interpretations and quantifiable measurements with improved precision. Interface migration rate measurements revealed solidification velocities that increased consistently from ∼1.3 m s{sup −1} to ∼2.5 m s{sup −1} during the rapid solidification process of the Al thin films. Under the influence of an additional large heat sink, increased crystal growth rates as high as 3.3 m s{sup −1} have been measured. The in situ experiments also provided evidence for development of a partially melted, two-phase region prior to the onset of rapid solidification facilitated crystal growth. Using the experimental observations and associated measurements as benchmarks, finite-element modeling based calculations of the melt pool evolution after pulsed laser irradiation have been performed to obtain estimates of the temperature evolution in the thin films.

Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets

Science.gov (United States)

Moynihan, Philip; Steenburg, Robert Van; Chao, Tien-Hsin

2004-01-01

A proposed optoelectronic instrument would identify targets rapidly, without need to radiate an interrogating signal, apply identifying marks to the targets, or equip the targets with transponders. The instrument was conceived as an identification, friend or foe (IFF) system in a battlefield setting, where it would be part of a targeting system for weapons, by providing rapid identification for aimed weapons to help in deciding whether and when to trigger them. The instrument could also be adapted to law-enforcement and industrial applications in which it is necessary to rapidly identify objects in view. The instrument would comprise mainly an optical correlator and a neural processor (see figure). The inherent parallel-processing speed and capability of the optical correlator would be exploited to obtain rapid identification of a set of probable targets within a scene of interest and to define regions within the scene for the neural processor to analyze. The neural processor would then concentrate on each region selected by the optical correlator in an effort to identify the target. Depending on whether or not a target was recognized by comparison of its image data with data in an internal database on which the neural processor was trained, the processor would generate an identifying signal (typically, friend or foe ). The time taken for this identification process would be less than the time needed by a human or robotic gunner to acquire a view of, and aim at, a target. An optical correlator that has been under development for several years and that has been demonstrated to be capable of tracking a cruise missile might be considered a prototype of the optical correlator in the proposed IFF instrument. This optical correlator features a 512-by-512-pixel input image frame and operates at an input frame rate of 60 Hz. It includes a spatial light modulator (SLM) for video-to-optical image conversion, a pair of precise lenses to effect Fourier transforms, a filter SLM

Novel perspectives of neural stem cell differentiation: from neurotransmitters to therapeutics.

Science.gov (United States)

Trujillo, Cleber A; Schwindt, Telma T; Martins, Antonio H; Alves, Janaína M; Mello, Luiz Eugênio; Ulrich, Henning

2009-01-01

In the past years, many reports have described the existence of neural progenitor and stem cells in the adult central nervous system capable of generating new neurons, astrocytes, and oligodendrocytes. This discovery has overturned the central assumption in the neuroscience field, of no new neurons being originated in the brain after birth and provided the fundaments to understand the molecular basis of neural differentiation and to develop new therapies for neural tissue repair. Although the mechanisms underlying cell fate during neural development are not yet understood, the importance of intrinsic and extrinsic factors and of an appropriate microenvironment is well known. In this context, emerging evidence strongly suggests that glial cells play a key role in controlling multiple steps of neurogenesis. Those cells, of particular radial glia, are important for migration, cell specification, and integration of neurons into a functional neural network. This review aims to present an update in the neurogenesis area and highlight the modulation of neural stem cell differentiation by neurotransmitters, growth factors, and their receptors, with possible applications for cell therapy strategies of neurological disorders.

Artificial neural network-based predictive model for bacterial growth in a simulated medium of modified-atmosphere-packed cooked meat products.

Science.gov (United States)

Lou, W; Nakai, S

2001-04-01

The data of Devilieghere et al. (Int. J. Food Microbiol. 1999, 46, 57--70) on bacterial growth in a simulated medium of modified-atmosphere-packed cooked meat products was processed for estimating maximum specific growth rate mu(max) and lag phase lambda of Lactobacillus sake using artificial neural networks-based model (ANNM) computation. The comparison between ANNM and response surface methodology (RSM) model showed that the accuracy of ANNM prediction was higher than that of RSM. Two-dimensional and three-dimensional plots of the response surfaces revealed that the relationships of water activity a(w), temperature T, and dissolved CO(2) concentration with mu(max) and lambda were complicated, not just linear or second-order relations. Furthermore, it was possible to compute the sensitivity of the model outputs against each input parameter by using ANNM. The results showed that mu(max) was most sensitive to a(w), T, and dissolved CO(2) in this order; whereas lambda was sensitive to T the most, followed by a(w), and dissolved CO(2) concentrations.

An Improved Neural Network Training Algorithm for Wi-Fi Fingerprinting Positioning

Directory of Open Access Journals (Sweden)

Esmond Mok

2013-09-01

Full Text Available Ubiquitous positioning provides continuous positional information in both indoor and outdoor environments for a wide spectrum of location based service (LBS applications. With the rapid development of the low-cost and high speed data communication, Wi-Fi networks in many metropolitan cities, strength of signals propagated from the Wi-Fi access points (APs namely received signal strength (RSS have been cleverly adopted for indoor positioning. In this paper, a Wi-Fi positioning algorithm based on neural network modeling of Wi-Fi signal patterns is proposed. This algorithm is based on the correlation between the initial parameter setting for neural network training and output of the mean square error to obtain better modeling of the nonlinear highly complex Wi-Fi signal power propagation surface. The test results show that this neural network based data processing algorithm can significantly improve the neural network training surface to achieve the highest possible accuracy of the Wi-Fi fingerprinting positioning method.

State-of-the-art of applications of neural networks in the nuclear industry

International Nuclear Information System (INIS)

Zwingelstein, G.; Masson, M.H.

1990-01-01

Artificial neural net models have been extensively studied for many years in various laboratories to try to simulate with computer programs the human brain performances. The first applications were developed in the fields of speech and image recognition. The aims of these studies were mainly to classify rapidly patterns corrupted by noises or partly missing. Neural networks with the development of new net topologies and algorithms and parallel computing hardwares and softwares are to-day very promising for applications in many industries. In the introduction, this paper presents the anticipated benefits of the uses of neural networks for industrial applications. Then a brief overview of the main neural networks is provided. Finally a short review of neural networks applications in the nuclear industry is given. It covers domains such as: predictive maintenance for vibratory surveillance of rotating machinery, signal processing, operator guidance and eddy current inspection. In conclusion recommendations are made to use with efficiency neural networks for practical applications. In particular the need for supercomputing will be pinpointed. (author)

Prenatal bisphenol a urine concentrations and early rapid growth and overweight risk in the offspring.

Science.gov (United States)

Valvi, Damaskini; Casas, Maribel; Mendez, Michelle A; Ballesteros-Gómez, Ana; Luque, Noelia; Rubio, Soledad; Sunyer, Jordi; Vrijheid, Martine

2013-11-01

Increasing experimental evidence suggests that prenatal bisphenol A (BPA) exposure induces offspring weight gain, but these effects remain largely unexplored in humans. We examined the effects of prenatal BPA exposure on postnatal growth and obesity. BPA concentrations were measured in two spot-urine samples collected in the 1st and 3rd trimesters of pregnancy from mothers in a Spanish birth cohort study (n = 402). We used the average of the two creatinine-adjusted BPA concentrations as the exposure variable. Rapid child growth was defined as a weight gain Z score >0.67 in the first 6 months of life. Age- and sex-specific Z scores for body mass index (BMI) were calculated at age 14 months and 4 years, based on the World Health Organization referent; overweight was defined as a BMI Z score greater than or equal to the 85th percentile. Age- and sex-specific waist circumference Z scores were calculated at age 14 months and 4 years using the analysis population mean. Twenty-six percent of children were rapid growers; 25% were overweight at 14 months and 21% at 4 years. Geometric mean BPA concentrations were 2.6 μg/g creatinine (standard deviation = 2.3) in 1st trimester and 2.0 (2.3) in 3rd trimester samples (Pearson r = 0.13). At 4 years, BPA exposure was associated with increased waist circumference (β per log10 μg/g = 0.28 [95% confidence interval = 0.01 to 0.57]) and BMI (β = 0.28 [-0.06 to 0.63]). BPA was not associated with obesity-related outcomes at earlier ages. This study provides some evidence for an association between prenatal BPA exposure and obesity-related outcomes in childhood, although not in infancy. The large uncertainties in BPA exposure assessment require that findings be interpreted with caution.

Single-Trial Event-Related Potential Based Rapid Image Triage System

Directory of Open Access Journals (Sweden)

Ke Yu

2011-06-01

Full Text Available Searching for points of interest (POI in large-volume imagery is a challenging problem with few good solutions. In this work, a neural engineering approach called rapid image triage (RIT which could offer about a ten-fold speed up in POI searching is developed. It is essentially a cortically-coupled computer vision technique, whereby the user is presented bursts of images at a speed of 6–15 images per second and then neural signals called event-related potential (ERP is used as the ‘cue’ for user seeing images of high relevance likelihood. Compared to past efforts, the implemented system has several unique features: (1 it applies overlapping frames in image chip preparation, to ensure rapid image triage performance; (2 a novel common spatial-temporal pattern (CSTP algorithm that makes use of both spatial and temporal patterns of ERP topography is proposed for high-accuracy single-trial ERP detection; (3 a weighted version of probabilistic support-vector-machine (SVM is used to address the inherent unbalanced nature of single-trial ERP detection for RIT. High accuracy, fast learning, and real-time capability of the developed system shown on 20 subjects demonstrate the feasibility of a brainmachine integrated rapid image triage system for fast detection of POI from large-volume imagery.

Forecasting PM10 in metropolitan areas: Efficacy of neural networks

International Nuclear Information System (INIS)

Fernando, H.J.S.; Mammarella, M.C.; Grandoni, G.; Fedele, P.; Di Marco, R.; Dimitrova, R.; Hyde, P.

2012-01-01

Deterministic photochemical air quality models are commonly used for regulatory management and planning of urban airsheds. These models are complex, computer intensive, and hence are prohibitively expensive for routine air quality predictions. Stochastic methods are becoming increasingly popular as an alternative, which relegate decision making to artificial intelligence based on Neural Networks that are made of artificial neurons or ‘nodes’ capable of ‘learning through training’ via historic data. A Neural Network was used to predict particulate matter concentration at a regulatory monitoring site in Phoenix, Arizona; its development, efficacy as a predictive tool and performance vis-à-vis a commonly used regulatory photochemical model are described in this paper. It is concluded that Neural Networks are much easier, quicker and economical to implement without compromising the accuracy of predictions. Neural Networks can be used to develop rapid air quality warning systems based on a network of automated monitoring stations.Highlights: ► Neural Network is an alternative technique to photochemical modelling. ► Neutral Networks can be as effective as traditional air photochemical modelling. ► Neural Networks are much easier and quicker to implement in health warning system. - Neutral networks are as effective as photochemical modelling for air quality predictions, but are much easier, quicker and economical to implement in air pollution (or health) warning systems.

DCS-Neural-Network Program for Aircraft Control and Testing

Science.gov (United States)

Jorgensen, Charles C.

2006-01-01

A computer program implements a dynamic-cell-structure (DCS) artificial neural network that can perform such tasks as learning selected aerodynamic characteristics of an airplane from wind-tunnel test data and computing real-time stability and control derivatives of the airplane for use in feedback linearized control. A DCS neural network is one of several types of neural networks that can incorporate additional nodes in order to rapidly learn increasingly complex relationships between inputs and outputs. In the DCS neural network implemented by the present program, the insertion of nodes is based on accumulated error. A competitive Hebbian learning rule (a supervised-learning rule in which connection weights are adjusted to minimize differences between actual and desired outputs for training examples) is used. A Kohonen-style learning rule (derived from a relatively simple training algorithm, implements a Delaunay triangulation layout of neurons) is used to adjust node positions during training. Neighborhood topology determines which nodes are used to estimate new values. The network learns, starting with two nodes, and adds new nodes sequentially in locations chosen to maximize reductions in global error. At any given time during learning, the error becomes homogeneously distributed over all nodes.

(GAGs) in normal and ethanol-induced chick embryo during neural

African Journals Online (AJOL)

Administrator

2011-09-14

Sep 14, 2011 ... Alcohol as a teratogenic agent inhibits cell growth, function, proliferation and migration by affecting .... formed along the right and left side of the neural tube .... of neurons by harming the developing brain and also can.

A comparative study of multilayer perceptron neural networks for the identification of rhubarb samples.

Science.gov (United States)

Zhang, Zhuoyong; Wang, Yamin; Fan, Guoqiang; Harrington, Peter de B

2007-01-01

Artificial neural networks have gained much attention in recent years as fast and flexible methods for quality control in traditional medicine. Near-infrared (NIR) spectroscopy has become an accepted method for the qualitative and quantitative analyses of traditional Chinese medicine since it is simple, rapid, and non-destructive. The present paper describes a method by which to discriminate official and unofficial rhubarb samples using three layer perceptron neural networks applied to NIR data. Multilayer perceptron neural networks were trained with back propagation, delta-bar-delta and quick propagation algorithms. Results obtained using these methods were all satisfactory, but the best outcomes were obtained with the delta-bar-delta algorithm.

Attenuating the alcohol allure: attentional broadening reduces rapid motivational response to alcohol pictures.

Science.gov (United States)

Ryerson, Nicole C; Neal, Lauren B; Gable, Philip A

2017-04-01

Past research has found that exposure to alcohol cues causes a narrowing of attentional scope and enhances the neural responses associated with approach motivation. The current research sought to determine if a manipulated broadened (global) attentional scope would reduce approach-motivated neural reactivity to alcohol pictures. In the current study, participants (n = 82) were exposed to alcohol and neutral pictures following either a global or local attentional scope manipulation. Early motivated attentional processing was assessed using the N1 event-related potential (ERP), a neurophysiological marker of rapid motivated attention. A global attentional scope reduced N1 amplitudes to alcohol pictures as compared to a local attentional scope. Self-reported binge drinking related to larger N1 amplitudes to alcohol pictures, but not to neutral pictures. Individuals with greater binge drinking experience demonstrated increased rapid motivated attentional processing to alcohol pictures. These results suggest that enhancing a global (vs. local) attentional scope attenuates rapid motivated attentional processing of alcohol pictures in comparison to neutral pictures. Graphical abstract ᅟ.

Hybrid Thin Film Organosilica Sol-Gel Coatings To Support Neuronal Growth and Limit Astrocyte Growth.

Science.gov (United States)

Capeletti, Larissa Brentano; Cardoso, Mateus Borba; Dos Santos, João Henrique Zimnoch; He, Wei

2016-10-07

Thin films of silica prepared by a sol-gel process are becoming a feasible coating option for surface modification of implantable neural sensors without imposing adverse effects on the devices' electrical properties. In order to advance the application of such silica-based coatings in the context of neural interfacing, the characteristics of silica sol-gel are further tailored to gain active control of interactions between cells and the coating materials. By incorporating various readily available organotrialkoxysilanes carrying distinct organic functional groups during the sol-gel process, a library of hybrid organosilica coatings is developed and investigated. In vitro neural cultures using PC12 cells and primary cortical neurons both reveal that, among these different types of hybrid organosilica, the introduction of aminopropyl groups drastically transforms the silica into robust neural permissive substrate, supporting neuron adhesion and neurite outgrowth. Moreover, when this organosilica is cultured with astrocytes, a key type of glial cells responsible for glial scar response toward neural implants, such cell growth promoting effect is not observed. These findings highlight the potential of organo-group-bearing silica sol-gel to function as advanced coating materials to selectively modulate cell response and promote neural integration with implantable sensing devices.

The Neural Foundations of Reaction and Action in Aversive Motivation.

Science.gov (United States)

Campese, Vincent D; Sears, Robert M; Moscarello, Justin M; Diaz-Mataix, Lorenzo; Cain, Christopher K; LeDoux, Joseph E

2016-01-01

Much of the early research in aversive learning concerned motivation and reinforcement in avoidance conditioning and related paradigms. When the field transitioned toward the focus on Pavlovian threat conditioning in isolation, this paved the way for the clear understanding of the psychological principles and neural and molecular mechanisms responsible for this type of learning and memory that has unfolded over recent decades. Currently, avoidance conditioning is being revisited, and with what has been learned about associative aversive learning, rapid progress is being made. We review, below, the literature on the neural substrates critical for learning in instrumental active avoidance tasks and conditioned aversive motivation.

Automatic gain control of neural coupling during cooperative hand movements.

Science.gov (United States)

Thomas, F A; Dietz, V; Schrafl-Altermatt, M

2018-04-13

Cooperative hand movements (e.g. opening a bottle) are controlled by a task-specific neural coupling, reflected in EMG reflex responses contralateral to the stimulation site. In this study the contralateral reflex responses in forearm extensor muscles to ipsilateral ulnar nerve stimulation was analyzed at various resistance and velocities of cooperative hand movements. The size of contralateral reflex responses was closely related to the level of forearm muscle activation required to accomplish the various cooperative hand movement tasks. This indicates an automatic gain control of neural coupling that allows a rapid matching of corrective forces exerted at both sides of an object with the goal 'two hands one action'.

Neural networks and their potential application to nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.

1991-01-01

A network of artificial neurons, usually called an artificial neural network is a data processing system consisting of a number of highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks exhibit characteristics and capabilities not provided by any other technology. Neural networks may be designed so as to classify an input pattern as one of several predefined types or to create, as needed, categories or classes of system states which can be interpreted by a human operator. Neural networks have the ability to recognize patterns, even when the information comprising these patterns is noisy, sparse, or incomplete. Thus, systems of artificial neural networks show great promise for use in environments in which robust, fault-tolerant pattern recognition is necessary in a real-time mode, and in which the incoming data may be distorted or noisy. The application of neural networks, a rapidly evolving technology used extensively in defense applications, alone or in conjunction with other advanced technologies, to some of the problems of operating nuclear power plants has the potential to enhance the safety, reliability and operability of nuclear power plants. The potential applications of neural networking include, but are not limited to diagnosing specific abnormal conditions, identification of nonlinear dynamics and transients, detection of the change of mode of operation, control of temperature and pressure during start-up, signal validation, plant-wide monitoring using autoassociative neural networks, monitoring of check valves, modeling of the plant thermodynamics, emulation of core reload calculations, analysis of temporal sequences in NRC's ''licensee event reports,'' and monitoring of plant parameters

Gelatin methacrylamide hydrogel with graphene nanoplatelets for neural cell-laden 3D bioprinting.

Science.gov (United States)

Wei Zhu; Harris, Brent T; Zhang, Lijie Grace

2016-08-01

Nervous system is extremely complex which leads to rare regrowth of nerves once injury or disease occurs. Advanced 3D bioprinting strategy, which could simultaneously deposit biocompatible materials, cells and supporting components in a layer-by-layer manner, may be a promising solution to address neural damages. Here we presented a printable nano-bioink composed of gelatin methacrylamide (GelMA), neural stem cells, and bioactive graphene nanoplatelets to target nerve tissue regeneration in the assist of stereolithography based 3D bioprinting technique. We found the resultant GelMA hydrogel has a higher compressive modulus with an increase of GelMA concentration. The porous GelMA hydrogel can provide a biocompatible microenvironment for the survival and growth of neural stem cells. The cells encapsulated in the hydrogel presented good cell viability at the low GelMA concentration. Printed neural construct exhibited well-defined architecture and homogenous cell distribution. In addition, neural stem cells showed neuron differentiation and neurites elongation within the printed construct after two weeks of culture. These findings indicate the 3D bioprinted neural construct has great potential for neural tissue regeneration.

Neural Correlates of Word Recognition: A Systematic Comparison of Natural Reading and Rapid Serial Visual Presentation.

Science.gov (United States)

Kornrumpf, Benthe; Niefind, Florian; Sommer, Werner; Dimigen, Olaf

2016-09-01

Neural correlates of word recognition are commonly studied with (rapid) serial visual presentation (RSVP), a condition that eliminates three fundamental properties of natural reading: parafoveal preprocessing, saccade execution, and the fast changes in attentional processing load occurring from fixation to fixation. We combined eye-tracking and EEG to systematically investigate the impact of all three factors on brain-electric activity during reading. Participants read lists of words either actively with eye movements (eliciting fixation-related potentials) or maintained fixation while the text moved passively through foveal vision at a matched pace (RSVP-with-flankers paradigm, eliciting ERPs). The preview of the upcoming word was manipulated by changing the number of parafoveally visible letters. Processing load was varied by presenting words of varying lexical frequency. We found that all three factors have strong interactive effects on the brain's responses to words: Once a word was fixated, occipitotemporal N1 amplitude decreased monotonically with the amount of parafoveal information available during the preceding fixation; hence, the N1 component was markedly attenuated under reading conditions with preview. Importantly, this preview effect was substantially larger during active reading (with saccades) than during passive RSVP with flankers, suggesting that the execution of eye movements facilitates word recognition by increasing parafoveal preprocessing. Lastly, we found that the N1 component elicited by a word also reflects the lexical processing load imposed by the previously inspected word. Together, these results demonstrate that, under more natural conditions, words are recognized in a spatiotemporally distributed and interdependent manner across multiple eye fixations, a process that is mediated by active motor behavior.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

Science.gov (United States)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

Neural network feedforward control of a closed-circuit wind tunnel

Science.gov (United States)

Sutcliffe, Peter

Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the

Zika virus infection dysregulates human neural stem cell growth and inhibits differentiation into neuroprogenitor cells.

Science.gov (United States)

Devhare, Pradip; Meyer, Keith; Steele, Robert; Ray, Ratna B; Ray, Ranjit

2017-10-12

The current outbreak of Zika virus-associated diseases in South America and its threat to spread to other parts of the world has emerged as a global health emergency. A strong link between Zika virus and microcephaly exists, and the potential mechanisms associated with microcephaly are under intense investigation. In this study, we evaluated the effect of Zika virus infection of Asian and African lineages (PRVABC59 and MR766) in human neural stem cells (hNSCs). These two Zika virus strains displayed distinct infection pattern and growth rates in hNSCs. Zika virus MR766 strain increased serine 139 phosphorylation of histone H2AX (γH2AX), a known early cellular response proteins to DNA damage. On the other hand, PRVABC59 strain upregulated serine 15 phosphorylation of p53, p21 and PUMA expression. MR766-infected cells displayed poly (ADP-ribose) polymerase (PARP) and caspase-3 cleavage. Interestingly, infection of hNSCs by both strains of Zika virus for 24 h, followed by incubation in astrocyte differentiation medium, induced rounding and cell death. However, astrocytes generated from hNSCs by incubation in differentiation medium when infected with Zika virus displayed minimal cytopathic effect at an early time point. Infected hNSCs incubated in astrocyte differentiating medium displayed PARP cleavage within 24-36 h. Together, these results showed that two distinct strains of Zika virus potentiate hNSC growth inhibition by different mechanisms, but both viruses strongly induce death in early differentiating neuroprogenitor cells even at a very low multiplicity of infection. Our observations demonstrate further mechanistic insights for impaired neuronal homeostasis during active Zika virus infection.

Zika virus infection dysregulates human neural stem cell growth and inhibits differentiation into neuroprogenitor cells

Science.gov (United States)

Devhare, Pradip; Meyer, Keith; Steele, Robert; Ray, Ratna B; Ray, Ranjit

2017-01-01

The current outbreak of Zika virus-associated diseases in South America and its threat to spread to other parts of the world has emerged as a global health emergency. A strong link between Zika virus and microcephaly exists, and the potential mechanisms associated with microcephaly are under intense investigation. In this study, we evaluated the effect of Zika virus infection of Asian and African lineages (PRVABC59 and MR766) in human neural stem cells (hNSCs). These two Zika virus strains displayed distinct infection pattern and growth rates in hNSCs. Zika virus MR766 strain increased serine 139 phosphorylation of histone H2AX (γH2AX), a known early cellular response proteins to DNA damage. On the other hand, PRVABC59 strain upregulated serine 15 phosphorylation of p53, p21 and PUMA expression. MR766-infected cells displayed poly (ADP-ribose) polymerase (PARP) and caspase-3 cleavage. Interestingly, infection of hNSCs by both strains of Zika virus for 24 h, followed by incubation in astrocyte differentiation medium, induced rounding and cell death. However, astrocytes generated from hNSCs by incubation in differentiation medium when infected with Zika virus displayed minimal cytopathic effect at an early time point. Infected hNSCs incubated in astrocyte differentiating medium displayed PARP cleavage within 24–36 h. Together, these results showed that two distinct strains of Zika virus potentiate hNSC growth inhibition by different mechanisms, but both viruses strongly induce death in early differentiating neuroprogenitor cells even at a very low multiplicity of infection. Our observations demonstrate further mechanistic insights for impaired neuronal homeostasis during active Zika virus infection. PMID:29022904

Genetic deletion of Rnd3 in neural stem cells promotes proliferation via upregulation of Notch signaling.

Science.gov (United States)

Dong, Huimin; Lin, Xi; Li, Yuntao; Hu, Ronghua; Xu, Yang; Guo, Xiaojie; La, Qiong; Wang, Shun; Fang, Congcong; Guo, Junli; Li, Qi; Mao, Shanping; Liu, Baohui

2017-10-31

Rnd3, a Rho GTPase, is involved in the inhibition of actin cytoskeleton dynamics through the Rho kinase-dependent signaling pathway. We previously demonstrated that mice with genetic deletion of Rnd3 developed a markedly larger brain compared with wild-type mice. Here, we demonstrate that Rnd3 knockout mice developed an enlarged subventricular zone, and we identify a novel role for Rnd3 as an inhibitor of Notch signaling in neural stem cells. Rnd3 deficiency, both in vivo and in vitro , resulted in increased levels of Notch intracellular domain protein. This led to enhanced Notch signaling and promotion of aberrant neural stem cell growth, thereby resulting in a larger subventricular zone and a markedly larger brain. Inhibition of Notch activity abrogated this aberrant neural stem cell growth.

Rapid regulation of leaf photosynthesis, carbohydrate status and leaf area expansion to maintain growth in irregular light environments

DEFF Research Database (Denmark)

Kjær, Katrine Heinsvig

2012-01-01

to maintain carbohydrate status and growth in unpredictable light environments. Our recent results show rapid regulation of photosynthesis and leaf carbohydrate status to maintain growth and light interception in dynamic light environments when campanula, rose and chrysanthemum were grown in a cost......-efficient light control system. Plant dry matter production was in all cases linear related to DLI, despite changes in daily light duration and light intensity of supplemental light suggesting that DLI is the main limiting factor for the prediction of production time in optimal temperature conditions. The results......Protected plant productions in northern latitudes rely heavily on supplemental light use to extend the number of light hours during the day. To conserve electricity and lower costs, a low-energy input system use supplemental lights preferable during less expensive off-peak hours and turn lighting...

The positional identity of iPSC-derived neural progenitor cells along the anterior-posterior axis is controlled in a dosage-dependent manner by bFGF and EGF

DEFF Research Database (Denmark)

Zhou, Shuling; Ochalek, Anna; Szczesna, Karolina

2016-01-01

Neural rosettes derived from human induced pluripotent stem cells (iPSCs) have been claimed to be a highly robust in vitro cellular model for biomedical application. They are able to propagate in vitro in the presence of mitogens, including basic fibroblast growth factor (bFGF) and epidermal growth...... factor (EGF). However, these two mitogens are also involved in anterior-posterior patterning in a gradient dependent manner along the neural tube axis. Here, we compared the regional identity of neural rosette cells and specific neural subtypes of their progeny propagated with low and high concentrations...... of the neural rosettes, resulting in subsequent cholinergic neuron differentiation. Thus, our results indicate that different concentrations of bFGF and EGF supplemented during propagation of neural rosettes are involved in altering the identity of the resultant neural cells....

IGF-II Promotes Stemness of Neural Restricted Precursors

Science.gov (United States)

Ziegler, Amber N.; Schneider, Joel S.; Qin, Mei; Tyler, William A.; Pintar, John E.; Fraidenraich, Diego; Wood, Teresa L.; Levison, Steven W.

2016-01-01

Insulin-like growth factor (IGF)-I and IGF-II regulate brain development and growth through the IGF type 1 receptor (IGF-1R). Less appreciated is that IGF-II, but not IGF-I, activates a splice variant of the insulin receptor (IR) known as IR-A. We hypothesized that IGF-II exerts distinct effects from IGF-I on neural stem/progenitor cells (NSPs) via its interaction with IR-A. Immunofluorescence revealed high IGF-II in the medial region of the subventricular zone (SVZ) comprising the neural stem cell niche, with IGF-II mRNA predominant in the adjacent choroid plexus. The IGF-1R and the IR isoforms were differentially expressed with IR-A predominant in the medial SVZ, whereas the IGF-1R was more abundant laterally. Similarly, IR-A was more highly expressed by NSPs, whereas the IGF-1R was more highly expressed by lineage restricted cells. In vitro, IGF-II was more potent in promoting NSP expansion than either IGF-I or standard growth medium. Limiting dilution and differentiation assays revealed that IGF-II was superior to IGF-I in promoting stemness. In vivo, NSPs propagated in IGF-II migrated to and took up residence in periventricular niches while IGF-I-treated NSPs predominantly colonized white matter. Knockdown of IR or IGF-1R using shRNAs supported the conclusion that the IGF-1R promotes progenitor proliferation, whereas the IR is important for self-renewal. Q-PCR revealed that IGF-II increased Oct4, Sox1, and FABP7 mRNA levels in NSPs. Our data support the conclusion that IGF-II promotes the self-renewal of neural stem/progenitors via the IR. By contrast, IGF-1R functions as a mitogenic receptor to increase precursor abundance. PMID:22593020

Rapid growth of amorphous carbon films on the inner surface of micron-thick and hollow-core fibers

Energy Technology Data Exchange (ETDEWEB)

Ji, Longfei [Fujian Key Laboratory for Plasma and Magnetic Resonance, Department of Electric Science, School of Physics and Mechanical and Electrical Engineering, Xiamen University, Xiamen, Fujian 361005 (China); School of Physics and Materials Engineering, Dalian Nationalities University, Dalian 116600 (China); School of Science, Changchun University of Science and Technology, Changchun, Jilin 130022 (China); Liu, Dongping, E-mail: Dongping.liu@dlnu.edu.cn [Fujian Key Laboratory for Plasma and Magnetic Resonance, Department of Electric Science, School of Physics and Mechanical and Electrical Engineering, Xiamen University, Xiamen, Fujian 361005 (China); School of Physics and Materials Engineering, Dalian Nationalities University, Dalian 116600 (China); School of Science, Changchun University of Science and Technology, Changchun, Jilin 130022 (China); Zhou, Xinwei [Department of Mechanical Engineering, Zhejiang University, Zhejiang 310007 (China); Song, Ying [School of Physics and Materials Engineering, Dalian Nationalities University, Dalian 116600 (China); School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116023 (China); Ni, Weiyuan [School of Physics and Materials Engineering, Dalian Nationalities University, Dalian 116600 (China); School of Science, Changchun University of Science and Technology, Changchun, Jilin 130022 (China); Niu, Jinhai; Fan, Hongyu [School of Physics and Materials Engineering, Dalian Nationalities University, Dalian 116600 (China)

2013-10-01

Ultrathick (> 25 μm) carbon films were obtained on the inner surface of hollow and micron-thick quartz fibers by confining CH{sub 4}/He or C{sub 2}H{sub 2}/He microplasmas in their hollow cores. The resulting carbon films were studied by using scanning electron microscopy and energy-dispersive X-ray spectroscopy. The microplasma-enhanced chemical vapor deposition (CVD) technique resulted in the uniform growth of amorphous carbon films on the inner surface of very long (> 1 m) hollow-core fibers. Film deposition is performed by using microplasmas at atmospheric pressure and at 50 Pa. The carbon films obtained with the latter show the smooth inner surfaces and the well continuity across the film/optical fiber. Low-pressure CH{sub 4}/He and C{sub 2}H{sub 2}/He microplasmas can lead to a rapid growth (∼ 2.00 μm/min) of carbon films with their thickness of > 25 μm. The optical emission measurements show that various hydrocarbon species were formed in these depositing microplasmas due to the collisions between CH{sub 4}/C{sub 2}H{sub 2} molecules and energetic species. The microplasma-enhanced CVD technique running without the complicated fabrication processes shows its potentials for rapidly depositing the overlong carbon tubes with their inner diameters of tens of microns. - Highlights: • The microplasma device is applied for coating deposition inside hollow-core fibers. • The microplasma device results in > 25 μm-thick carbon films. • The microplasma device is simple for deposition of ultralong carbon tubes.

Neural cell adhesion molecule-180-mediated homophilic binding induces epidermal growth factor receptor (EGFR) down-regulation and uncouples the inhibitory function of EGFR in neurite outgrowth

DEFF Research Database (Denmark)

Povlsen, Gro Klitgaard; Berezin, Vladimir; Bock, Elisabeth

2008-01-01

The neural cell adhesion molecule (NCAM) plays important roles in neuronal development, regeneration, and synaptic plasticity. NCAM homophilic binding mediates cell adhesion and induces intracellular signals, in which the fibroblast growth factor receptor plays a prominent role. Recent studies...... this NCAM-180-induced EGFR down-regulation involves increased EGFR ubiquitination and lysosomal EGFR degradation. Furthermore, NCAM-180-mediated EGFR down-regulation requires NCAM homophilic binding and interactions of the cytoplasmic domain of NCAM-180 with intracellular interaction partners, but does...

Emulation of Neural Networks on a Nanoscale Architecture

International Nuclear Information System (INIS)

Eshaghian-Wilner, Mary M; Friesz, Aaron; Khitun, Alex; Navab, Shiva; Parker, Alice C; Wang, Kang L; Zhou, Chongwu

2007-01-01

In this paper, we propose using a nanoscale spin-wave-based architecture for implementing neural networks. We show that this architecture can efficiently realize highly interconnected neural network models such as the Hopfield model. In our proposed architecture, no point-to-point interconnection is required, so unlike standard VLSI design, no fan-in/fan-out constraint limits the interconnectivity. Using spin-waves, each neuron could broadcast to all other neurons simultaneously and similarly a neuron could concurrently receive and process multiple data. Therefore in this architecture, the total weighted sum to each neuron can be computed by the sum of the values from all the incoming waves to that neuron. In addition, using the superposition property of waves, this computation can be done in O(1) time, and neurons can update their states quite rapidly

A Rapid Subcortical Amygdala Route for Faces Irrespective of Spatial Frequency and Emotion.

Science.gov (United States)

McFadyen, Jessica; Mermillod, Martial; Mattingley, Jason B; Halász, Veronika; Garrido, Marta I

2017-04-05

There is significant controversy over the existence and function of a direct subcortical visual pathway to the amygdala. It is thought that this pathway rapidly transmits low spatial frequency information to the amygdala independently of the cortex, and yet the directionality of this function has never been determined. We used magnetoencephalography to measure neural activity while human participants discriminated the gender of neutral and fearful faces filtered for low or high spatial frequencies. We applied dynamic causal modeling to demonstrate that the most likely underlying neural network consisted of a pulvinar-amygdala connection that was uninfluenced by spatial frequency or emotion, and a cortical-amygdala connection that conveyed high spatial frequencies. Crucially, data-driven neural simulations revealed a clear temporal advantage of the subcortical connection over the cortical connection in influencing amygdala activity. Thus, our findings support the existence of a rapid subcortical pathway that is nonselective in terms of the spatial frequency or emotional content of faces. We propose that that the "coarseness" of the subcortical route may be better reframed as "generalized." SIGNIFICANCE STATEMENT The human amygdala coordinates how we respond to biologically relevant stimuli, such as threat or reward. It has been postulated that the amygdala first receives visual input via a rapid subcortical route that conveys "coarse" information, namely, low spatial frequencies. For the first time, the present paper provides direction-specific evidence from computational modeling that the subcortical route plays a generalized role in visual processing by rapidly transmitting raw, unfiltered information directly to the amygdala. This calls into question a widely held assumption across human and animal research that fear responses are produced faster by low spatial frequencies. Our proposed mechanism suggests organisms quickly generate fear responses to a wide range

Placental determinants of fetal growth: identification of key factors in the insulin-like growth factor and cytokine systems using artificial neural networks

Directory of Open Access Journals (Sweden)

Faleschini Elena

2008-06-01

Full Text Available Abstract Background Changes and relationships of components of the cytokine and IGF systems have been shown in placenta and cord serum of fetal growth restricted (FGR compared with normal newborns (AGA. This study aimed to analyse a data set of clinical and biochemical data in FGR and AGA newborns to assess if a mathematical model existed and was capable of identifying these two different conditions in order to identify the variables which had a mathematically consistent biological relevance to fetal growth. Methods Whole villous tissue was collected at birth from FGR (N = 20 and AGA neonates (N = 28. Total RNA was extracted, reverse transcribed and then real-time quantitative (TaqMan RT-PCR was performed to quantify cDNA for IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IL-6. The corresponding proteins with TNF-α in addition were assayed in placental lysates using specific kits. The data were analysed using Artificial Neural Networks (supervised networks, and principal component analysis and connectivity map. Results The IGF system and IL-6 allowed to predict FGR in approximately 92% of the cases and AGA in 85% of the cases with a low number of errors. IGF-II, IGFBP-2, and IL-6 content in the placental lysates were the most important factors connected with FGR. The condition of being FGR was connected mainly with the IGF-II placental content, and the latter with IL-6 and IGFBP-2 concentrations in placental lysates. Conclusion These results suggest that further research in humans should focus on these biochemical data. Furthermore, this study offered a critical revision of previous studies. The understanding of this system biology is relevant to the development of future therapeutical interventions possibly aiming at reducing IL-6 and IGFBP-2 concentrations preserving IGF bioactivity in both placenta and fetus.

Characterization of TLX expression in neural stem cells and progenitor cells in adult brains.

Science.gov (United States)

Li, Shengxiu; Sun, Guoqiang; Murai, Kiyohito; Ye, Peng; Shi, Yanhong

2012-01-01

TLX has been shown to play an important role in regulating the self-renewal and proliferation of neural stem cells in adult brains. However, the cellular distribution of endogenous TLX protein in adult brains remains to be elucidated. In this study, we used immunostaining with a TLX-specific antibody to show that TLX is expressed in both neural stem cells and transit-amplifying neural progenitor cells in the subventricular zone (SVZ) of adult mouse brains. Then, using a double thymidine analog labeling approach, we showed that almost all of the self-renewing neural stem cells expressed TLX. Interestingly, most of the TLX-positive cells in the SVZ represented the thymidine analog-negative, relatively quiescent neural stem cell population. Using cell type markers and short-term BrdU labeling, we demonstrated that TLX was also expressed in the Mash1+ rapidly dividing type C cells. Furthermore, loss of TLX expression dramatically reduced BrdU label-retaining neural stem cells and the actively dividing neural progenitor cells in the SVZ, but substantially increased GFAP staining and extended GFAP processes. These results suggest that TLX is essential to maintain the self-renewing neural stem cells in the SVZ and that the GFAP+ cells in the SVZ lose neural stem cell property upon loss of TLX expression. Understanding the cellular distribution of TLX and its function in specific cell types may provide insights into the development of therapeutic tools for neurodegenerative diseases by targeting TLX in neural stem/progenitors cells.

Neural plasticity underlying visual perceptual learning in aging.

Science.gov (United States)

Mishra, Jyoti; Rolle, Camarin; Gazzaley, Adam

2015-07-01

Healthy aging is associated with a decline in basic perceptual abilities, as well as higher-level cognitive functions such as working memory. In a recent perceptual training study using moving sweeps of Gabor stimuli, Berry et al. (2010) observed that older adults significantly improved discrimination abilities on the most challenging perceptual tasks that presented paired sweeps at rapid rates of 5 and 10 Hz. Berry et al. further showed that this perceptual training engendered transfer-of-benefit to an untrained working memory task. Here, we investigated the neural underpinnings of the improvements in these perceptual tasks, as assessed by event-related potential (ERP) recordings. Early visual ERP components time-locked to stimulus onset were compared pre- and post-training, as well as relative to a no-contact control group. The visual N1 and N2 components were significantly enhanced after training, and the N1 change correlated with improvements in perceptual discrimination on the task. Further, the change observed for the N1 and N2 was associated with the rapidity of the perceptual challenge; the visual N1 (120-150 ms) was enhanced post-training for 10 Hz sweep pairs, while the N2 (240-280 ms) was enhanced for the 5 Hz sweep pairs. We speculate that these observed post-training neural enhancements reflect improvements by older adults in the allocation of attention that is required to accurately dissociate perceptually overlapping stimuli when presented in rapid sequence. This article is part of a Special Issue entitled SI: Memory Å. Copyright © 2014 Elsevier B.V. All rights reserved.

A model of interval timing by neural integration.

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Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

Orphan nuclear receptor TLX activates Wnt/β-catenin signalling to stimulate neural stem cell proliferation and self-renewal

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Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T.; Gage, Fred H.; Evans, Ronald M.; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/β-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/β-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active β-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a β-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active β-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active β-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active β-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/β-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode. PMID:20010817

Orphan nuclear receptor TLX activates Wnt/beta-catenin signalling to stimulate neural stem cell proliferation and self-renewal.

Science.gov (United States)

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T; Gage, Fred H; Evans, Ronald M; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/beta-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/beta-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active beta-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a beta-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active beta-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active beta-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active beta-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/beta-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode.

Typology of nonlinear activity waves in a layered neural continuum.

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Koch, Paul; Leisman, Gerry

2006-04-01

Neural tissue, a medium containing electro-chemical energy, can amplify small increments in cellular activity. The growing disturbance, measured as the fraction of active cells, manifests as propagating waves. In a layered geometry with a time delay in synaptic signals between the layers, the delay is instrumental in determining the amplified wavelengths. The growth of the waves is limited by the finite number of neural cells in a given region of the continuum. As wave growth saturates, the resulting activity patterns in space and time show a variety of forms, ranging from regular monochromatic waves to highly irregular mixtures of different spatial frequencies. The type of wave configuration is determined by a number of parameters, including alertness and synaptic conditioning as well as delay. For all cases studied, using numerical solution of the nonlinear Wilson-Cowan (1973) equations, there is an interval in delay in which the wave mixing occurs. As delay increases through this interval, during a series of consecutive waves propagating through a continuum region, the activity within that region changes from a single-frequency to a multiple-frequency pattern and back again. The diverse spatio-temporal patterns give a more concrete form to several metaphors advanced over the years to attempt an explanation of cognitive phenomena: Activity waves embody the "holographic memory" (Pribram, 1991); wave mixing provides a plausible cause of the competition called "neural Darwinism" (Edelman, 1988); finally the consecutive generation of growing neural waves can explain the discontinuousness of "psychological time" (Stroud, 1955).

Vein matching using artificial neural network in vein authentication systems

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Noori Hoshyar, Azadeh; Sulaiman, Riza

2011-10-01

Personal identification technology as security systems is developing rapidly. Traditional authentication modes like key; password; card are not safe enough because they could be stolen or easily forgotten. Biometric as developed technology has been applied to a wide range of systems. According to different researchers, vein biometric is a good candidate among other biometric traits such as fingerprint, hand geometry, voice, DNA and etc for authentication systems. Vein authentication systems can be designed by different methodologies. All the methodologies consist of matching stage which is too important for final verification of the system. Neural Network is an effective methodology for matching and recognizing individuals in authentication systems. Therefore, this paper explains and implements the Neural Network methodology for finger vein authentication system. Neural Network is trained in Matlab to match the vein features of authentication system. The Network simulation shows the quality of matching as 95% which is a good performance for authentication system matching.

Incorporating an extended dendritic growth model into the CAFE model for rapidly solidified non-dilute alloys

International Nuclear Information System (INIS)

Ma, Jie; Wang, Bo; Zhao, Shunli; Wu, Guangxin; Zhang, Jieyu; Yang, Zhiliang

2016-01-01

We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.

Incorporating an extended dendritic growth model into the CAFE model for rapidly solidified non-dilute alloys

Energy Technology Data Exchange (ETDEWEB)

Ma, Jie; Wang, Bo [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhao, Shunli [Research Institute, Baoshan Iron & Steel Co., Ltd, Shanghai 201900 (China); Wu, Guangxin [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhang, Jieyu, E-mail: zjy6162@staff.shu.edu.cn [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Yang, Zhiliang [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China)

2016-05-25

We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.

Bone Marrow-Derived, Neural-Like Cells Have the Characteristics of Neurons to Protect the Peripheral Nerve in Microenvironment

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Shi-lei Guo

2015-01-01

Full Text Available Effective repair of peripheral nerve defects is difficult because of the slow growth of new axonal growth. We propose that “neural-like cells” may be useful for the protection of peripheral nerve destructions. Such cells should prolong the time for the disintegration of spinal nerves, reduce lesions, and improve recovery. But the mechanism of neural-like cells in the peripheral nerve is still unclear. In this study, bone marrow-derived neural-like cells were used as seed cells. The cells were injected into the distal end of severed rabbit peripheral nerves that were no longer integrated with the central nervous system. Electromyography (EMG, immunohistochemistry, and transmission electron microscopy (TEM were employed to analyze the development of the cells in the peripheral nerve environment. The CMAP amplitude appeared during the 5th week following surgery, at which time morphological characteristics of myelinated nerve fiber formation were observed. Bone marrow-derived neural-like cells could protect the disintegration and destruction of the injured peripheral nerve.

Gradient microfluidics enables rapid bacterial growth inhibition testing.

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Li, Bing; Qiu, Yong; Glidle, Andrew; McIlvenna, David; Luo, Qian; Cooper, Jon; Shi, Han-Chang; Yin, Huabing

2014-03-18

Bacterial growth inhibition tests have become a standard measure of the adverse effects of inhibitors for a wide range of applications, such as toxicity testing in the medical and environmental sciences. However, conventional well-plate formats for these tests are laborious and provide limited information (often being restricted to an end-point assay). In this study, we have developed a microfluidic system that enables fast quantification of the effect of an inhibitor on bacteria growth and survival, within a single experiment. This format offers a unique combination of advantages, including long-term continuous flow culture, generation of concentration gradients, and single cell morphology tracking. Using Escherichia coli and the inhibitor amoxicillin as one model system, we show excellent agreement between an on-chip single cell-based assay and conventional methods to obtain quantitative measures of antibiotic inhibition (for example, minimum inhibition concentration). Furthermore, we show that our methods can provide additional information, over and above that of the standard well-plate assay, including kinetic information on growth inhibition and measurements of bacterial morphological dynamics over a wide range of inhibitor concentrations. Finally, using a second model system, we show that this chip-based systems does not require the bacteria to be labeled and is well suited for the study of naturally occurring species. We illustrate this using Nitrosomonas europaea, an environmentally important bacteria, and show that the chip system can lead to a significant reduction in the period required for growth and inhibition measurements (<4 days, compared to weeks in a culture flask).

A Rapid Identification Method for Calamine Using Near-Infrared Spectroscopy Based on Multi-Reference Correlation Coefficient Method and Back Propagation Artificial Neural Network.

Science.gov (United States)

Sun, Yangbo; Chen, Long; Huang, Bisheng; Chen, Keli

2017-07-01

As a mineral, the traditional Chinese medicine calamine has a similar shape to many other minerals. Investigations of commercially available calamine samples have shown that there are many fake and inferior calamine goods sold on the market. The conventional identification method for calamine is complicated, therefore as a result of the large scale of calamine samples, a rapid identification method is needed. To establish a qualitative model using near-infrared (NIR) spectroscopy for rapid identification of various calamine samples, large quantities of calamine samples including crude products, counterfeits and processed products were collected and correctly identified using the physicochemical and powder X-ray diffraction method. The NIR spectroscopy method was used to analyze these samples by combining the multi-reference correlation coefficient (MRCC) method and the error back propagation artificial neural network algorithm (BP-ANN), so as to realize the qualitative identification of calamine samples. The accuracy rate of the model based on NIR and MRCC methods was 85%; in addition, the model, which took comprehensive multiple factors into consideration, can be used to identify crude calamine products, its counterfeits and processed products. Furthermore, by in-putting the correlation coefficients of multiple references as the spectral feature data of samples into BP-ANN, a BP-ANN model of qualitative identification was established, of which the accuracy rate was increased to 95%. The MRCC method can be used as a NIR-based method in the process of BP-ANN modeling.

Anger in brain and body: the neural and physiological perturbation of decision-making by emotion.

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Garfinkel, Sarah N; Zorab, Emma; Navaratnam, Nakulan; Engels, Miriam; Mallorquí-Bagué, Núria; Minati, Ludovico; Dowell, Nicholas G; Brosschot, Jos F; Thayer, Julian F; Critchley, Hugo D

2016-01-01

Emotion and cognition are dynamically coupled to bodily arousal: the induction of anger, even unconsciously, can reprioritise neural and physiological resources toward action states that bias cognitive processes. Here we examine behavioural, neural and bodily effects of covert anger processing and its influence on cognition, indexed by lexical decision-making. While recording beat-to-beat blood pressure, the words ANGER or RELAX were presented subliminally just prior to rapid word/non-word reaction-time judgements of letter-strings. Subliminal ANGER primes delayed the time taken to reach rapid lexical decisions, relative to RELAX primes. However, individuals with high trait anger were speeded up by subliminal anger primes. ANGER primes increased systolic blood pressure and the magnitude of this increase predicted reaction time prolongation. Within the brain, ANGER trials evoked an enhancement of activity within dorsal pons and an attenuation of activity within visual occipitotemporal and attentional parietal cortices. Activity within periaqueductal grey matter, occipital and parietal regions increased linearly with evoked blood pressure changes, indicating neural substrates through which covert anger impairs semantic decisions, putatively through its expression as visceral arousal. The behavioural and physiological impact of anger states compromises the efficiency of cognitive processing through action-ready changes in autonomic response that skew regional neural activity. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Rapid and Objective Assessment of Neural Function in Autism Spectrum Disorder Using Transient Visual Evoked Potentials.

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Paige M Siper

Full Text Available There is a critical need to identify biomarkers and objective outcome measures that can be used to understand underlying neural mechanisms in autism spectrum disorder (ASD. Visual evoked potentials (VEPs offer a noninvasive technique to evaluate the functional integrity of neural mechanisms, specifically visual pathways, while probing for disease pathophysiology.Transient VEPs (tVEPs were obtained from 96 unmedicated children, including 37 children with ASD, 36 typically developing (TD children, and 23 unaffected siblings (SIBS. A conventional contrast-reversing checkerboard condition was compared to a novel short-duration condition, which was developed to enable objective data collection from severely affected populations who are often excluded from electroencephalographic (EEG studies.Children with ASD showed significantly smaller amplitudes compared to TD children at two of the earliest critical VEP components, P60-N75 and N75-P100. SIBS showed intermediate responses relative to ASD and TD groups. There were no group differences in response latency. Frequency band analyses indicated significantly weaker responses for the ASD group in bands encompassing gamma-wave activity. Ninety-two percent of children with ASD were able to complete the short-duration condition compared to 68% for the standard condition.The current study establishes the utility of a short-duration tVEP test for use in children at varying levels of functioning and describes neural abnormalities in children with idiopathic ASD. Implications for excitatory/inhibitory balance as well as the potential application of VEP for use in clinical trials are discussed.

Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

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Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C

2013-11-01

Human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, are unique cell sources for disease modeling, drug discovery screens, and cell therapy applications. The first step in producing neural lineages from hPSCs is the generation of neural stem cells (NSCs). Current methods of NSC derivation involve the time-consuming, labor-intensive steps of an embryoid body generation or coculture with stromal cell lines that result in low-efficiency derivation of NSCs. In this study, we report a highly efficient serum-free pluripotent stem cell neural induction medium that can induce hPSCs into primitive NSCs (pNSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. The pNSCs expressed the neural stem cell markers Pax6, Sox1, Sox2, and Nestin; were negative for Oct4; could be expanded for multiple passages; and could be differentiated into neurons, astrocytes, and oligodendrocytes, in addition to the brain region-specific neuronal subtypes GABAergic, dopaminergic, and motor neurons. Global gene expression of the transcripts of pNSCs was comparable to that of rosette-derived and human fetal-derived NSCs. This work demonstrates an efficient method to generate expandable pNSCs, which can be further differentiated into central nervous system neurons and glia with temporal, spatial, and positional cues of brain regional heterogeneity. This method of pNSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

Evolvable synthetic neural system

Science.gov (United States)

Curtis, Steven A. (Inventor)

2009-01-01

An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

The Effects of Low-Dose Bisphenol A and Bisphenol F on Neural Differentiation of a Fetal Brain-Derived Neural Progenitor Cell Line.

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Fujiwara, Yuki; Miyazaki, Wataru; Koibuchi, Noriyuki; Katoh, Takahiko

2018-01-01

Environmental chemicals are known to disrupt the endocrine system in humans and to have adverse effects on several organs including the developing brain. Recent studies indicate that exposure to environmental chemicals during gestation can interfere with neuronal differentiation, subsequently affecting normal brain development in newborns. Xenoestrogen, bisphenol A (BPA), which is widely used in plastic products, is one such chemical. Adverse effects of exposure to BPA during pre- and postnatal periods include the disruption of brain function. However, the effect of BPA on neural differentiation remains unclear. In this study, we explored the effects of BPA or bisphenol F (BPF), an alternative compound for BPA, on neural differentiation using ReNcell, a human fetus-derived neural progenitor cell line. Maintenance in growth factor-free medium initiated the differentiation of ReNcell to neuronal cells including neurons, astrocytes, and oligodendrocytes. We exposed the cells to BPA or BPF for 3 days from the period of initiation and performed real-time PCR for neural markers such as β III-tubulin and glial fibrillary acidic protein (GFAP), and Olig2. The β III-tubulin mRNA level decreased in response to BPA, but not BPF, exposure. We also observed that the number of β III-tubulin-positive cells in the BPA-exposed group was less than that of the control group. On the other hand, there were no changes in the MAP2 mRNA level. These results indicate that BPA disrupts neural differentiation in human-derived neural progenitor cells, potentially disrupting brain development.

The Effects of Low-Dose Bisphenol A and Bisphenol F on Neural Differentiation of a Fetal Brain-Derived Neural Progenitor Cell Line

Directory of Open Access Journals (Sweden)

Yuki Fujiwara

2018-02-01

Full Text Available Environmental chemicals are known to disrupt the endocrine system in humans and to have adverse effects on several organs including the developing brain. Recent studies indicate that exposure to environmental chemicals during gestation can interfere with neuronal differentiation, subsequently affecting normal brain development in newborns. Xenoestrogen, bisphenol A (BPA, which is widely used in plastic products, is one such chemical. Adverse effects of exposure to BPA during pre- and postnatal periods include the disruption of brain function. However, the effect of BPA on neural differentiation remains unclear. In this study, we explored the effects of BPA or bisphenol F (BPF, an alternative compound for BPA, on neural differentiation using ReNcell, a human fetus-derived neural progenitor cell line. Maintenance in growth factor-free medium initiated the differentiation of ReNcell to neuronal cells including neurons, astrocytes, and oligodendrocytes. We exposed the cells to BPA or BPF for 3 days from the period of initiation and performed real-time PCR for neural markers such as β III-tubulin and glial fibrillary acidic protein (GFAP, and Olig2. The β III-tubulin mRNA level decreased in response to BPA, but not BPF, exposure. We also observed that the number of β III-tubulin-positive cells in the BPA-exposed group was less than that of the control group. On the other hand, there were no changes in the MAP2 mRNA level. These results indicate that BPA disrupts neural differentiation in human-derived neural progenitor cells, potentially disrupting brain development.

Controlling Growth High Uniformity Indium Selenide (In2Se3) Nanowires via the Rapid Thermal Annealing Process at Low Temperature.

Science.gov (United States)

Hsu, Ya-Chu; Hung, Yu-Chen; Wang, Chiu-Yen

2017-09-15

High uniformity Au-catalyzed indium selenide (In 2 Se 3) nanowires are grown with the rapid thermal annealing (RTA) treatment via the vapor-liquid-solid (VLS) mechanism. The diameters of Au-catalyzed In 2 Se 3 nanowires could be controlled with varied thicknesses of Au films, and the uniformity of nanowires is improved via a fast pre-annealing rate, 100 °C/s. Comparing with the slower heating rate, 0.1 °C/s, the average diameters and distributions (standard deviation, SD) of In 2 Se 3 nanowires with and without the RTA process are 97.14 ± 22.95 nm (23.63%) and 119.06 ± 48.75 nm (40.95%), respectively. The in situ annealing TEM is used to study the effect of heating rate on the formation of Au nanoparticles from the as-deposited Au film. The results demonstrate that the average diameters and distributions of Au nanoparticles with and without the RTA process are 19.84 ± 5.96 nm (30.00%) and about 22.06 ± 9.00 nm (40.80%), respectively. It proves that the diameter size, distribution, and uniformity of Au-catalyzed In 2 Se 3 nanowires are reduced and improved via the RTA pre-treated. The systemic study could help to control the size distribution of other nanomaterials through tuning the annealing rate, temperatures of precursor, and growth substrate to control the size distribution of other nanomaterials. Graphical Abstract Rapid thermal annealing (RTA) process proved that it can uniform the size distribution of Au nanoparticles, and then it can be used to grow the high uniformity Au-catalyzed In 2 Se 3 nanowires via the vapor-liquid-solid (VLS) mechanism. Comparing with the general growth condition, the heating rate is slow, 0.1 °C/s, and the growth temperature is a relatively high growth temperature, > 650 °C. RTA pre-treated growth substrate can form smaller and uniform Au nanoparticles to react with the In 2 Se 3 vapor and produce the high uniformity In 2 Se 3 nanowires. The in situ annealing TEM is used to realize the effect of heating

Microfluidic systems for stem cell-based neural tissue engineering.

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Karimi, Mahdi; Bahrami, Sajad; Mirshekari, Hamed; Basri, Seyed Masoud Moosavi; Nik, Amirala Bakhshian; Aref, Amir R; Akbari, Mohsen; Hamblin, Michael R

2016-07-05

Neural tissue engineering aims at developing novel approaches for the treatment of diseases of the nervous system, by providing a permissive environment for the growth and differentiation of neural cells. Three-dimensional (3D) cell culture systems provide a closer biomimetic environment, and promote better cell differentiation and improved cell function, than could be achieved by conventional two-dimensional (2D) culture systems. With the recent advances in the discovery and introduction of different types of stem cells for tissue engineering, microfluidic platforms have provided an improved microenvironment for the 3D-culture of stem cells. Microfluidic systems can provide more precise control over the spatiotemporal distribution of chemical and physical cues at the cellular level compared to traditional systems. Various microsystems have been designed and fabricated for the purpose of neural tissue engineering. Enhanced neural migration and differentiation, and monitoring of these processes, as well as understanding the behavior of stem cells and their microenvironment have been obtained through application of different microfluidic-based stem cell culture and tissue engineering techniques. As the technology advances it may be possible to construct a "brain-on-a-chip". In this review, we describe the basics of stem cells and tissue engineering as well as microfluidics-based tissue engineering approaches. We review recent testing of various microfluidic approaches for stem cell-based neural tissue engineering.

Cocaine action on peripheral, non-monoamine neural substrates as a trigger of electroencephalographic desynchronization and electromyographic activation following i.v. administration in freely moving rats.

Science.gov (United States)

Smirnov, M S; Kiyatkin, E A

2010-01-20

Many important physiological, behavioral and subjective effects of i.v. cocaine (COC) are exceptionally rapid and transient, suggesting a possible involvement of peripheral neural substrates in their triggering. In the present study, we used high-speed electroencephalographic (EEG) and electromyographic (EMG) recordings (4-s resolution) in freely moving rats to characterize the central electrophysiological effects of i.v. COC at low doses within a self-administration range (0.25-1.0 mg/kg). We found that COC induces rapid, strong, and prolonged desynchronization of cortical EEG (decrease in alpha and increase in beta and gamma activity) and activation of the neck EMG that begin within 2-6 s following the start of a 10-s injection; immediate components of both effects were dose-independent. The rapid effects of COC were mimicked by i.v. COC methiodide (COC-MET), a derivative that cannot cross the blood-brain barrier. At equimolar doses (0.33-1.33 mg/kg), COC-MET had equally fast and strong effects on EEG and EMG total powers, decreasing alpha and increasing beta and gamma activities. Rapid EEG desynchronization and EMG activation was also induced by i.v. procaine, a structurally similar, short-acting local anesthetic with virtually no effects on monoamine uptake; at equipotential doses (1.25-5.0 mg/kg), these effects were weaker and shorter in duration than those of COC. Surprisingly, i.v. saline injection delivered during slow-wave sleep (but not during quiet wakefulness) also induced a transient EEG desynchronization but without changes in EMG and motor activity; these effects were significantly weaker and much shorter than those induced by all tested drugs. These data suggest that in awake animals, i.v. COC induces rapid cortical activation and a subsequent motor response via its action on peripheral non-monoamine neural elements, involving neural transmission via visceral sensory pathways. By providing a rapid neural signal and triggering neural activation, such

Characterization of TLX expression in neural stem cells and progenitor cells in adult brains.

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Shengxiu Li

Full Text Available TLX has been shown to play an important role in regulating the self-renewal and proliferation of neural stem cells in adult brains. However, the cellular distribution of endogenous TLX protein in adult brains remains to be elucidated. In this study, we used immunostaining with a TLX-specific antibody to show that TLX is expressed in both neural stem cells and transit-amplifying neural progenitor cells in the subventricular zone (SVZ of adult mouse brains. Then, using a double thymidine analog labeling approach, we showed that almost all of the self-renewing neural stem cells expressed TLX. Interestingly, most of the TLX-positive cells in the SVZ represented the thymidine analog-negative, relatively quiescent neural stem cell population. Using cell type markers and short-term BrdU labeling, we demonstrated that TLX was also expressed in the Mash1+ rapidly dividing type C cells. Furthermore, loss of TLX expression dramatically reduced BrdU label-retaining neural stem cells and the actively dividing neural progenitor cells in the SVZ, but substantially increased GFAP staining and extended GFAP processes. These results suggest that TLX is essential to maintain the self-renewing neural stem cells in the SVZ and that the GFAP+ cells in the SVZ lose neural stem cell property upon loss of TLX expression. Understanding the cellular distribution of TLX and its function in specific cell types may provide insights into the development of therapeutic tools for neurodegenerative diseases by targeting TLX in neural stem/progenitors cells.

Meninges harbor cells expressing neural precursor markers during development and adulthood.

Science.gov (United States)

Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

2015-01-01

Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood.

Ultra-thin flexible polyimide neural probe embedded in a dissolvable maltose-coated microneedle

International Nuclear Information System (INIS)

Xiang, Zhuolin; Yen, Shih-Cheng; Zhang, Songsong; Lee, Chengkuo; Xue, Ning; Sun, Tao; Tsang, Wei Mong; Liao, Lun-De; Thakor, Nitish V

2014-01-01

The ultra-thin flexible polyimide neural probe can reduce the glial sheath growth on the probe body while its flexibility can minimize the micromotion between the probe and brain tissue. To provide sufficient stiffness for penetration purposes, we developed a drawing lithography technology for uniform maltose coating to make the maltose-coated polyimide neural probe become a stiff microneedle. The coating thicknesses under different temperature and the corresponding stiffness are studied. It has been proven that the coated maltose is dissolved by body fluids after implantation for a few seconds. Moreover, carbon nanotubes are coated on the neural probe recording electrodes to improve the charge delivery ability and reduce the impedance. Last but not least, the feasibility and recording characteristic of this ultra-thin polyimide neural probe embedded in a maltose-coated microneedle are further demonstrated by in vivo tests. (paper)

Ultra-thin flexible polyimide neural probe embedded in a dissolvable maltose-coated microneedle

Science.gov (United States)

Xiang, Zhuolin; Yen, Shih-Cheng; Xue, Ning; Sun, Tao; Mong Tsang, Wei; Zhang, Songsong; Liao, Lun-De; Thakor, Nitish V.; Lee, Chengkuo

2014-06-01

The ultra-thin flexible polyimide neural probe can reduce the glial sheath growth on the probe body while its flexibility can minimize the micromotion between the probe and brain tissue. To provide sufficient stiffness for penetration purposes, we developed a drawing lithography technology for uniform maltose coating to make the maltose-coated polyimide neural probe become a stiff microneedle. The coating thicknesses under different temperature and the corresponding stiffness are studied. It has been proven that the coated maltose is dissolved by body fluids after implantation for a few seconds. Moreover, carbon nanotubes are coated on the neural probe recording electrodes to improve the charge delivery ability and reduce the impedance. Last but not least, the feasibility and recording characteristic of this ultra-thin polyimide neural probe embedded in a maltose-coated microneedle are further demonstrated by in vivo tests.

Curative effect of surgery combined with nerve growth factor preparation treatment of acute cerebral hemorrhage

Directory of Open Access Journals (Sweden)

Fei Luo

2017-01-01

Conclusion: Surgery combined with nerve growth factor preparation treatment of acute cerebral hemorrhage can improve neural nutritional status and reduce nerve injury degree, and it is beneficial to the recovery of neural function.

High growth and rapid internationalisation of firms from emerging markets: the case of the Middle East and North Africa (MENA) Region

OpenAIRE

Hatem, Omaima

2012-01-01

The aim of this thesis is to understand the phenomena of the high growth and rapid internationalisation of firms from emerging markets. It explores the applicability of international entrepreneurship theory to the context of the emerging market enterprises in the Middle East and North Africa (MENA) region. It integrates the literature of strategic entrepreneurship and that of portfolio entrepreneurship with the literature of international entrepreneurship to provide a closer fi...

Dissociated neural processing for decisions in managers and non-managers.

Science.gov (United States)

Caspers, Svenja; Heim, Stefan; Lucas, Marc G; Stephan, Egon; Fischer, Lorenz; Amunts, Katrin; Zilles, Karl

2012-01-01

Functional neuroimaging studies of decision-making so far mainly focused on decisions under uncertainty or negotiation with other persons. Dual process theory assumes that, in such situations, decision making relies on either a rapid intuitive, automated or a slower rational processing system. However, it still remains elusive how personality factors or professional requirements might modulate the decision process and the underlying neural mechanisms. Since decision making is a key task of managers, we hypothesized that managers, facing higher pressure for frequent and rapid decisions than non-managers, prefer the heuristic, automated decision strategy in contrast to non-managers. Such different strategies may, in turn, rely on different neural systems. We tested managers and non-managers in a functional magnetic resonance imaging study using a forced-choice paradigm on word-pairs. Managers showed subcortical activation in the head of the caudate nucleus, and reduced hemodynamic response within the cortex. In contrast, non-managers revealed the opposite pattern. With the head of the caudate nucleus being an initiating component for process automation, these results supported the initial hypothesis, hinting at automation during decisions in managers. More generally, the findings reveal how different professional requirements might modulate cognitive decision processing.

Rapid broad area search and detection of Chinese surface-to-air missile sites using deep convolutional neural networks

Science.gov (United States)

Marcum, Richard A.; Davis, Curt H.; Scott, Grant J.; Nivin, Tyler W.

2017-10-01

We evaluated how deep convolutional neural networks (DCNN) could assist in the labor-intensive process of human visual searches for objects of interest in high-resolution imagery over large areas of the Earth's surface. Various DCNN were trained and tested using fewer than 100 positive training examples (China only) from a worldwide surface-to-air-missile (SAM) site dataset. A ResNet-101 DCNN achieved a 98.2% average accuracy for the China SAM site data. The ResNet-101 DCNN was used to process ˜19.6 M image chips over a large study area in southeastern China. DCNN chip detections (˜9300) were postprocessed with a spatial clustering algorithm to produce a ranked list of ˜2100 candidate SAM site locations. The combination of DCNN processing and spatial clustering effectively reduced the search area by ˜660X (0.15% of the DCNN-processed land area). An efficient web interface was used to facilitate a rapid serial human review of the candidate SAM sites in the China study area. Four novice imagery analysts with no prior imagery analysis experience were able to complete a DCNN-assisted SAM site search in an average time of ˜42 min. This search was ˜81X faster than a traditional visual search over an equivalent land area of ˜88,640 km2 while achieving nearly identical statistical accuracy (˜90% F1).

Natural language acquisition in large scale neural semantic networks

Science.gov (United States)

Ealey, Douglas

This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

Science.gov (United States)

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Rapid Aminoglycoside NP Test for Rapid Detection of Multiple Aminoglycoside Resistance in Enterobacteriaceae.

Science.gov (United States)

Nordmann, Patrice; Jayol, Aurélie; Dobias, Jan; Poirel, Laurent

2017-04-01

The rapid aminoglycoside NP (Nordmann/Poirel) test was developed to rapidly identify multiple aminoglycoside (AG) resistance in Enterobacteriaceae It is based on the detection of the glucose metabolism related to enterobacterial growth in the presence of a defined concentration of amikacin plus gentamicin. Formation of acid metabolites was evidenced by a color change (orange to yellow) of the red phenol pH indicator. The rapid aminoglycoside NP test was evaluated by using bacterial colonies of 18 AG-resistant isolates producing 16S rRNA methylases, 20 AG-resistant isolates expressing AG-modifying enzymes (acetyl-, adenyl-, and phosphotransferases), and 10 isolates susceptible to AG. Its sensitivity and specificity were 100% and 97%, respectively, compared to the broth dilution method, which was taken as the gold standard for determining aminoglycoside resistance. The test is inexpensive, rapid (<2 h), and implementable worldwide. Copyright © 2017 American Society for Microbiology.

Deletion of OTX2 in neural ectoderm delays anterior pituitary development

Science.gov (United States)

Mortensen, Amanda H.; Schade, Vanessa; Lamonerie, Thomas; Camper, Sally A.

2015-01-01

OTX2 is a homeodomain transcription factor that is necessary for normal head development in mouse and man. Heterozygosity for loss-of-function alleles causes an incompletely penetrant, haploinsufficiency disorder. Affected individuals exhibit a spectrum of features that range from developmental defects in eye and/or pituitary development to acephaly. To investigate the mechanism underlying the pituitary defects, we used different cre lines to inactivate Otx2 in early head development and in the prospective anterior and posterior lobes. Mice homozygous for Otx2 deficiency in early head development and pituitary oral ectoderm exhibit craniofacial defects and pituitary gland dysmorphology, but normal pituitary cell specification. The morphological defects mimic those observed in humans and mice with OTX2 heterozygous mutations. Mice homozygous for Otx2 deficiency in the pituitary neural ectoderm exhibited altered patterning of gene expression and ablation of FGF signaling. The posterior pituitary lobe and stalk, which normally arise from neural ectoderm, were extremely hypoplastic. Otx2 expression was intact in Rathke's pouch, the precursor to the anterior lobe, but the anterior lobe was hypoplastic. The lack of FGF signaling from the neural ectoderm was sufficient to impair anterior lobe growth, but not the differentiation of hormone-producing cells. This study demonstrates that Otx2 expression in the neural ectoderm is important intrinsically for the development of the posterior lobe and pituitary stalk, and it has significant extrinsic effects on anterior pituitary growth. Otx2 expression early in head development is important for establishing normal craniofacial features including development of the brain, eyes and pituitary gland. PMID:25315894

Rapid Startup and Loading of an Attached Growth, Simultaneous Nitrification/Denitrification Membrane Aerated Bioreactor

Science.gov (United States)

Meyer, Caitlin; Vega, Leticia

2014-01-01

The Membrane Aerated Bioreactor (MABR) is an attached-growth biological system for simultaneous nitrification and denitrification. This design is an innovative approach to common terrestrial wastewater treatments for nitrogen and carbon removal. Implementing a biologically-based water treatment system for long-duration human exploration is an attractive, low energy alternative to physiochemical processes. Two obstacles to implementing such a system are (1) the "start-up" duration from inoculation to steady-state operations and (2) the amount of surface area needed for the biological activity to occur. The Advanced Water Recovery Systems (AWRS) team at JSC explored these two issues through two tests; a rapid inoculation study and a wastewater loading study. Results from these tests demonstrate that the duration from inoculation to steady state can be reduced to two weeks and that the surface area to volume ratio baseline used in the Alternative Water Processor (AWP) test was higher than what was needed to remove the organic carbon and ammonium from the system.

The neural optimal control hierarchy for motor control

Science.gov (United States)

DeWolf, T.; Eliasmith, C.

2011-10-01

Our empirical, neuroscientific understanding of biological motor systems has been rapidly growing in recent years. However, this understanding has not been systematically mapped to a quantitative characterization of motor control based in control theory. Here, we attempt to bridge this gap by describing the neural optimal control hierarchy (NOCH), which can serve as a foundation for biologically plausible models of neural motor control. The NOCH has been constructed by taking recent control theoretic models of motor control, analyzing the required processes, generating neurally plausible equivalent calculations and mapping them on to the neural structures that have been empirically identified to form the anatomical basis of motor control. We demonstrate the utility of the NOCH by constructing a simple model based on the identified principles and testing it in two ways. First, we perturb specific anatomical elements of the model and compare the resulting motor behavior with clinical data in which the corresponding area of the brain has been damaged. We show that damaging the assigned functions of the basal ganglia and cerebellum can cause the movement deficiencies seen in patients with Huntington's disease and cerebellar lesions. Second, we demonstrate that single spiking neuron data from our model's motor cortical areas explain major features of single-cell responses recorded from the same primate areas. We suggest that together these results show how NOCH-based models can be used to unify a broad range of data relevant to biological motor control in a quantitative, control theoretic framework.

Adipose stromal cells contain phenotypically distinct adipogenic progenitors derived from neural crest.

Directory of Open Access Journals (Sweden)

Yoshihiro Sowa

Full Text Available Recent studies have shown that adipose-derived stromal/stem cells (ASCs contain phenotypically and functionally heterogeneous subpopulations of cells, but their developmental origin and their relative differentiation potential remain elusive. In the present study, we aimed at investigating how and to what extent the neural crest contributes to ASCs using Cre-loxP-mediated fate mapping. ASCs harvested from subcutaneous fat depots of either adult P0-Cre/or Wnt1-Cre/Floxed-reporter mice contained a few neural crest-derived ASCs (NCDASCs. This subpopulation of cells was successfully expanded in vitro under standard culture conditions and their growth rate was comparable to non-neural crest derivatives. Although NCDASCs were positive for several mesenchymal stem cell markers as non-neural crest derivatives, they exhibited a unique bipolar or multipolar morphology with higher expression of markers for both neural crest progenitors (p75NTR, Nestin, and Sox2 and preadipocytes (CD24, CD34, S100, Pref-1, GATA2, and C/EBP-delta. NCDASCs were able to differentiate into adipocytes with high efficiency but their osteogenic and chondrogenic potential was markedly attenuated, indicating their commitment to adipogenesis. In vivo, a very small proportion of adipocytes were originated from the neural crest. In addition, p75NTR-positive neural crest-derived cells were identified along the vessels within the subcutaneous adipose tissue, but they were negative for mural and endothelial markers. These results demonstrate that ASCs contain neural crest-derived adipocyte-restricted progenitors whose phenotype is distinct from that of non-neural crest derivatives.

An analysis of social consequences of rapid fertility decline in China.

Science.gov (United States)

Liu, Z; Liu, L

1988-12-01

Rapid fertility decline in China has brought about 2 direct effects: 1) the natural increase of the population has slowed down, and 2) the age structure has changed from the young to the adult type. These 2 effects have caused a series of economic and social consequences. Rapid fertility decline increases the gross national product per capita and accelerates the improvement of people's lives. Rapid fertility decline slows population growth and speeds up the accumulation of capital and the development of the economy. Since 1981, accumulation growth has exceeded consumption growth. Fertility decline alleviates the enrollment pressure on primary and secondary schools, raises the efficiency of education funds, and promotes the popularization of education. The family planning program strengthens the maternal and child health care and the medical care systems. As the result of economic development, the people's nutritional levels are improving. The physical quality of teenagers has improved steadily. The change in the age structure will alleviate the tension of rapid population growth and benefit population control in the next century. Fertility decline forces the traditional attitude toward childbearing from "more children, more happiness" to improved quality of children. The rapid fertility decline has caused a great deal of concern both inside and outside China about the aging of the population. The labor force, however, will continue to grow for the next 60 years. At present, China's population problems are still those of population growth.

Morphological neural networks

Energy Technology Data Exchange (ETDEWEB)

Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

1996-12-31

The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

Spatially pooled contrast responses predict neural and perceptual similarity of naturalistic image categories.

Directory of Open Access Journals (Sweden)

Iris I A Groen

Full Text Available The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis. Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task.

Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

Science.gov (United States)

Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

2012-01-01

The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task. PMID:23093921

Application of self-organizing competition artificial neural network to logging data explanation of sandstone-hosted uranium deposits

International Nuclear Information System (INIS)

Xu Jianguo; Xu Xianli; Wang Weiguo

2008-01-01

The article describes the model construction of self-organizing competition artificial neural network, its principle and automatic recognition process of borehole lithology in detail, and then proves the efficiency of the neural network model for automatically recognizing the borehole lithology with some cases. The self-organizing competition artificial neural network has the ability of self- organization, self-adjustment and high permitting errors. Compared with the BP algorithm, it takes less calculation quantity and more rapidly converges. Furthermore, it can automatically confirm the category without the known sample information. Trial results based on contrasting the identification results of the borehole lithology with geological documentations, indicate that self-organizing artificial neural network can be well applied to automatically performing the category of borehole lithology, during the logging data explanation of sandstone-hosted uranium deposits. (authors)

Population Growth and Poverty in the Developing World.

Science.gov (United States)

Birdsall, Nancy

1980-01-01

The link between rapid population growth and the absolute poverty which currently afflicts 780 million people in developing countries (excluding China and other centrally planned economies) is examined. As a result of rapid population growth, many countries suffer slow per capita income growth, a lack of progress in reducing income inequality, and…

On the mechanism of rapid postirradiation recovery of yeast

International Nuclear Information System (INIS)

Glazunov, A.V.; Kapul'tsevich, Yu.G.

1983-01-01

Rapid postirradiation recovery of diploid yeast Saccharomyces cerevisiae is equally effective both in water and in a liquid nutrition medium. In the haploid strains, rapid recovery occurs more readily in the log phase than in the stationary phase of growth. In the diploid strains, rapid recovery is more effective in the log phase than in the stationary phase. Rapid recovery of yeast does not require an additional protein synthesis. Damages induced by UV-light are not sub ected to rapid recovery

ETOH inhibits embryonic neural stem/precursor cell proliferation via PLD signaling

International Nuclear Information System (INIS)

Fujita, Yuko; Hiroyama, Masami; Sanbe, Atsushi; Yamauchi, Junji; Murase, Shoko; Tanoue, Akito

2008-01-01

While a mother's excessive alcohol consumption during pregnancy is known to have adverse effects on fetal neural development, little is known about the underlying mechanism of these effects. In order to investigate these mechanisms, we investigated the toxic effect of ethanol (ETOH) on neural stem/precursor cell (NSC) proliferation. In cultures of NSCs, phospholipase D (PLD) is activated following stimulation with epidermal growth factor (EGF) and fibroblast growth factor 2 (FGF2). Exposure of NSCs to ETOH suppresses cell proliferation, while it has no effect on cell death. Phosphatidic acid (PA), which is a signaling messenger produced by PLD, reverses ETOH inhibition of NSC proliferation. Blocking the PLD signal by 1-butanol suppresses the proliferation. ETOH-induced suppression of NSC proliferation and the protective effect of PA for ETOH-induced suppression are mediated through extracellular signal-regulated kinase signaling. These results indicate that exposure to ETOH impairs NSC proliferation by altering the PLD signaling pathway

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Stage-specific control of neural crest stem cell proliferation by the small rho GTPases Cdc42 and Rac1

DEFF Research Database (Denmark)

Fuchs, Sebastian; Herzog, Dominik; Sumara, Grzegorz

2009-01-01

-renewal and proliferation of later stage, but not early migratory NCSCs. This stage-specific requirement for small Rho GTPases is due to changes in NCSCs that, during development, acquire responsiveness to mitogenic EGF acting upstream of both Cdc42 and Rac1. Thus, our data reveal distinct mechanisms for growth control......The neural crest (NC) generates a variety of neural and non-neural tissues during vertebrate development. Both migratory NC cells and their target structures contain cells with stem cell features. Here we show that these populations of neural crest-derived stem cells (NCSCs) are differentially...

Rapidity distributions of secondary particles in hadron-nucleus collisions

International Nuclear Information System (INIS)

Alaverdyan, G.B.; Pak, A.S.; Tarasov, A.V.; Tseren, Ch.; Uzhinsky, V.V.

1979-01-01

In the framework of the cascade model of a leading particle the rapidity distributions of secondary particles in the hadron-nucleus interactions are considered. The energy loss fluctuations of leading particles in the successive collisions have been taken into account. It is shown that the centre of rapidity distribution is displaced towards small rapidity with target nucleus atomic number A growth. The model well reproduces the energy and A dependences of the rapidity distributions

Neural Based Orthogonal Data Fitting The EXIN Neural Networks

CERN Document Server

Cirrincione, Giansalvo

2008-01-01

Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

Application of neural networks to waste site screening

Energy Technology Data Exchange (ETDEWEB)

Dabiri, A.E.; Kraft, T.; Hilton, J.M. [Science Applications International Corp., San Diego, CA (United States)

1993-03-01

Waste site screening requires knowledge of the actual concentrations of hazardous materials and rates of flow around and below the site with time. The present approach to site screening consists primarily of drilling, boreholes near contaminated site and chemically analyzing the extracted physical samples and processing the data. In addition, hydraulic and geochemical soil properties are obtained so that numerical simulation models can be used to interpret and extrapolate the field data. The objective of this work is to investigate the feasibility of using neural network techniques to reduce the cost of waste site screening. A successful technique may lead to an ability to reduce the number of boreholes and the number of samples analyzed from each borehole to properly screen the waste site. The analytic tool development described here is inexpensive because it makes use of neural network techniques that can interpolate rapidly and which can learn how to analyze data rather than having to be explicitly programmed. In the following sections, data collection and data analyses will be described, followed by a section on different neural network techniques used. The results will be presented and compared with mathematical model. Finally, the last section will summarize the research work performed and make several recommendations for future work.

Rapid Start-up and Loading of an Attached Growth, Simultaneous Nitrification/Denitrification Membrane Aerated Bioreactor

Science.gov (United States)

Meyer, Caitlin E.; Pensinger, Stuart; Pickering, Karen D.; Barta, Daniel; Shull, Sarah A.; Vega, Letticia M.; Christenson, Dylan; Jackson, W. Andrew

2015-01-01

Membrane aerated bioreactors (MABR) are attached-growth biological systems used for simultaneous nitrification and denitrification to reclaim water from waste. This design is an innovative approach to common terrestrial wastewater treatments for nitrogen and carbon removal and implementing a biologically-based water treatment system for long-duration human exploration is an attractive, low energy alternative to physiochemical processes. Two obstacles to implementing such a system are (1) the "start-up" duration from inoculation to steady-state operations and (2) the amount of surface area needed for the biological activity to occur. The Advanced Water Recovery Systems (AWRS) team at JSC explored these two issues through two tests; a rapid inoculation study and a wastewater loading study. Results from these tests demonstrate that the duration from inoculation to steady state can be reduced to under two weeks, and that despite low ammonium removal rates, the MABRs are oversized.

Study of neural cells on organic semiconductor ultra thin films

Energy Technology Data Exchange (ETDEWEB)

Bystrenova, Eva; Tonazzini, Ilaria; Stoliar, Pablo; Greco, Pierpaolo; Lazar, Adina; Dutta, Soumya; Dionigi, Chiara; Cacace, Marcello; Biscarini, Fabio [ISMN-CNR, Bologna (Italy); Jelitai, Marta; Madarasz, Emilia [IEM- HAS, Budapest (Hungary); Huth, Martin; Nickel, Bert [LMU, Munich (Germany); Martini, Claudia [Dept. PNPB, Univ. of Pisa (Italy)

2008-07-01

Many technological advances are currently being developed for nano-fabrication, offering the ability to create and control patterns of soft materials. We report the deposition of cells on organic semiconductor ultra-thin films. This is a first step towards the development of active bio/non bio systems for electrical transduction. Thin films of pentacene, whose thickness was systematically varied, were grown by high vacuum sublimation. We report adhesion, growth, and differentiation of human astroglial cells and mouse neural stem cells on an organic semiconductor. Viability of astroglial cells in time was measured as a function of the roughness and the characteristic morphology of ultra thin organic film, as well as the features of the patterned molecules. Optical fluorescence microscope coupled to atomic force microscope was used to monitor the presence, density and shape of deposited cells. Neural stem cells remain viable, differentiate by retinoic acid and form dense neuronal networks. We have shown the possibility to integrate living neural cells on organic semiconductor thin films.

Prenatal organochlorine compound exposure, rapid weight gain, and overweight in infancy.

Science.gov (United States)

Mendez, Michelle A; Garcia-Esteban, Raquel; Guxens, Mónica; Vrijheid, Martine; Kogevinas, Manolis; Goñi, Fernando; Fochs, Silvia; Sunyer, Jordi

2011-02-01

Although it has been hypothesized that fetal exposure to endocrine-disrupting chemicals may increase obesity risk, empirical data are limited, and it is uncertain how early in life any effects may begin. We explored whether prenatal exposure to several organochlorine compounds (OCs) is associated with rapid growth in the first 6 months of life and body mass index (BMI) later in infancy. Data come from the INMA (Infancia y Medio-Ambiente) Child and Environment birth cohort in Spain, which recruited 657 women in early pregnancy. Rapid growth during the first 6 months was defined as a change in weight-for-age z-scores > 0.67, and elevated BMI at 14 months, as a z-score ≥ the 85th percentile. Generalized linear models were used to estimate the risk of rapid growth or elevated BMI associated with 2,2-bis(p-chlorophenyl)-1,1-dichloroethylene (DDE), hexachlorobenzene, β-hexachlorohexane, and polychlorinated biphenyls in first-trimester maternal serum. After multivariable adjustment including other OCs, DDE exposure above the first quartile was associated with doubling of the risk of rapid growth among children of normal-weight (BMI < 25 kg/m2), but not overweight, mothers. DDE was also associated with elevated BMI at 14 months (relative risk per unit increase in log DDE = 1.50; 95% confidence interval, 1.11-2.03). Other OCs were not associated with rapid growth or elevated BMI after adjustment. In this study we found prenatal DDE exposure to be associated with rapid weight gain in the first 6 months and elevated BMI later in infancy, among infants of normal-weight mothers. More research exploring the potential role of chemical exposures in early-onset obesity is needed.

Adaptive Neuron Model: An architecture for the rapid learning of nonlinear topological transformations

Science.gov (United States)

Tawel, Raoul (Inventor)

1994-01-01

A method for the rapid learning of nonlinear mappings and topological transformations using a dynamically reconfigurable artificial neural network is presented. This fully-recurrent Adaptive Neuron Model (ANM) network was applied to the highly degenerate inverse kinematics problem in robotics, and its performance evaluation is bench-marked. Once trained, the resulting neuromorphic architecture was implemented in custom analog neural network hardware and the parameters capturing the functional transformation downloaded onto the system. This neuroprocessor, capable of 10(exp 9) ops/sec, was interfaced directly to a three degree of freedom Heathkit robotic manipulator. Calculation of the hardware feed-forward pass for this mapping was benchmarked at approximately 10 microsec.

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

Science.gov (United States)

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

[Research on Rapid Discrimination of Edible Oil by ATR Infrared Spectroscopy].

Science.gov (United States)

Ma, Xiao; Yuan, Hong-fu; Song, Chun-feng; Hu, Ai-qin; Li, Xiao-yu; Zhao, Zhong; Li, Xiu-qin; Guo Zhen; Zhu, Zhi-qiang

2015-07-01

A rapid discrimination method of edible oils, KL-BP model, was proposed by attenuated total reflectance infrared spectroscopy. The model extracts the characteristic of classification from source data by KL and reduces data dimension at the same time. Then the neural network model is constructed by the new data which as the input of the model. 84 edible oil samples which include sesame oil, corn oil, canola oil, blend oil, sunflower oil, peanut oil, olive oil, soybean oil and tea seed oil, were collected and their infrared spectra determined using an ATR FT-IR spectrometer. In order to compare the method performance, principal component analysis (PCA) direct-classification model, KL direct-classification model, PLS-DA model, PCA-BP model and KL-BP model are constructed in this paper. The results show that the recognition rates of PCA, PCA-BP, KL, PLS-DA and KL-BP are 59.1%, 68.2%, 77.3%, 77.3% and 90.9% for discriminating the 9 kinds of edible oils, respectively. KL extracts the eigenvector which make the distance between different class and distance of every class ratio is the largest. So the method can get much more classify information than PCA. BP neural network can effectively enhance the classification ability and accuracy. Taking full of the advantages of KL in extracting more category information in dimension reducing and the features of BP neural network in self-learning, adaptive, nonlinear, the KL-BP method has the best classification ability and recognition accuracy and great importance for rapidly recognizing edible oil in practice.

Real-Coded Quantum-Inspired Genetic Algorithm-Based BP Neural Network Algorithm

Directory of Open Access Journals (Sweden)

Jianyong Liu

2015-01-01

Full Text Available The method that the real-coded quantum-inspired genetic algorithm (RQGA used to optimize the weights and threshold of BP neural network is proposed to overcome the defect that the gradient descent method makes the algorithm easily fall into local optimal value in the learning process. Quantum genetic algorithm (QGA is with good directional global optimization ability, but the conventional QGA is based on binary coding; the speed of calculation is reduced by the coding and decoding processes. So, RQGA is introduced to explore the search space, and the improved varied learning rate is adopted to train the BP neural network. Simulation test shows that the proposed algorithm is effective to rapidly converge to the solution conformed to constraint conditions.

Rapid adaptation of multisensory integration in vestibular pathways

Directory of Open Access Journals (Sweden)

Jerome eCarriot

2015-04-01

Full Text Available Sensing gravity is vital for our perception of spatial orientation, the control of upright posture, and generation of our every day activities. When an astronaut transitions to microgravity or returns to earth, the vestibular input arising from self-motion will not match the brain’s expectation. Our recent neurophysiological studies have provided insight into how the nervous system rapidly reorganizes when vestibular input becomes unreliable by both 1 updating its internal model of the sensory consequences of motion and 2 up-weighting more reliable extra-vestibular information. These neural strategies, in turn, are linked to improvements in sensorimotor performance (e.g., gaze and postural stability, locomotion, orienting and perception characterized by similar time courses. We suggest that furthering our understanding of the neural mechanisms that underlie sensorimotor adaptation will have important implications for optimizing training programs for astronauts before and after space exploration missions and for the design of goal-oriented rehabilitation for patients.

Impaired neuronal maturation of hippocampal neural progenitor cells in mice lacking CRAF.

Science.gov (United States)

Pfeiffer, Verena; Götz, Rudolf; Camarero, Guadelupe; Heinsen, Helmut; Blum, Robert; Rapp, Ulf Rüdiger

2018-01-01

RAF kinases are major constituents of the mitogen activated signaling pathway, regulating cell proliferation, differentiation and cell survival of many cell types, including neurons. In mammals, the family of RAF proteins consists of three members, ARAF, BRAF, and CRAF. Ablation of CRAF kinase in inbred mouse strains causes major developmental defects during fetal growth and embryonic or perinatal lethality. Heterozygous germline mutations in CRAF result in Noonan syndrome, which is characterized by neurocognitive impairment that may involve hippocampal physiology. The role of CRAF signaling during hippocampal development and generation of new postnatal hippocampal granule neurons has not been examined and may provide novel insight into the cause of hippocampal dysfunction in Noonan syndrome. In this study, by crossing CRAF-deficiency to CD-1 outbred mice, a CRAF mouse model was established which enabled us to investigate the interplay of neural progenitor proliferation and postmitotic differentiation during adult neurogenesis in the hippocampus. Albeit the general morphology of the hippocampus was unchanged, CRAF-deficient mice displayed smaller granule cell layer (GCL) volume at postnatal day 30 (P30). In CRAF-deficient mice a substantial number of abnormal, chromophilic, fast dividing cells were found in the subgranular zone (SGZ) and hilus of the dentate gyrus (DG), indicating that CRAF signaling contributes to hippocampal neural progenitor proliferation. CRAF-deficient neural progenitor cells showed an increased cell death rate and reduced neuronal maturation. These results indicate that CRAF function affects postmitotic neural cell differentiation and points to a critical role of CRAF-dependent growth factor signaling pathway in the postmitotic development of adult-born neurons.

Persistent Environmental Toxicants in Breast Milk and Rapid Infant Growth

NARCIS (Netherlands)

Criswell, Rachel; Lenters, Virissa; Mandal, Siddhartha; Stigum, Hein; Iszatt, Nina; Eggesbø, Merete

2017-01-01

BACKGROUND/AIMS: Many environmental toxicants are passed to infants in utero and through breast milk. Exposure to toxicants during the perinatal period can alter growth patterns, impairing growth or increasing obesity risk. Previous studies have focused on only a few toxicants at a time, which may

Artificial neural network modelling in heavy ion collisions

International Nuclear Information System (INIS)

El-dahshan, E.; Radi, A.; El-Bakry, M.Y.; El Mashad, M.

2008-01-01

The neural network (NN) model and parton two fireball model (PTFM) have been used to study the pseudo-rapidity distribution of the shower particles for C 12, O 16, Si 28 and S 32 on nuclear emulsion. The trained NN shows a better fitting with experimental data than the PTFM calculations. The NN is then used to predict the distributions that are not present in the training set and matched them effectively. The NN simulation results prove a strong presence modeling in heavy ion collisions

Matrix regulators in neural stem cell functions.

Science.gov (United States)

Wade, Anna; McKinney, Andrew; Phillips, Joanna J

2014-08-01

Neural stem/progenitor cells (NSPCs) reside within a complex and dynamic extracellular microenvironment, or niche. This niche regulates fundamental aspects of their behavior during normal neural development and repair. Precise yet dynamic regulation of NSPC self-renewal, migration, and differentiation is critical and must persist over the life of an organism. In this review, we summarize some of the major components of the NSPC niche and provide examples of how cues from the extracellular matrix regulate NSPC behaviors. We use proteoglycans to illustrate the many diverse roles of the niche in providing temporal and spatial regulation of cellular behavior. The NSPC niche is comprised of multiple components that include; soluble ligands, such as growth factors, morphogens, chemokines, and neurotransmitters, the extracellular matrix, and cellular components. As illustrated by proteoglycans, a major component of the extracellular matrix, the NSPC, niche provides temporal and spatial regulation of NSPC behaviors. The factors that control NSPC behavior are vital to understand as we attempt to modulate normal neural development and repair. Furthermore, an improved understanding of how these factors regulate cell proliferation, migration, and differentiation, crucial for malignancy, may reveal novel anti-tumor strategies. This article is part of a Special Issue entitled Matrix-mediated cell behaviour and properties. Copyright © 2014 Elsevier B.V. All rights reserved.

Neural Plasticity Is Involved in Physiological Sleep, Depressive Sleep Disturbances, and Antidepressant Treatments

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Meng-Qi Zhang

2017-01-01

Full Text Available Depression, which is characterized by a pervasive and persistent low mood and anhedonia, greatly impacts patients, their families, and society. The associated and recurring sleep disturbances further reduce patient’s quality of life. However, therapeutic sleep deprivation has been regarded as a rapid and robust antidepressant treatment for several decades, which suggests a complicated role of sleep in development of depression. Changes in neural plasticity are observed during physiological sleep, therapeutic sleep deprivation, and depression. This correlation might help us to understand better the mechanism underlying development of depression and the role of sleep. In this review, we first introduce the structure of sleep and the facilitated neural plasticity caused by physiological sleep. Then, we introduce sleep disturbances and changes in plasticity in patients with depression. Finally, the effects and mechanisms of antidepressants and therapeutic sleep deprivation on neural plasticity are discussed.

Dissociated neural processing for decisions in managers and non-managers.

Directory of Open Access Journals (Sweden)

Svenja Caspers

Full Text Available Functional neuroimaging studies of decision-making so far mainly focused on decisions under uncertainty or negotiation with other persons. Dual process theory assumes that, in such situations, decision making relies on either a rapid intuitive, automated or a slower rational processing system. However, it still remains elusive how personality factors or professional requirements might modulate the decision process and the underlying neural mechanisms. Since decision making is a key task of managers, we hypothesized that managers, facing higher pressure for frequent and rapid decisions than non-managers, prefer the heuristic, automated decision strategy in contrast to non-managers. Such different strategies may, in turn, rely on different neural systems. We tested managers and non-managers in a functional magnetic resonance imaging study using a forced-choice paradigm on word-pairs. Managers showed subcortical activation in the head of the caudate nucleus, and reduced hemodynamic response within the cortex. In contrast, non-managers revealed the opposite pattern. With the head of the caudate nucleus being an initiating component for process automation, these results supported the initial hypothesis, hinting at automation during decisions in managers. More generally, the findings reveal how different professional requirements might modulate cognitive decision processing.

Pipeline for Tracking Neural Progenitor Cells

DEFF Research Database (Denmark)

Vestergaard, Jacob Schack; Dahl, Anders Lindbjerg; Holm, Peter

2012-01-01

Automated methods for neural stem cell lineage construction become increasingly important due to the large amount of data produced from time lapse imagery of in vitro cell growth experiments. Segmentation algorithms with the ability to adapt to the problem at hand and robust tracking methods play...... a key role in constructing these lineages. We present here a tracking pipeline based on learning a dictionary of discriminative image patches for segmentation and a graph formulation of the cell matching problem incorporating topology changes and acknowledging the fact that segmentation errors do occur...

Rapid blockade of telomerase activity and tumor cell growth by the DPL lipofection of ribbon antisense to hTR.

Science.gov (United States)

Bajpai, Arun K; Park, Jeong-Hoh; Moon, Ik-Jae; Kang, Hyungu; Lee, Yun-Han; Doh, Kyung-Oh; Suh, Seong-Il; Chang, Byeong-Churl; Park, Jong-Gu

2005-09-29

Ribbon antisense (RiAS) to the hTR RNA, a component of the telomerase complex, was employed to inhibit telomerase activity and cancer cell growth. The antisense molecule, hTR-RiAS, combined with enhanced cellular uptake was shown to effectively inhibit telomerase activity and cause rapid cell death in various cancer cell lines. When cancer cells were treated with hTR-RiAS, the level of hTR RNA was reduced by more than 90% accompanied with reduction in telomerase activity. When checked for cancer cell viability, cancer cell lines treated with hTR-RiAS using DNA+Peptide+Lipid complex showed 70-80% growth inhibition in 3 days. The reduced cell viability was due to apoptosis as the percentage of cells exhibiting the sub-G0 arrest and DNA fragmentation increased after antisense treatment. Further, when subcutaneous tumors of a colon cancer cell line (SW480) were treated intratumorally with hTR-RiAS, tumor growth was markedly suppressed with almost total ablation of hTR RNA in the tumor tissue. Cells in the tumor tissue were also found to undergo apoptosis after hTR-RiAS treatment. These results suggest that hTR-RiAS is an effective anticancer reagent, with a potential for broad efficacy to diverse malignant tumors.

Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

Science.gov (United States)

Patrick, M. Clinton; Thaler, Stephen L.; Stevenson-Chavis, Katherine

2006-01-01

Neural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.

Growth dynamics of Australia's polar dinosaurs.

Science.gov (United States)

Woodward, Holly N; Rich, Thomas H; Chinsamy, Anusuya; Vickers-Rich, Patricia

2011-01-01

Analysis of bone microstructure in ornithopod and theropod dinosaurs from Victoria, Australia, documents ontogenetic changes, providing insight into the dinosaurs' successful habitation of Cretaceous Antarctic environments. Woven-fibered bone tissue in the smallest specimens indicates rapid growth rates during early ontogeny. Later ontogeny is marked by parallel-fibered tissue, suggesting reduced growth rates approaching skeletal maturity. Bone microstructure similarities between the ornithopods and theropods, including the presence of LAGs in each group, suggest there is no osteohistologic evidence supporting the hypothesis that polar theropods hibernated seasonally. Results instead suggest high-latitude dinosaurs had growth trajectories similar to their lower-latitude relatives and thus, rapid early ontogenetic growth and the cyclical suspensions of growth inherent in the theropod and ornithopod lineages enabled them to successfully exploit polar regions.

Dynamic methylation and expression of Oct4 in early neural stem cells.

Science.gov (United States)

Lee, Shih-Han; Jeyapalan, Jennie N; Appleby, Vanessa; Mohamed Noor, Dzul Azri; Sottile, Virginie; Scotting, Paul J

2010-09-01

Neural stem cells are a multipotent population of tissue-specific stem cells with a broad but limited differentiation potential. However, recent studies have shown that over-expression of the pluripotency gene, Oct4, alone is sufficient to initiate a process by which these can form 'induced pluripotent stem cells' (iPS cells) with the same broad potential as embryonic stem cells. This led us to examine the expression of Oct4 in endogenous neural stem cells, as data regarding its expression in neural stem cells in vivo are contradictory and incomplete. In this study we have therefore analysed the expression of Oct4 and other genes associated with pluripotency throughout development of the mouse CNS and in neural stem cells grown in vitro. We find that Oct4 is still expressed in the CNS by E8.5, but that this expression declines rapidly until it is undetectable by E15.5. This decline is coincident with the gradual methylation of the Oct4 promoter and proximal enhancer. Immunostaining suggests that the Oct4 protein is predominantly cytoplasmic in location. We also found that neural stem cells from all ages expressed the pluripotency associated genes, Sox2, c-Myc, Klf4 and Nanog. These data provide an explanation for the varying behaviour of cells from the early neuroepithelium at different stages of development. The expression of these genes also provides an indication of why Oct4 alone is sufficient to induce iPS formation in neural stem cells at later stages.

Early life stress accelerates behavioral and neural maturation of the hippocampus in male mice.

Science.gov (United States)

Bath, K; Manzano-Nieves, G; Goodwill, H

2016-06-01

Early life stress (ELS) increases the risk for later cognitive and emotional dysfunction. ELS is known to truncate neural development through effects on suppressing cell birth, increasing cell death, and altering neuronal morphology, effects that have been associated with behavioral profiles indicative of precocious maturation. However, how earlier silencing of growth drives accelerated behavioral maturation has remained puzzling. Here, we test the novel hypothesis that, ELS drives a switch from growth to maturation to accelerate neural and behavioral development. To test this, we used a mouse model of ELS, fragmented maternal care, and a cross-sectional dense sampling approach focusing on hippocampus and measured effects of ELS on the ontogeny of behavioral development and biomarkers of neural maturation. Consistent with previous work, ELS was associated with an earlier developmental decline in expression of markers of cell proliferation (Ki-67) and differentiation (doublecortin). However, ELS also led to a precocious arrival of Parvalbumin-positive cells, led to an earlier switch in NMDA receptor subunit expression (marker of synaptic maturity), and was associated with an earlier rise in myelin basic protein expression (key component of the myelin sheath). In addition, in a contextual fear-conditioning task, ELS accelerated the timed developmental suppression of contextual fear. Together, these data provide support for the hypothesis that ELS serves to switch neurodevelopment from processes of growth to maturation and promotes accelerated development of some forms of emotional learning. Copyright © 2016 Elsevier Inc. All rights reserved.

ATHENS SEASONAL VARIATION OF GROUND RESISTANCE PREDICTION USING NEURAL NETWORKS

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S. Anbazhagan

2015-10-01

Full Text Available The objective in ground resistance is to attain the most minimal ground safety esteem conceivable that bodes well monetarily and physically. An application of artificial neural networks (ANN to presage and relegation has been growing rapidly due to sundry unique characteristics of ANN models. A decent forecast is able to capture the dubiousness associated with those ground resistance. A portion of the key instabilities are soil composition, moisture content, temperature, ground electrodes and spacing of the electrodes. Propelled by this need, this paper endeavors to develop a generalized regression neural network (GRNN to predict the ground resistance. The GRNN has a single design parameter and expeditious learning and efficacious modeling for nonlinear time series. The precision of the forecast is applied to the Athens seasonal variation of ground resistance that shows the efficacy of the proposed approach.

Alteration in neonatal nutrition causes perturbations in hypothalamic neural circuits controlling reproductive function.

Science.gov (United States)

Caron, Emilie; Ciofi, Philippe; Prevot, Vincent; Bouret, Sebastien G

2012-08-15

It is increasingly accepted that alterations of the early life environment may have lasting impacts on physiological functions. In particular, epidemiological and animal studies have indicated that changes in growth and nutrition during childhood and adolescence can impair reproductive function. However, the precise biological mechanisms that underlie these programming effects of neonatal nutrition on reproduction are still poorly understood. Here, we used a mouse model of divergent litter size to investigate the effects of early postnatal overnutrition and undernutrition on the maturation of hypothalamic circuits involved in reproductive function. Neonatally undernourished females display attenuated postnatal growth associated with delayed puberty and defective development of axonal projections from the arcuate nucleus to the preoptic region. These alterations persist into adulthood and specifically affect the organization of neural projections containing kisspeptin, a key neuropeptide involved in pubertal activation and fertility. Neonatal overfeeding also perturbs the development of neural projections from the arcuate nucleus to the preoptic region, but it does not result in alterations in kisspeptin projections. These studies indicate that alterations in the early nutritional environment cause lasting and deleterious effects on the organization of neural circuits involved in the control of reproduction, and that these changes are associated with lifelong functional perturbations.

Three-Dimensional-Bioprinted Dopamine-Based Matrix for Promoting Neural Regeneration.

Science.gov (United States)

Zhou, Xuan; Cui, Haitao; Nowicki, Margaret; Miao, Shida; Lee, Se-Jun; Masood, Fahed; Harris, Brent T; Zhang, Lijie Grace

2018-03-14

Central nerve repair and regeneration remain challenging problems worldwide, largely because of the extremely weak inherent regenerative capacity and accompanying fibrosis of native nerves. Inadequate solutions to the unmet needs for clinical therapeutics encourage the development of novel strategies to promote nerve regeneration. Recently, 3D bioprinting techniques, as one of a set of valuable tissue engineering technologies, have shown great promise toward fabricating complex and customizable artificial tissue scaffolds. Gelatin methacrylate (GelMA) possesses excellent biocompatible and biodegradable properties because it contains many arginine-glycine-aspartic acids (RGD) and matrix metalloproteinase sequences. Dopamine (DA), as an essential neurotransmitter, has proven effective in regulating neuronal development and enhancing neurite outgrowth. In this study, GelMA-DA neural scaffolds with hierarchical structures were 3D-fabricated using our custom-designed stereolithography-based printer. DA was functionalized on GelMA to synthesize a biocompatible printable ink (GelMA-DA) for improving neural differentiation. Additionally, neural stem cells (NSCs) were employed as the primary cell source for these scaffolds because of their ability to terminally differentiate into a variety of cell types including neurons, astrocytes, and oligodendrocytes. The resultant GelMA-DA scaffolds exhibited a highly porous and interconnected 3D environment, which is favorable for supporting NSC growth. Confocal microscopy analysis of neural differentiation demonstrated that a distinct neural network was formed on the GelMA-DA scaffolds. In particular, the most significant improvements were the enhanced neuron gene expression of TUJ1 and MAP2. Overall, our results demonstrated that 3D-printed customizable GelMA-DA scaffolds have a positive role in promoting neural differentiation, which is promising for advancing nerve repair and regeneration in the future.

Hybrid energy system evaluation in water supply system energy production: neural network approach

Energy Technology Data Exchange (ETDEWEB)

Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

2010-07-01

Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

Evolvable Neural Software System

Science.gov (United States)

Curtis, Steven A.

2009-01-01

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Three neural network based sensor systems for environmental monitoring

International Nuclear Information System (INIS)

Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

1994-05-01

Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

Science.gov (United States)

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Prenatal Nicotine Exposure Disrupts Infant Neural Markers of Orienting.

Science.gov (United States)

King, Erin; Campbell, Alana; Belger, Aysenil; Grewen, Karen

2017-08-17

Prenatal nicotine exposure (PNE) from maternal cigarette-smoking is linked to developmental deficits, including impaired auditory processing, language, generalized intelligence, attention and sleep. Fetal brain undergoes massive growth, organization and connectivity during gestation, making it particularly vulnerable to neurotoxic insult. Nicotine binds to nicotinic acetylcholine receptors, which are extensively involved in growth, connectivity and function of developing neural circuitry and neurotransmitter systems. Thus, PNE may have long-term impact on neurobehavioral development. The purpose of this study was to compare the auditory K-complex, an event-related potential reflective of auditory gating, sleep preservation and memory consolidation during sleep, in infants with and without PNE and to relate these neural correlates to neurobehavioral development. We compared brain responses to an auditory paired-click paradigm in 3 to 5-month-old infants during Stage 2 sleep, when the K-complex is best observed. We measured component amplitude and delta activity during the K-complex. PNE may impair auditory sensory gating, which may contribute to disrupted sleep and to reduced auditory discrimination and learning, attention re-orienting and/or arousal during wakefulness reported in other studies. Links between PNE and reduced K-complex amplitude and delta power may represent altered cholinergic and GABAergic synaptic programming, and possibly reflect early neural bases for PNE-linked disruptions in sleep quality and auditory processing. These may pose significant disadvantage for language acquisition, attention, and social interaction necessary for academic and social success. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Neural stem cell sex dimorphism in aromatase (CYP19 expression: a basis for differential neural fate

Directory of Open Access Journals (Sweden)

Jay Waldron

2010-11-01

Full Text Available Jay Waldron1, Althea McCourty1, Laurent Lecanu1,21The Research Institute of the McGill University Health Centre, Montreal, Canada; 2Department of Medicine, McGill University, Quebec, CanadaPurpose: Neural stem cell (NSC transplantation and pharmacologic activation of endogenous neurogenesis are two approaches that trigger a great deal of interest as brain repair strategies. However, the success rate of clinical attempts using stem cells to restore neurologic functions altered either after traumatic brain injury or as a consequence of neurodegenerative disease remains rather disappointing. This suggests that factors affecting the fate of grafted NSCs are largely understudied and remain to be characterized. We recently reported that aging differentially affects the neurogenic properties of male and female NSCs. Although the sex steroids androgens and estrogens participate in the regulation of neurogenesis, to our knowledge, research on how gender-based differences affect the capacity of NSCs to differentiate and condition their neural fate is lacking. In the present study, we explored further the role of cell sex as a determining factor of the neural fate followed by differentiating NSCs and its relationship with a potential differential expression of aromatase (CYP19, the testosterone-metabolizing enzyme.Results: Using NSCs isolated from the subventricular zone of three-month-old male and female Long-Evans rats and maintained as neurospheres, we showed that differentiation triggered by retinoic acid resulted in a neural phenotype that depends on cell sex. Differentiated male NSCs mainly expressed markers of neuronal fate, including ßIII-tubulin, microtubule associated protein 2, growth-associated protein 43, and doublecortin. In contrast, female NSCs essentially expressed the astrocyte marker glial fibrillary acidic protein. Quantification of the expression of aromatase showed a very low level of expression in undifferentiated female NSCs

Incorporating rapid neocortical learning of new schema-consistent information into complementary learning systems theory.

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McClelland, James L

2013-11-01

The complementary learning systems theory of the roles of hippocampus and neocortex (McClelland, McNaughton, & O'Reilly, 1995) holds that the rapid integration of arbitrary new information into neocortical structures is avoided to prevent catastrophic interference with structured knowledge representations stored in synaptic connections among neocortical neurons. Recent studies (Tse et al., 2007, 2011) showed that neocortical circuits can rapidly acquire new associations that are consistent with prior knowledge. The findings challenge the complementary learning systems theory as previously presented. However, new simulations extending those reported in McClelland et al. (1995) show that new information that is consistent with knowledge previously acquired by a putatively cortexlike artificial neural network can be learned rapidly and without interfering with existing knowledge; it is when inconsistent new knowledge is acquired quickly that catastrophic interference ensues. Several important features of the findings of Tse et al. (2007, 2011) are captured in these simulations, indicating that the neural network model used in McClelland et al. has characteristics in common with neocortical learning mechanisms. An additional simulation generalizes beyond the network model previously used, showing how the rate of change of cortical connections can depend on prior knowledge in an arguably more biologically plausible network architecture. In sum, the findings of Tse et al. are fully consistent with the idea that hippocampus and neocortex are complementary learning systems. Taken together, these findings and the simulations reported here advance our knowledge by bringing out the role of consistency of new experience with existing knowledge and demonstrating that the rate of change of connections in real and artificial neural networks can be strongly prior-knowledge dependent. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Growth dynamics of Australia's polar dinosaurs.

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Holly N Woodward

Full Text Available Analysis of bone microstructure in ornithopod and theropod dinosaurs from Victoria, Australia, documents ontogenetic changes, providing insight into the dinosaurs' successful habitation of Cretaceous Antarctic environments. Woven-fibered bone tissue in the smallest specimens indicates rapid growth rates during early ontogeny. Later ontogeny is marked by parallel-fibered tissue, suggesting reduced growth rates approaching skeletal maturity. Bone microstructure similarities between the ornithopods and theropods, including the presence of LAGs in each group, suggest there is no osteohistologic evidence supporting the hypothesis that polar theropods hibernated seasonally. Results instead suggest high-latitude dinosaurs had growth trajectories similar to their lower-latitude relatives and thus, rapid early ontogenetic growth and the cyclical suspensions of growth inherent in the theropod and ornithopod lineages enabled them to successfully exploit polar regions.

Chaotic diagonal recurrent neural network

International Nuclear Information System (INIS)

Wang Xing-Yuan; Zhang Yi

2012-01-01

We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

Computational modeling of neural plasticity for self-organization of neural networks.

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Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Effect of short-term escitalopram treatment on neural activation during emotional processing.

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Maron, Eduard; Wall, Matt; Norbury, Ray; Godlewska, Beata; Terbeck, Sylvia; Cowen, Philip; Matthews, Paul; Nutt, David J

2016-01-01

Recent functional magnetic resonance (fMRI) imaging studies have revealed that subchronic medication with escitalopram leads to significant reduction in both amygdala and medial frontal gyrus reactivity during processing of emotional faces, suggesting that escitalopram may have a distinguishable modulatory effect on neural activation as compared with other serotonin-selective antidepressants. In this fMRI study we aimed to explore whether short-term medication with escitalopram in healthy volunteers is associated with reduced neural response to emotional processing, and whether this effect is predicted by drug plasma concentration. The neural response to fearful and happy faces was measured before and on day 7 of treatment with escitalopram (10mg) in 15 healthy volunteers and compared with those in a control unmedicated group (n=14). Significantly reduced activation to fearful, but not to happy facial expressions was observed in the bilateral amygdala, cingulate and right medial frontal gyrus following escitalopram medication. This effect was not correlated with plasma drug concentration. In accordance with previous data, we showed that escitalopram exerts its rapid direct effect on emotional processing via attenuation of neural activation in pathways involving medial frontal gyrus and amygdala, an effect that seems to be distinguishable from that of other SSRIs. © The Author(s) 2015.

Maximum entropy methods for extracting the learned features of deep neural networks.

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Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

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Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

2017-02-01

It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

A neural network technique for remeshing of bone microstructure.

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Fischer, Anath; Holdstein, Yaron

2012-01-01

Today, there is major interest within the biomedical community in developing accurate noninvasive means for the evaluation of bone microstructure and bone quality. Recent improvements in 3D imaging technology, among them development of micro-CT and micro-MRI scanners, allow in-vivo 3D high-resolution scanning and reconstruction of large specimens or even whole bone models. Thus, the tendency today is to evaluate bone features using 3D assessment techniques rather than traditional 2D methods. For this purpose, high-quality meshing methods are required. However, the 3D meshes produced from current commercial systems usually are of low quality with respect to analysis and rapid prototyping. 3D model reconstruction of bone is difficult due to the complexity of bone microstructure. The small bone features lead to a great deal of neighborhood ambiguity near each vertex. The relatively new neural network method for mesh reconstruction has the potential to create or remesh 3D models accurately and quickly. A neural network (NN), which resembles an artificial intelligence (AI) algorithm, is a set of interconnected neurons, where each neuron is capable of making an autonomous arithmetic calculation. Moreover, each neuron is affected by its surrounding neurons through the structure of the network. This paper proposes an extension of the growing neural gas (GNN) neural network technique for remeshing a triangular manifold mesh that represents bone microstructure. This method has the advantage of reconstructing the surface of a genus-n freeform object without a priori knowledge regarding the original object, its topology, or its shape.

Continuity and change in children's longitudinal neural responses to numbers.

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Emerson, Robert W; Cantlon, Jessica F

2015-03-01

Human children possess the ability to approximate numerical quantity nonverbally from a young age. Over the course of early childhood, children develop increasingly precise representations of numerical values, including a symbolic number system that allows them to conceive of numerical information as Arabic numerals or number words. Functional brain imaging studies of adults report that activity in bilateral regions of the intraparietal sulcus (IPS) represents a key neural correlate of numerical cognition. Developmental neuroimaging studies indicate that the right IPS develops its number-related neural response profile more rapidly than the left IPS during early childhood. One prediction that can be derived from previous findings is that there is longitudinal continuity in the number-related neural responses of the right IPS over development while the development of the left IPS depends on the acquisition of numerical skills. We tested this hypothesis using fMRI in a longitudinal design with children ages 4 to 9. We found that neural responses in the right IPS are correlated over a 1-2-year period in young children whereas left IPS responses change systematically as a function of children's numerical discrimination acuity. The data are consistent with the hypothesis that functional properties of the right IPS in numerical processing are stable over early childhood whereas the functions of the left IPS are dynamically modulated by the development of numerical skills. © 2014 John Wiley & Sons Ltd.

Briefly Cuing Memories Leads to Suppression of Their Neural Representations

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Norman, Kenneth A.

2014-01-01

Previous studies have linked partial memory activation with impaired subsequent memory retrieval (e.g., Detre et al., 2013) but have not provided an account of this phenomenon at the level of memory representations: How does partial activation change the neural pattern subsequently elicited when the memory is cued? To address this question, we conducted a functional magnetic resonance imaging (fMRI) experiment in which participants studied word-scene paired associates. Later, we weakly reactivated some memories by briefly presenting the cue word during a rapid serial visual presentation (RSVP) task; other memories were more strongly reactivated or not reactivated at all. We tested participants' memory for the paired associates before and after RSVP. Cues that were briefly presented during RSVP triggered reduced levels of scene activity on the post-RSVP memory test, relative to the other conditions. We used pattern similarity analysis to assess how representations changed as a function of the RSVP manipulation. For briefly cued pairs, we found that neural patterns elicited by the same cue on the pre- and post-RSVP tests (preA–postA; preB–postB) were less similar than neural patterns elicited by different cues (preA–postB; preB–postA). These similarity reductions were predicted by neural measures of memory activation during RSVP. Through simulation, we show that our pattern similarity results are consistent with a model in which partial memory activation triggers selective weakening of the strongest parts of the memory. PMID:24899722

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

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Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

GH mediates exercise-dependent activation of SVZ neural precursor cells in aged mice.

Directory of Open Access Journals (Sweden)

Daniel G Blackmore

Full Text Available Here we demonstrate, both in vivo and in vitro, that growth hormone (GH mediates precursor cell activation in the subventricular zone (SVZ of the aged (12-month-old brain following exercise, and that GH signaling stimulates precursor activation to a similar extent to exercise. Our results reveal that both addition of GH in culture and direct intracerebroventricular infusion of GH stimulate neural precursor cells in the aged brain. In contrast, no increase in neurosphere numbers was observed in GH receptor null animals following exercise. Continuous infusion of a GH antagonist into the lateral ventricle of wild-type animals completely abolished the exercise-induced increase in neural precursor cell number. Given that the aged brain does not recover well after injury, we investigated the direct effect of exercise and GH on neural precursor cell activation following irradiation. This revealed that physical exercise as well as infusion of GH promoted repopulation of neural precursor cells in irradiated aged animals. Conversely, infusion of a GH antagonist during exercise prevented recovery of precursor cells in the SVZ following irradiation.

GH Mediates Exercise-Dependent Activation of SVZ Neural Precursor Cells in Aged Mice

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Blackmore, Daniel G.; Vukovic, Jana; Waters, Michael J.; Bartlett, Perry F.

2012-01-01

Here we demonstrate, both in vivo and in vitro, that growth hormone (GH) mediates precursor cell activation in the subventricular zone (SVZ) of the aged (12-month-old) brain following exercise, and that GH signaling stimulates precursor activation to a similar extent to exercise. Our results reveal that both addition of GH in culture and direct intracerebroventricular infusion of GH stimulate neural precursor cells in the aged brain. In contrast, no increase in neurosphere numbers was observed in GH receptor null animals following exercise. Continuous infusion of a GH antagonist into the lateral ventricle of wild-type animals completely abolished the exercise-induced increase in neural precursor cell number. Given that the aged brain does not recover well after injury, we investigated the direct effect of exercise and GH on neural precursor cell activation following irradiation. This revealed that physical exercise as well as infusion of GH promoted repopulation of neural precursor cells in irradiated aged animals. Conversely, infusion of a GH antagonist during exercise prevented recovery of precursor cells in the SVZ following irradiation. PMID:23209615

Does Rapid and Sustained Economic Growth Lead to Convergence in Health Resources: The Case of China From 1980 to 2010.

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Liang, Di; Zhang, Donglan; Huang, Jiayan; Schweitzer, Stuart

2016-01-01

China's rapid and sustained economic growth offers an opportunity to ask whether the advantages of growth diffuse throughout an economy, or remain localized in areas where the growth has been the greatest. A critical policy area in China has been the health system, and health inequality has become an issue that has led the government to broaden national health insurance programs. This study investigates whether health system resources and performance have converged over the past 30 years across China's 31 provinces. To examine geographic variation of health system resources and performance at the provincial level, we measure the degree of sigma convergence and beta convergence in indicators of health system resources (structure), health services utilization (process), and outcome. All data are from officially published sources: the China Health Statistics Year Book and the China Statistics Year Book. Sigma convergence is found for resource indicators, whereas it is not observed for either process or outcome indicators, indicating that disparities only narrowed in health system resources. Beta convergence is found in most indicators, except for 2 procedure indicators, reflecting that provinces with poorer resources were catching up. Convergence found in this study probably reflects the mixed outcome of government input, and market forces. Thus, left alone, the equitable distribution of health care resources may not occur naturally during a period of economic growth. Governmental and societal efforts are needed to reduce geographic health variation and promote health equity. © The Author(s) 2016.

Ethylene production throughout growth and development of plants

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Wheeler, Raymond M.; Peterson, Barbara V.; Stutte, Gary W.

2004-01-01

Ethylene production by 10 or 20 m2 stands of wheat, soybean, lettuce, potato, and tomato was monitored throughout growth and development in an atmospherically closed plant chamber. Chamber ethylene levels varied among species and rose during periods of canopy expansion and rapid growth for all species. Following this, ethylene levels either declined during seed fill and maturation for wheat and soybean, or remained relatively constant for potato and tomato (during flowering and early fruit development). Lettuce plants were harvested during rapid growth and peak ethylene production. Chamber ethylene levels increased rapidly during tomato ripening, reaching concentrations about 10 times that measured during vegetative growth. The highest ethylene production rates during vegetative growth ranged from 1.6 to 2.5 nmol m-2 d-1 during rapid growth of lettuce and wheat stands, or about 0.3 to 0.5 nmol g-1 fresh weight per hour. Estimates of stand ethylene production during tomato ripening showed that rates reached 43 nmol m-2 d-1 in one study and 93 nmol m-2 d-1 in a second study with higher lighting, or about 50x that of the rate during vegetative growth of tomato. In a related test with potato, the photoperiod was extended from 12 to 24 hours (continuous light) at 58 days after planting (to increase tuber yield), but this change in the environment caused a sharp increase in ethylene production from the basal rate of 0.4 to 6.2 nmol m-2 d-1. Following this, the photoperiod was changed back to 12 h at 61 days and ethylene levels decreased. The results suggest three separate categories of ethylene production were observed with whole stands of plants: 1) production during rapid vegetative growth, 2) production during climacteric fruit ripening, and 3) production from environmental stress.

The neural cell adhesion molecule-derived peptide, FGL, attenuates lipopolysaccharide-induced changes in glia in a CD200-dependent manner

DEFF Research Database (Denmark)

Cox, F F; Berezin, V; Bock, E

2013-01-01

Fibroblast growth loop (FGL) is a neural cell adhesion molecule (NCAM)-mimetic peptide that mimics the interaction of NCAM with fibroblast growth factor receptor (FGFR). FGL increases neurite outgrowth and promotes neuronal survival in vitro, and it has also been shown to have neuroprotective eff...

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

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Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

The neural response properties and cortical organization of a rapidly adapting muscle sensory group response that overlaps with the frequencies that elicit the kinesthetic illusion.

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Marasco, Paul D; Bourbeau, Dennis J; Shell, Courtney E; Granja-Vazquez, Rafael; Ina, Jason G

2017-01-01

Kinesthesia is the sense of limb movement. It is fundamental to efficient motor control, yet its neurophysiological components remain poorly understood. The contributions of primary muscle spindles and cutaneous afferents to the kinesthetic sense have been well studied; however, potential contributions from muscle sensory group responses that are different than the muscle spindles have not been ruled out. Electrophysiological recordings in peripheral nerves and brains of male Sprague Dawley rats with a degloved forelimb preparation provide evidence of a rapidly adapting muscle sensory group response that overlaps with vibratory inputs known to generate illusionary perceptions of limb movement in humans (kinesthetic illusion). This group was characteristically distinct from type Ia muscle spindle fibers, the receptor historically attributed to limb movement sensation, suggesting that type Ia muscle spindle fibers may not be the sole carrier of kinesthetic information. The sensory-neural structure of muscles is complex and there are a number of possible sources for this response group; with Golgi tendon organs being the most likely candidate. The rapidly adapting muscle sensory group response projected to proprioceptive brain regions, the rodent homolog of cortical area 3a and the second somatosensory area (S2), with similar adaption and frequency response profiles between the brain and peripheral nerves. Their representational organization was muscle-specific (myocentric) and magnified for proximal and multi-articulate limb joints. Projection to proprioceptive brain areas, myocentric representational magnification of muscles prone to movement error, overlap with illusionary vibrational input, and resonant frequencies of volitional motor unit contraction suggest that this group response may be involved with limb movement processing.

Periodicity and global exponential stability of generalized Cohen-Grossberg neural networks with discontinuous activations and mixed delays.

Science.gov (United States)

Wang, Dongshu; Huang, Lihong

2014-03-01

In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen-Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results. Copyright © 2013 Elsevier Ltd. All rights reserved.

EDITORIAL: Special issue on optical neural engineering: advances in optical stimulation technology Special issue on optical neural engineering: advances in optical stimulation technology

Science.gov (United States)

Shoham, Shy; Deisseroth, Karl

2010-08-01

a single spine, with two-photon uncaging) and in rapid, flexible spatial-temporal patterns [10-14]. Nevertheless, current technology generally requires damaging doses of UV or violet illumination and the continuous re-introduction of the caged compound, which, despite interest, makes for a difficult transition beyond in vitro preparations. Thus, the tremendous progress in the in vivo application of photo-stimulation tools over the past five years has been largely facilitated by two 'exciting' new photo-stimulation technologies: photo-biological stimulation of a rapidly increasing arsenal of light-sensitive ion channels and pumps ('optogenetic' probes[15-18]) and direct photo-thermal stimulation of neural tissue with an IR laser [19-21]. The Journal of Neural Engineering has dedicated a special section in this issue to highlight advances in optical stimulation technology, which includes original peer-reviewed contributions dealing with the design of modern optical systems for spatial-temporal control of optical excitation patterns and with the biophysics of neural-thermal interaction mediated by electromagnetic waves. The paper by Nikolenko, Peterka and Yuste [22] presents a compact design of a microscope-photo-stimulator based on a transmissive phase-modulating spatial-light modulator (SLM). Computer-generated holographic photo-stimulation using SLMs [12-14, 23] allows the efficient parallel projection of intense sparse patterns of light, and the welcome development of compact, user-friendly systems will likely reduce the barrier to its widespread adoption. The paper by Losavio et al [24] presents the design and functional characteristics of their acousto-optical deflector (AOD) systems for studying spatial-temporal dendritic integration in single neurons in vitro. Both single-photon (UV) and two-photon (femtosecond pulsed IR) AOD uncaging systems are described in detail. The paper presents an excellent overview of the current state of the art and limitations of

Neural chips, neural computers and application in high and superhigh energy physics experiments

International Nuclear Information System (INIS)

Nikityuk, N.M.; )

2001-01-01

Architecture peculiarity and characteristics of series of neural chips and neural computes used in scientific instruments are considered. Tendency of development and use of them in high energy and superhigh energy physics experiments are described. Comparative data which characterize the efficient use of neural chips for useful event selection, classification elementary particles, reconstruction of tracks of charged particles and for search of hypothesis Higgs particles are given. The characteristics of native neural chips and accelerated neural boards are considered [ru

Augmented cognition tool for rapid military decision making.

Energy Technology Data Exchange (ETDEWEB)

Taylor, Shawn Ellis; Bernard, Michael Lewis; Verzi, Stephen J.; Dubicka, Irene; Vineyard, Craig Michael

2011-10-01

This report describes the laboratory directed research and development work to model relevant areas of the brain that associate multi-modal information for long-term storage for the purpose of creating a more effective, and more automated, association mechanism to support rapid decision making. Using the biology and functionality of the hippocampus as an analogy or inspiration, we have developed an artificial neural network architecture to associate k-tuples (paired associates) of multimodal input records. The architecture is composed of coupled unimodal self-organizing neural modules that learn generalizations of unimodal components of the input record. Cross modal associations, stored as a higher-order tensor, are learned incrementally as these generalizations form. Graph algorithms are then applied to the tensor to extract multi-modal association networks formed during learning. Doing so yields a novel approach to data mining for knowledge discovery. This report describes the neurobiological inspiration, architecture, and operational characteristics of our model, and also provides a real world terrorist network example to illustrate the model's functionality.

Molecular beam epitaxy growth of In0.52Al0.48As/In0.53Ga0.47As metamorphic high electron mobility transistor employing growth interruption and in situ rapid thermal annealing

International Nuclear Information System (INIS)

Ihn, Soo-Ghang; Jo, Seong June; Song, Jong-In

2006-01-01

We investigated the effects of high temperature (∼700 deg. C) in situ rapid thermal annealing (RTA) carried out during growth interruption between spacer and δ-doping layers of an In 0.52 Al 0.48 As/In 0.53 Ga 0.47 As metamorphic high electron mobility transistor (MHEMT) grown on a compositionally graded InGaAlAs buffer layer. The in situ RTA improved optical and structural properties of the MHEMT without degradation of transport property, while postgrowth RTA improved the structural property of the MHEMT but significantly degraded mobility due to the defect-assisted Si diffusion. The results indicate the potential of the in situ RTA for use in the growth of high-quality metamorphic epitaxial layers for optoelectronic applications requiring improved optical and electrical properties

Enhancement of neurite outgrowth in neuron cancer stem cells by growth on 3-D collagen scaffolds

Energy Technology Data Exchange (ETDEWEB)

Chen, Chih-Hao [Department of Electrical Engineering, I-Shou University, Taiwan, ROC (China); Neurosurgery, Department of Surgery, Kaohsiung Veterans General Hospital, Taiwan, ROC (China); Department of Biomedical Engineering, I-Shou University, Taiwan, ROC (China); Kuo, Shyh Ming [Department of Biomedical Engineering, I-Shou University, Taiwan, ROC (China); Liu, Guei-Sheung [Centre for Eye Research Australia, University of Melbourne (Australia); Chen, Wan-Nan U. [Department of Biological Science and Technology, I-Shou University, Taiwan, ROC (China); Chuang, Chin-Wen [Department of Electrical Engineering, I-Shou University, Taiwan, ROC (China); Liu, Li-Feng, E-mail: liulf@isu.edu.tw [Department of Biological Science and Technology, I-Shou University, Taiwan, ROC (China)

2012-11-09

Highlights: Black-Right-Pointing-Pointer Neuron cancer stem cells (NCSCs) behave high multiply of growth on collagen scaffold. Black-Right-Pointing-Pointer Enhancement of NCSCs neurite outgrowth on porous collagen scaffold. Black-Right-Pointing-Pointer 3-D collagen culture of NCSCs shows an advance differentiation than 2-D culture. -- Abstract: Collagen is one component of the extracellular matrix that has been widely used for constructive remodeling to facilitate cell growth and differentiation. The 3-D distribution and growth of cells within the porous scaffold suggest a clinical significance for nerve tissue engineering. In the current study, we investigated proliferation and differentiation of neuron cancer stem cells (NCSCs) on a 3-D porous collagen scaffold that mimics the natural extracellular matrix. We first generated green fluorescence protein (GFP) expressing NCSCs using a lentiviral system to instantly monitor the transitions of morphological changes during growth on the 3-D scaffold. We found that proliferation of GFP-NCSCs increased, and a single cell mass rapidly grew with unrestricted expansion between days 3 and 9 in culture. Moreover, immunostaining with neuronal nuclei (NeuN) revealed that NCSCs grown on the 3-D collagen scaffold significantly enhanced neurite outgrowth. Our findings confirmed that the 80 {mu}m porous collagen scaffold could enhance attachment, viability and differentiation of the cancer neural stem cells. This result could provide a new application for nerve tissue engineering and nerve regeneration.

Enhancement of neurite outgrowth in neuron cancer stem cells by growth on 3-D collagen scaffolds

International Nuclear Information System (INIS)

Chen, Chih-Hao; Kuo, Shyh Ming; Liu, Guei-Sheung; Chen, Wan-Nan U.; Chuang, Chin-Wen; Liu, Li-Feng

2012-01-01

Highlights: ► Neuron cancer stem cells (NCSCs) behave high multiply of growth on collagen scaffold. ► Enhancement of NCSCs neurite outgrowth on porous collagen scaffold. ► 3-D collagen culture of NCSCs shows an advance differentiation than 2-D culture. -- Abstract: Collagen is one component of the extracellular matrix that has been widely used for constructive remodeling to facilitate cell growth and differentiation. The 3-D distribution and growth of cells within the porous scaffold suggest a clinical significance for nerve tissue engineering. In the current study, we investigated proliferation and differentiation of neuron cancer stem cells (NCSCs) on a 3-D porous collagen scaffold that mimics the natural extracellular matrix. We first generated green fluorescence protein (GFP) expressing NCSCs using a lentiviral system to instantly monitor the transitions of morphological changes during growth on the 3-D scaffold. We found that proliferation of GFP-NCSCs increased, and a single cell mass rapidly grew with unrestricted expansion between days 3 and 9 in culture. Moreover, immunostaining with neuronal nuclei (NeuN) revealed that NCSCs grown on the 3-D collagen scaffold significantly enhanced neurite outgrowth. Our findings confirmed that the 80 μm porous collagen scaffold could enhance attachment, viability and differentiation of the cancer neural stem cells. This result could provide a new application for nerve tissue engineering and nerve regeneration.

Neural tissue-spheres

DEFF Research Database (Denmark)

Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

2007-01-01

By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Lei Feng

2018-06-01

Full Text Available Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874–1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN, evolutionary neural network (ENN, extreme learning machine (ELM, general regression neural network (GRNN and radial basis neural network (RBNN were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts.

Texture control and growth mechanism of WSe{sub 2} film prepared by rapid selenization of W film

Energy Technology Data Exchange (ETDEWEB)

Li, Hongchao [State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China); Chongyi Zhangyuan Tungsten Industry Corporation Limited, Ganzhou 341300 (China); Gao, Di; Li, Kun; Pang, Mengde; Xie, Senlin [State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China); Liu, Rutie, E-mail: llrrtt@csu.edu.cn [State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China); Zou, Jianpeng [State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China)

2017-02-01

Highlights: • We present a highly efficient method for preparing WSe{sub 2} film by rapid selenization. • The W film phase composition has little effect on WSe{sub 2} film orientation. • W film density is a critical factor that influences the WSe{sub 2} orientation. • A growth model was proposed for two kinds of WSe{sub 2} film textures. - Abstract: The tungsten diselenide (WSe{sub 2}) films with different orientation present unique properties suitable for specific applications, such as WSe{sub 2} with a C-axis⊥substrate for optoelectronics and WSe{sub 2} with a C-axis // substrate for electrocatalysts. Orientation control of WSe{sub 2} is essential for realizing the practical applications. In this letter, a WSe{sub 2} film has been prepared via rapid selenization of a magnetron-sputtered tungsten (W) film. The influence of the magnetron-sputtered W film on WSe{sub 2} film growth was studied systematically. Scanning electron microscopy, X-ray diffractometry and high-resolution transmission electron microscopy were used to evaluate the morphology, microstructure and phase composition of the W and WSe{sub 2} films. The substrate temperature has a significant effect on the W film phase composition, but little effect on the WSe{sub 2} film orientation. The WSe{sub 2} orientation can be controlled by changing the W film microstructure. A dense W film that is deposited at low pressure is conducive to the formation of WSe{sub 2} with a C-axis⊥substrate, whereas a porous W film deposited at high pressure favors the formation of WSe{sub 2} with a C-axis // substrate. A growth model for the WSe{sub 2} film with different texture has been proposed based on the experimental results. The direction of selenium (Se) vapor diffusion differs at the top and side surfaces. This is a key factor for the preparation of anisotropic WSe{sub 2} films. Highly oriented WSe{sub 2} films with a C-axis⊥substrate grow from the dense W film deposited at low pressure because Se vapor

EXPERIMENT BASED FAULT DIAGNOSIS ON BOTTLE FILLING PLANT WITH LVQ ARTIFICIAL NEURAL NETWORK ALGORITHM

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Mustafa DEMETGÜL

2008-01-01

Full Text Available In this study, an artificial neural network is developed to find an error rapidly on pneumatic system. Also the ANN prevents the system versus the failure. The error on the experimental bottle filling plant can be defined without any interference using analog values taken from pressure sensors and linear potentiometers. The sensors and potentiometers are placed on different places of the plant. Neural network diagnosis faults on plant, where no bottle, cap closing cylinder B is not working, bottle cap closing cylinder C is not working, air pressure is not sufficient, water is not filling and low air pressure faults. The fault is diagnosed by artificial neural network with LVQ. It is possible to find an failure by using normal programming or PLC. The reason offing Artificial Neural Network is to give a information where the fault is. However, ANN can be used for different systems. The aim is to find the fault by using ANN simultaneously. In this situation, the error taken place on the pneumatic system is collected by a data acquisition card. It is observed that the algorithm is very capable program for many industrial plants which have mechatronic systems.

Enhanced viability and neural differential potential in poor post-thaw hADSCs by agarose multi-well dishes and spheroid culture.

Science.gov (United States)

Guo, Xiaoling; Li, Shanyi; Ji, Qingshan; Lian, Ruiling; Chen, Jiansu

2015-10-01

Human adipose-derived stem cells (hADSCs) are potential adult stem cells source for cell therapy. But hADSCs with multi-passage or cryopreservation often revealed poor growth performance. The aim of our work was to improve the activity of poor post-thaw hADSCs by simple and effective means. We describe here a simple method based on commercially available silicone micro-wells for creating hADSCs spheroids to improve viability and neural differentiation potential on poor post-thaw hADSCs. The isolated hADSCs positively expresse d CD29, CD44, CD105, and negatively expressed CD34, CD45, HLA-DR by flow cytometry. Meanwhile, they had adipogenic and osteogenic differentiation capacity. The post-thaw and post-spheroid hADSCs from poor growth status hADSCs showed a marked increase in cell proliferation by CKK-8 analysis, cell cycle analysis and Ki67/P27 quantitative polymerase chain reaction (qPCR) analysis. They also displayed an increase viability of anti-apoptosis by annexin v and propidium iodide assays and mitochondrial membrane potential assays. After 3 days of neural induction, the neural differentiation potential of post-thaw and post-spheroid hADSCs could be enhanced by qPCR analysis and western blotting analysis. These results suggested that the spheroid formation could improve the viability and neural differentiation potential of bad growth status hADSCs, which is conducive to ADSCs research and cell therapy.

Pulsed DC Electric Field-Induced Differentiation of Cortical Neural Precursor Cells.

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Hui-Fang Chang

Full Text Available We report the differentiation of neural stem and progenitor cells solely induced by direct current (DC pulses stimulation. Neural stem and progenitor cells in the adult mammalian brain are promising candidates for the development of therapeutic neuroregeneration strategies. The differentiation of neural stem and progenitor cells depends on various in vivo environmental factors, such as nerve growth factor and endogenous EF. In this study, we demonstrated that the morphologic and phenotypic changes of mouse neural stem and progenitor cells (mNPCs could be induced solely by exposure to square-wave DC pulses (magnitude 300 mV/mm at frequency of 100-Hz. The DC pulse stimulation was conducted for 48 h, and the morphologic changes of mNPCs were monitored continuously. The length of primary processes and the amount of branching significantly increased after stimulation by DC pulses for 48 h. After DC pulse treatment, the mNPCs differentiated into neurons, astrocytes, and oligodendrocytes simultaneously in stem cell maintenance medium. Our results suggest that simple DC pulse treatment could control the fate of NPCs. With further studies, DC pulses may be applied to manipulate NPC differentiation and may be used for the development of therapeutic strategies that employ NPCs to treat nervous system disorders.

Pulsed DC Electric Field-Induced Differentiation of Cortical Neural Precursor Cells.

Science.gov (United States)

Chang, Hui-Fang; Lee, Ying-Shan; Tang, Tang K; Cheng, Ji-Yen

2016-01-01

We report the differentiation of neural stem and progenitor cells solely induced by direct current (DC) pulses stimulation. Neural stem and progenitor cells in the adult mammalian brain are promising candidates for the development of therapeutic neuroregeneration strategies. The differentiation of neural stem and progenitor cells depends on various in vivo environmental factors, such as nerve growth factor and endogenous EF. In this study, we demonstrated that the morphologic and phenotypic changes of mouse neural stem and progenitor cells (mNPCs) could be induced solely by exposure to square-wave DC pulses (magnitude 300 mV/mm at frequency of 100-Hz). The DC pulse stimulation was conducted for 48 h, and the morphologic changes of mNPCs were monitored continuously. The length of primary processes and the amount of branching significantly increased after stimulation by DC pulses for 48 h. After DC pulse treatment, the mNPCs differentiated into neurons, astrocytes, and oligodendrocytes simultaneously in stem cell maintenance medium. Our results suggest that simple DC pulse treatment could control the fate of NPCs. With further studies, DC pulses may be applied to manipulate NPC differentiation and may be used for the development of therapeutic strategies that employ NPCs to treat nervous system disorders.

Robust Adaptive Exponential Synchronization of Stochastic Perturbed Chaotic Delayed Neural Networks with Parametric Uncertainties

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Yang Fang

2014-01-01

Full Text Available This paper investigates the robust adaptive exponential synchronization in mean square of stochastic perturbed chaotic delayed neural networks with nonidentical parametric uncertainties. A robust adaptive feedback controller is proposed based on Gronwally’s inequality, drive-response concept, and adaptive feedback control technique with the update laws of nonidentical parametric uncertainties as well as linear matrix inequality (LMI approach. The sufficient conditions for robust adaptive exponential synchronization in mean square of uncoupled uncertain stochastic chaotic delayed neural networks are derived in terms of linear matrix inequalities (LMIs. The effect of nonidentical uncertain parameter uncertainties is suppressed by the designed robust adaptive feedback controller rapidly. A numerical example is provided to validate the effectiveness of the proposed method.

Modeling by artificial neural networks. Application to the management of fuel in a nuclear power plant

International Nuclear Information System (INIS)

Gaudier, F.

1999-01-01

The determination of the family of optimum core loading patterns for Pressurized Water Reactors (PWRs) involves the assessment of the core attributes, such as the power peaking factor for thousands of candidate loading patterns. Despite the rapid advances in computer architecture, the direct calculation of these attributes by a neutronic code needs a lot of of time and memory. With the goal of reducing the calculation time and optimizing the loading pattern, we propose in this thesis a method based on ideas of neural and statistical learning to provide a feed forward neural network capable of calculating the power peaking corresponding to an eighth core PWR. We use statistical methods to deduct judicious inputs (reduction of the input space dimension) and neural methods to train the model (learning capabilities). Indeed, on one hand, a principal component analysis allows us to characterize more efficiently the fuel assemblies (neural model inputs) and the other hand, the introduction of the a priori knowledge allows us to reducing the number of freedom parameters in the neural network. The model was built using a multi layered perceptron trained with the standard back propagation algorithm. We introduced our neural network in the automatic optimization code FORMOSA, and on EDF real problems we showed an important saving in time. Finally, we propose an hybrid method which combining the best characteristics of the linear local approximator GPT (Generalized Perturbation Theory) and the artificial neural network. (author)

Robust recurrent neural network modeling for software fault detection and correction prediction

International Nuclear Information System (INIS)

Hu, Q.P.; Xie, M.; Ng, S.H.; Levitin, G.

2007-01-01

Software fault detection and correction processes are related although different, and they should be studied together. A practical approach is to apply software reliability growth models to model fault detection, and fault correction process is assumed to be a delayed process. On the other hand, the artificial neural networks model, as a data-driven approach, tries to model these two processes together with no assumptions. Specifically, feedforward backpropagation networks have shown their advantages over analytical models in fault number predictions. In this paper, the following approach is explored. First, recurrent neural networks are applied to model these two processes together. Within this framework, a systematic networks configuration approach is developed with genetic algorithm according to the prediction performance. In order to provide robust predictions, an extra factor characterizing the dispersion of prediction repetitions is incorporated into the performance function. Comparisons with feedforward neural networks and analytical models are developed with respect to a real data set

DNA topoisomerase IIβ stimulates neurite outgrowth in neural differentiated human mesenchymal stem cells through regulation of Rho-GTPases (RhoA/Rock2 pathway) and Nurr1 expression.

Science.gov (United States)

Zaim, Merve; Isik, Sevim

2018-04-25

DNA topoisomerase IIβ (topo IIβ) is known to regulate neural differentiation by inducing the neuronal genes responsible for critical neural differentiation events such as neurite outgrowth and axon guidance. However, the pathways of axon growth controlled by topo IIβ have not been clarified yet. Microarray results of our previous study have shown that topo IIβ silencing in neural differentiated primary human mesenchymal stem cells (hMSCs) significantly alters the expression pattern of genes involved in neural polarity, axonal growth, and guidance, including Rho-GTPases. This study aims to further analyze the regulatory role of topo IIβ on the process of axon growth via regulation of Rho-GTPases. For this purpose, topo IIβ was silenced in neurally differentiated hMSCs. Cells lost their morphology because of topo IIβ deficiency, becoming enlarged and flattened. Additionally, a reduction in both neural differentiation efficiency and neurite length, upregulation in RhoA and Rock2, downregulation in Cdc42 gene expression were detected. On the other hand, cells were transfected with topo IIβ gene to elucidate the possible neuroprotective effect of topo IIβ overexpression on neural-induced hMSCs. Topo IIβ overexpression prompted all the cells to exhibit neural cell morphology as characterized by longer neurites. RhoA and Rock2 expressions were downregulated, whereas Cdc42 expression was upregulated. Nurr1 expression level correlated with topo IIβ in both topo IIβ-overexpressed and -silenced cells. Furthermore, differential translocation of Rho-GTPases was detected by immunostaining in response to topo IIβ. Our results suggest that topo IIβ deficiency could give rise to neurodegeneration through dysregulation of Rho-GTPases. However, further in-vivo research is needed to demonstrate if re-regulation of Rho GTPases by topo IIβ overexpression could be a neuroprotective treatment in the case of neurodegenerative diseases.

Transfection of glioma cells with the neural-cell adhesion molecule NCAM

DEFF Research Database (Denmark)

Edvardsen, K; Pedersen, P H; Bjerkvig, R

1994-01-01

The tumor growth and the invasive capacity of a rat glioma cell line (BT4Cn) were studied after transfection with the human transmembrane 140-kDa isoform of the neural-cell adhesion molecule, NCAM. After s.c. injection, the NCAM-transfected cells showed a slower growth rate than the parent cell...... of the injection site, with a sharply demarcated border between the tumor and brain tissue. In contrast, the parental cell line showed single-cell infiltration and more pronounced destruction of normal brain tissue. Using a 51Cr-release assay, spleen cells from rats transplanted with BT4Cn tumor cells generally...

Novel insight into the origin of the growth dynamics of sauropod dinosaurs.

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Ignacio Alejandro Cerda

Full Text Available Sauropod dinosaurs include the largest terrestrial animals and are considered to have uninterrupted rapid rates of growth, which differs from their more basal relatives, which have a slower cyclical growth. Here we examine the bone microstructure of several sauropodomorph dinosaurs, including basal taxa, as well as the more derived sauropods. Although our results agree that the plesiomorphic condition for Sauropodomorpha is cyclical growth dynamics, we found that the hypothesized dichotomy between the growth patterns of basal and more derived sauropodomorphs is not supported. Here, we show that sauropod-like growth dynamics of uninterrupted rapid growth also occurred in some basal sauropodomorphs, and that some basal sauropods retained the plesiomorphic cyclical growth patterns. Among the sauropodomorpha it appears that the basal taxa exploited different growth strategies, but the more derived Eusauropoda successfully utilized rapid, uninterrupted growth strategies.

Novel insight into the origin of the growth dynamics of sauropod dinosaurs.

Science.gov (United States)

Cerda, Ignacio Alejandro; Chinsamy, Anusuya; Pol, Diego; Apaldetti, Cecilia; Otero, Alejandro; Powell, Jaime Eduardo; Martínez, Ricardo Nestor

2017-01-01

Sauropod dinosaurs include the largest terrestrial animals and are considered to have uninterrupted rapid rates of growth, which differs from their more basal relatives, which have a slower cyclical growth. Here we examine the bone microstructure of several sauropodomorph dinosaurs, including basal taxa, as well as the more derived sauropods. Although our results agree that the plesiomorphic condition for Sauropodomorpha is cyclical growth dynamics, we found that the hypothesized dichotomy between the growth patterns of basal and more derived sauropodomorphs is not supported. Here, we show that sauropod-like growth dynamics of uninterrupted rapid growth also occurred in some basal sauropodomorphs, and that some basal sauropods retained the plesiomorphic cyclical growth patterns. Among the sauropodomorpha it appears that the basal taxa exploited different growth strategies, but the more derived Eusauropoda successfully utilized rapid, uninterrupted growth strategies.

Neural correlates of cross-domain affective priming.

Science.gov (United States)

Zhang, Qin; Li, Xiaohua; Gold, Brian T; Jiang, Yang

2010-05-06

The affective priming effect has mostly been studied using reaction time (RT) measures; however, the neural bases of affective priming are not well established. To understand the neural correlates of cross-domain emotional stimuli presented rapidly, we obtained event-related potential (ERP) measures during an affective priming task using short SOA (stimulus onset asynchrony) conditions. Two sets of 480 picture-word pairs were presented at SOAs of either 150ms or 250ms between prime and target stimuli. Participants decided whether the valence of each target word was pleasant or unpleasant. Behavioral results from both SOA conditions were consistent with previous reports of affective priming, with longer RTs for incongruent than congruent pairs at SOAs of 150ms (771 vs. 738ms) and 250ms (765 vs. 720ms). ERP results revealed that the N400 effect (associated with incongruent pairs in affective processing) occurred at anterior scalp regions at an SOA of 150ms, and this effect was only observed for negative target words across the scalp at an SOA of 250ms. In contrast, late positive potentials (LPPs) (associated with attentional resource allocation) occurred across the scalp at an SOA of 250ms. LPPs were only observed for positive target words at posterior parts of the brain at an SOA of 150ms. Our finding of ERP signatures at very short SOAs provides the first neural evidence that affective pictures can exert an automatic influence on the evaluation of affective target words. Copyright 2010 Elsevier B.V. All rights reserved.

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

Science.gov (United States)

Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

2018-01-02

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Artificial neural network applications in the calibration of spark-ignition engines: An overview

Directory of Open Access Journals (Sweden)

Richard Fiifi Turkson

2016-09-01

Full Text Available Emission legislation has become progressively tighter, making the development of new internal combustion engines very challenging. New engine technologies for complying with these regulations introduce an exponential dependency between the number of test combinations required for obtaining optimum results and the time and cost outlays. This makes the calibration task very expensive and virtually impossible to carry out. The potential use of trained neural networks in combination with Design of Experiments (DoE methods for engine calibration has been a subject of research activities in recent times. This is because artificial neural networks, compared with other data-driven modeling techniques, perform better in satisfying a majority of the modeling requirements for engine calibration including the curse of dimensionality; the use of DoE for obtaining few measurements as practicable, with the aim of reducing engine calibration costs; the required flexibility that allows model parameters to be optimized to avoid overfitting; and the facilitation of automated online optimization during the engine calibration process that eliminates the need for user intervention. The purpose of this review is to give an overview of the various applications of neural networks in the calibration of spark-ignition engines. The identified and discussed applications include system identification for rapid prototyping, virtual sensing, use of neural networks as look-up table surrogates, emerging control strategies and On-Board Diagnostic (OBD applications. The demerits of neural networks, future possibilities and alternatives were also discussed.

How to build VLSI-efficient neural chips

Energy Technology Data Exchange (ETDEWEB)

Beiu, V.

1998-02-01

This paper presents several upper and lower bounds for the number-of-bits required for solving a classification problem, as well as ways in which these bounds can be used to efficiently build neural network chips. The focus will be on complexity aspects pertaining to neural networks: (1) size complexity and depth (size) tradeoffs, and (2) precision of weights and thresholds as well as limited interconnectivity. They show difficult problems-exponential growth in either space (precision and size) and/or time (learning and depth)-when using neural networks for solving general classes of problems (particular cases may enjoy better performances). The bounds for the number-of-bits required for solving a classification problem represent the first step of a general class of constructive algorithms, by showing how the quantization of the input space could be done in O (m{sup 2}n) steps. Here m is the number of examples, while n is the number of dimensions. The second step of the algorithm finds its roots in the implementation of a class of Boolean functions using threshold gates. It is substantiated by mathematical proofs for the size O (mn/{Delta}), and the depth O [log(mn)/log{Delta}] of the resulting network (here {Delta} is the maximum fan in). Using the fan in as a parameter, a full class of solutions can be designed. The third step of the algorithm represents a reduction of the size and an increase of its generalization capabilities. Extensions by using analogue COMPARISONs, allows for real inputs, and increase the generalization capabilities at the expense of longer training times. Finally, several solutions which can lower the size of the resulting neural network are detailed. The interesting aspect is that they are obtained for limited, or even constant, fan-ins. In support of these claims many simulations have been performed and are called upon.

Larger Neural Responses Produce BOLD Signals That Begin Earlier in Time

Directory of Open Access Journals (Sweden)

Serena eThompson

2014-06-01

Full Text Available Functional MRI analyses commonly rely on the assumption that the temporal dynamics of hemodynamic response functions (HRFs are independent of the amplitude of the neural signals that give rise to them. The validity of this assumption is particularly important for techniques that use fMRI to resolve sub-second timing distinctions between responses, in order to make inferences about the ordering of neural processes. Whether or not the detailed shape of the HRF is independent of neural response amplitude remains an open question, however. We performed experiments in which we measured responses in primary visual cortex (V1 to large, contrast-reversing checkerboards at a range of contrast levels, which should produce varying amounts of neural activity. Ten subjects (ages 22-52 were studied in each of two experiments using 3 Tesla scanners. We used rapid, 250 msec, temporal sampling (repetition time, or TR and both short and long inter-stimulus interval (ISI stimulus presentations. We tested for a systematic relationship between the onset of the HRF and its amplitude across conditions, and found a strong negative correlation between the two measures when stimuli were separated in time (long- and medium-ISI experiments, but not the short-ISI experiment. Thus, stimuli that produce larger neural responses, as indexed by HRF amplitude, also produced HRFs with shorter onsets. The relationship between amplitude and latency was strongest in voxels with lowest mean-normalized variance (i.e., parenchymal voxels. The onset differences observed in the longer-ISI experiments are likely attributable to mechanisms of neurovascular coupling, since they are substantially larger than reported differences in the onset of action potentials in V1 as a function of response amplitude.

Systematic Three-Dimensional Coculture Rapidly Recapitulates Interactions between Human Neurons and Astrocytes

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Robert Krencik

2017-12-01

Full Text Available Summary: Human astrocytes network with neurons in dynamic ways that are still poorly defined. Our ability to model this relationship is hampered by the lack of relevant and convenient tools to recapitulate this complex interaction. To address this barrier, we have devised efficient coculture systems utilizing 3D organoid-like spheres, termed asteroids, containing pre-differentiated human pluripotent stem cell (hPSC-derived astrocytes (hAstros combined with neurons generated from hPSC-derived neural stem cells (hNeurons or directly induced via Neurogenin 2 overexpression (iNeurons. Our systematic methods rapidly produce structurally complex hAstros and synapses in high-density coculture with iNeurons in precise numbers, allowing for improved studies of neural circuit function, disease modeling, and drug screening. We conclude that these bioengineered neural circuit model systems are reliable and scalable tools to accurately study aspects of human astrocyte-neuron functional properties while being easily accessible for cell-type-specific manipulations and observations. : In this article, Krencik and colleagues show that high-density cocultures of pre-differentiated human astrocytes with induced neurons, from pluripotent stem cells, elicit mature characteristics by 3–5 weeks. This provides a faster and more defined alternative method to organoid cultures for investigating human neural circuit function. Keywords: human pluripotent stem cells, neurons, astrocytes, synapses, coculture, three-dimensional spheres, organoids, disease modeling

Rapid Automatic Motor Encoding of Competing Reach Options

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Jason P. Gallivan

2017-02-01

Full Text Available Mounting neural evidence suggests that, in situations in which there are multiple potential targets for action, the brain prepares, in parallel, competing movements associated with these targets, prior to implementing one of them. Central to this interpretation is the idea that competing viewed targets, prior to selection, are rapidly and automatically transformed into corresponding motor representations. Here, by applying target-specific, gradual visuomotor rotations and dissociating, unbeknownst to participants, the visual direction of potential targets from the direction of the movements required to reach the same targets, we provide direct evidence for this provocative idea. Our results offer strong empirical support for theories suggesting that competing action options are automatically represented in terms of the movements required to attain them. The rapid motor encoding of potential targets may support the fast optimization of motor costs under conditions of target uncertainty and allow the motor system to inform decisions about target selection.

Using deep recurrent neural network for direct beam solar irradiance cloud screening

Science.gov (United States)

Chen, Maosi; Davis, John M.; Liu, Chaoshun; Sun, Zhibin; Zempila, Melina Maria; Gao, Wei

2017-09-01

Cloud screening is an essential procedure for in-situ calibration and atmospheric properties retrieval on (UV-)MultiFilter Rotating Shadowband Radiometer [(UV-)MFRSR]. Previous study has explored a cloud screening algorithm for direct-beam (UV-)MFRSR voltage measurements based on the stability assumption on a long time period (typically a half day or a whole day). To design such an algorithm requires in-depth understanding of radiative transfer and delicate data manipulation. Recent rapid developments on deep neural network and computation hardware have opened a window for modeling complicated End-to-End systems with a standardized strategy. In this study, a multi-layer dynamic bidirectional recurrent neural network is built for determining the cloudiness on each time point with a 17-year training dataset and tested with another 1-year dataset. The dataset is the daily 3-minute cosine corrected voltages, airmasses, and the corresponding cloud/clear-sky labels at two stations of the USDA UV-B Monitoring and Research Program. The results show that the optimized neural network model (3-layer, 250 hidden units, and 80 epochs of training) has an overall test accuracy of 97.87% (97.56% for the Oklahoma site and 98.16% for the Hawaii site). Generally, the neural network model grasps the key concept of the original model to use data in the entire day rather than short nearby measurements to perform cloud screening. A scrutiny of the logits layer suggests that the neural network model automatically learns a way to calculate a quantity similar to total optical depth and finds an appropriate threshold for cloud screening.

Integrative analysis of genes and miRNA alterations in human embryonic stem cells-derived neural cells after exposure to silver nanoparticles

International Nuclear Information System (INIS)

Oh, Jung-Hwa; Son, Mi-Young; Choi, Mi-Sun; Kim, Soojin; Choi, A-young; Lee, Hyang-Ae; Kim, Ki-Suk; Kim, Janghwan; Song, Chang Woo; Yoon, Seokjoo

2016-01-01

Given the rapid growth of engineered and customer products made of silver nanoparticles (Ag NPs), understanding their biological and toxicological effects on humans is critically important. The molecular developmental neurotoxic effects associated with exposure to Ag NPs were analyzed at the physiological and molecular levels, using an alternative cell model: human embryonic stem cell (hESC)-derived neural stem/progenitor cells (NPCs). In this study, the cytotoxic effects of Ag NPs (10–200 μg/ml) were examined in these hESC-derived NPCs, which have a capacity for neurogenesis in vitro, at 6 and 24 h. The results showed that Ag NPs evoked significant toxicity in hESC-derived NPCs at 24 h in a dose-dependent manner. In addition, Ag NPs induced cell cycle arrest and apoptosis following a significant increase in oxidative stress in these cells. To further clarify the molecular mechanisms of the toxicological effects of Ag NPs at the transcriptional and post-transcriptional levels, the global expression profiles of genes and miRNAs were analyzed in hESC-derived NPCs after Ag NP exposure. The results showed that Ag NPs induced oxidative stress and dysfunctional neurogenesis at the molecular level in hESC-derived NPCs. Based on this hESC-derived neural cell model, these findings have increased our understanding of the molecular events underlying developmental neurotoxicity induced by Ag NPs in humans. - Highlights: • This system served as a suitable model for developmental neurotoxicity testing. • Ag NPs induce the apoptosis in human neural cells by ROS generation. • Genes for development of neurons were dysregulated in response to Ag NPs. • Molecular events during early developmental neurotoxicity were proposed.

Integrative analysis of genes and miRNA alterations in human embryonic stem cells-derived neural cells after exposure to silver nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Oh, Jung-Hwa [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of); Son, Mi-Young [Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahangno, Yuseong-gu, Daejeon 34141 (Korea, Republic of); Department of functional genomics, University of Science & Technology, 217 Gajungro, Yuseong-gu, Daejeon 34113 (Korea, Republic of); Choi, Mi-Sun; Kim, Soojin; Choi, A-young [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Lee, Hyang-Ae; Kim, Ki-Suk [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of); Kim, Janghwan [Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahangno, Yuseong-gu, Daejeon 34141 (Korea, Republic of); Department of functional genomics, University of Science & Technology, 217 Gajungro, Yuseong-gu, Daejeon 34113 (Korea, Republic of); Song, Chang Woo, E-mail: cwsong@kitox.re.kr [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of); Yoon, Seokjoo, E-mail: sjyoon@kitox.re.kr [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of)

2016-05-15

Given the rapid growth of engineered and customer products made of silver nanoparticles (Ag NPs), understanding their biological and toxicological effects on humans is critically important. The molecular developmental neurotoxic effects associated with exposure to Ag NPs were analyzed at the physiological and molecular levels, using an alternative cell model: human embryonic stem cell (hESC)-derived neural stem/progenitor cells (NPCs). In this study, the cytotoxic effects of Ag NPs (10–200 μg/ml) were examined in these hESC-derived NPCs, which have a capacity for neurogenesis in vitro, at 6 and 24 h. The results showed that Ag NPs evoked significant toxicity in hESC-derived NPCs at 24 h in a dose-dependent manner. In addition, Ag NPs induced cell cycle arrest and apoptosis following a significant increase in oxidative stress in these cells. To further clarify the molecular mechanisms of the toxicological effects of Ag NPs at the transcriptional and post-transcriptional levels, the global expression profiles of genes and miRNAs were analyzed in hESC-derived NPCs after Ag NP exposure. The results showed that Ag NPs induced oxidative stress and dysfunctional neurogenesis at the molecular level in hESC-derived NPCs. Based on this hESC-derived neural cell model, these findings have increased our understanding of the molecular events underlying developmental neurotoxicity induced by Ag NPs in humans. - Highlights: • This system served as a suitable model for developmental neurotoxicity testing. • Ag NPs induce the apoptosis in human neural cells by ROS generation. • Genes for development of neurons were dysregulated in response to Ag NPs. • Molecular events during early developmental neurotoxicity were proposed.

Neural networks for aircraft control

Science.gov (United States)

Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Communication and The Challenges of Rapid Population Growth in ...

African Journals Online (AJOL)

2005) which projected the African Population at 1,349 million by 2025 and 1,969 million by 2050. These figures are so frightening that the use of communication to contribute to checking the high population growth is challenged. We discuss ...

Angiogenic factors stimulate growth of adult neural stem cells.

Directory of Open Access Journals (Sweden)

Andreas Androutsellis-Theotokis

2010-02-01

Full Text Available The ability to grow a uniform cell type from the adult central nervous system (CNS is valuable for developing cell therapies and new strategies for drug discovery. The adult mammalian brain is a source of neural stem cells (NSC found in both neurogenic and non-neurogenic zones but difficulties in culturing these hinders their use as research tools.Here we show that NSCs can be efficiently grown in adherent cell cultures when angiogenic signals are included in the medium. These signals include both anti-angiogenic factors (the soluble form of the Notch receptor ligand, Dll4 and pro-angiogenic factors (the Tie-2 receptor ligand, Angiopoietin 2. These treatments support the self renewal state of cultured NSCs and expression of the transcription factor Hes3, which also identifies the cancer stem cell population in human tumors. In an organotypic slice model, angiogenic factors maintain vascular structure and increase the density of dopamine neuron processes.We demonstrate new properties of adult NSCs and a method to generate efficient adult NSC cultures from various central nervous system areas. These findings will help establish cellular models relevant to cancer and regeneration.

Neural Networks Method in modeling of the financial company’s performance

Directory of Open Access Journals (Sweden)

I. P. Kurochkina

2017-01-01

Full Text Available The content of modern management accounting is formed in conjunction with the rapid development of information technology, using complex algorithms of economic analysis. It makes possible the practical realization of the effective management idea - management of key performance indicators, which certainly includes the indicators of financial performance of economic entities.An important place in this process is given to the construction and calculation of factorial systems of economic indicators. A substantial theoretical and empirical experience has been accumulated to solve the problems that arise. The aim of this study is to develop a universal modern model for factor analysis of finance results, allowing multivariate solutions both current and promising character with monitoring in real time.The realization of this goal is achievable by using artificial neural networks (ANN in an appropriate simulation, which are increasingly used in the economy as a tool for supporting management decisionmaking. In comparison with classical deterministic and stochastic models, ANN brings the intellectual component to the modeling process. They are able to learn to function based on the gained experience, the result of allowing less and less mistakes.The article reveals the advantages of such an alternative approach. An alternative approach to factor analysis, based on the method of neural networks, is proposed. Advantages of this approach are marked. The paper presents a phased algorithm of modeling complex cause-and-effect nature relationships, including factors’ selection for the studied result, the creation of the neural network architecture and its training. The universality of such modeling lies in the fact that it can be used for any resulting indicator.The authors have proposed and described a mathematical model of the factor analysis for financial indicators. It is important that the model included the factors of both direct and indirect actions

Extracellular matrix and its receptors in Drosophila neural development

Science.gov (United States)

Broadie, Kendal; Baumgartner, Stefan; Prokop, Andreas

2011-01-01

Extracellular matrix (ECM) and matrix receptors are intimately involved in most biological processes. The ECM plays fundamental developmental and physiological roles in health and disease, including processes underlying the development, maintenance and regeneration of the nervous system. To understand the principles of ECM-mediated functions in the nervous system, genetic model organisms like Drosophila provide simple, malleable and powerful experimental platforms. This article provides an overview of ECM proteins and receptors in Drosophila. It then focuses on their roles during three progressive phases of neural development: 1) neural progenitor proliferation, 2) axonal growth and pathfinding and 3) synapse formation and function. Each section highlights known ECM and ECM-receptor components and recent studies done in mutant conditions to reveal their in vivo functions, all illustrating the enormous opportunities provided when merging work on the nervous system with systematic research into ECM-related gene functions. PMID:21688401

Dissecting neural pathways for forgetting in Drosophila olfactory aversive memory.

Science.gov (United States)

Shuai, Yichun; Hirokawa, Areekul; Ai, Yulian; Zhang, Min; Li, Wanhe; Zhong, Yi

2015-12-01

Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay without altering learning, whereas activating them promotes forgetting. These neurons, including a cluster of dopaminergic neurons (PAM-β'1) and a pair of glutamatergic neurons (MBON-γ4>γ1γ2), terminate in distinct subdomains in the mushroom body and represent parallel neural pathways for regulating forgetting. Interestingly, although activity of these neurons is required for memory decay over time, they are not required for acute forgetting during reversal learning. Our results thus not only establish the presence of multiple neural pathways for forgetting in Drosophila but also suggest the existence of diverse circuit mechanisms of forgetting in different contexts.

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

Science.gov (United States)

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

Neural network regulation driven by autonomous neural firings

Science.gov (United States)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

The neural response properties and cortical organization of a rapidly adapting muscle sensory group response that overlaps with the frequencies that elicit the kinesthetic illusion.

Directory of Open Access Journals (Sweden)

Paul D Marasco

Full Text Available Kinesthesia is the sense of limb movement. It is fundamental to efficient motor control, yet its neurophysiological components remain poorly understood. The contributions of primary muscle spindles and cutaneous afferents to the kinesthetic sense have been well studied; however, potential contributions from muscle sensory group responses that are different than the muscle spindles have not been ruled out. Electrophysiological recordings in peripheral nerves and brains of male Sprague Dawley rats with a degloved forelimb preparation provide evidence of a rapidly adapting muscle sensory group response that overlaps with vibratory inputs known to generate illusionary perceptions of limb movement in humans (kinesthetic illusion. This group was characteristically distinct from type Ia muscle spindle fibers, the receptor historically attributed to limb movement sensation, suggesting that type Ia muscle spindle fibers may not be the sole carrier of kinesthetic information. The sensory-neural structure of muscles is complex and there are a number of possible sources for this response group; with Golgi tendon organs being the most likely candidate. The rapidly adapting muscle sensory group response projected to proprioceptive brain regions, the rodent homolog of cortical area 3a and the second somatosensory area (S2, with similar adaption and frequency response profiles between the brain and peripheral nerves. Their representational organization was muscle-specific (myocentric and magnified for proximal and multi-articulate limb joints. Projection to proprioceptive brain areas, myocentric representational magnification of muscles prone to movement error, overlap with illusionary vibrational input, and resonant frequencies of volitional motor unit contraction suggest that this group response may be involved with limb movement processing.

A rapidly enlarging cutaneous hemangioma in pregnancy.

LENUS (Irish Health Repository)

Ma'ayeh, Marwan

2014-06-18

This is a case of a rapidly enlarging cutaneous pedunculated tumor on a patient\\'s thumb during her pregnancy. This was excised and identified as a hemangioma. A literature search identified a possible hormonal factor in causing an accelerated growth of this tumor.

Open source tools for the information theoretic analysis of neural data

Directory of Open Access Journals (Sweden)

Robin A. A Ince

2010-05-01

Full Text Available The recent and rapid development of open-source software tools for the analysis of neurophysiological datasets consisting of multiple simultaneous recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and integrate the information obtained at different spatial and temporal scales. In this Review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in Matlab and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

Open source tools for the information theoretic analysis of neural data.

Science.gov (United States)

Ince, Robin A A; Mazzoni, Alberto; Petersen, Rasmus S; Panzeri, Stefano

2010-01-01

The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

Dynamics of neural cryptography.

Science.gov (United States)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-05-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

Dynamics of neural cryptography

International Nuclear Information System (INIS)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-01-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

Dynamics of neural cryptography

Science.gov (United States)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-05-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

Catch-up Growth Followed by Stagnation: Mexico, 1950-2010

OpenAIRE

Timothy J. Kehoe; Felipe Meza

2011-01-01

In 1950 Mexico entered an economic takeoff and grew rapidly for more than 30 years. Growth stopped during the crises of 1982-1995, despite major reforms, including liberalization of foreign trade and investment. Since then growth has been modest. We analyze the economic history of Mexico 1877-2010. We conclude that the growth 1950-1981 was driven by urbanization, industrialization, and education and that Mexico would have grown even more rapidly if trade and investment had been liberalized so...

Bioprinting for Neural Tissue Engineering.

Science.gov (United States)

Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

2018-01-01

Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

Science.gov (United States)

Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

2013-04-30

The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

Effects of hyperbaric oxygen and nerve growth factor on the long-term neural behavior of neonatal rats with hypoxic ischemic brain damage.

Science.gov (United States)

Wei, Lixia; Ren, Qing; Zhang, Yongjun; Wang, Jiwen

2017-04-01

To evaluate the effects of HBO (Hyperbaric oxygen) and NGF (Nerve growth factor) on the long-term neural behavior of neonatal rats with HIBD (Neonatal hypoxic ischemic brain damage). The HIBD model was produced by ligating the right common carotid artery of 7 days old SD (Sprague-Dawley) rats followed by 8% O2 + 92% N2 for 2h. Totally 40 rats were randomly divided into 5 groups including sham-operated group, HIBD control group, HBO treated group, NGF treated group and NGF + HBO treated group. The learning and memory ability of these rats was evaluated by Morris water maze at 30 days after birth, and sensory motor function was assessed by experiments of foot error and limb placement at 42 days after birth. The escape latency of HBO treated group, NGF treated group and NGF + HBO treated group was shorter than that of HIBD control group (pmemory ability and sensory motor function in neonatal rats after hypoxic ischemic brain damage.

Expression of Pluripotency Markers in Nonpluripotent Human Neural Stem and Progenitor Cells

DEFF Research Database (Denmark)

Vincent, P.; Benedikz, Eirikur; Uhlén, Per

2017-01-01

Nonpluripotent neural progenitor cells (NPCs) derived from the human fetal central nervous system were found to express a number of messenger RNA (mRNA) species associated with pluripotency, such as NANOG, REX1, and OCT4. The expression was restricted to small subpopulations of NPCs. In contrast...... to pluripotent stem cells, there was no coexpression of the pluripotency-associated genes studied. Although the expression of these genes rapidly declined during the in vitro differentiation of NPCs, we found no evidence that the discrete expression was associated with the markers of multipotent neural stem...... cells (CD133+/CD24lo), the capacity of sphere formation, or high cell proliferation rates. The rate of cell death among NPCs expressing pluripotency-associated genes was also similar to that of other NPCs. Live cell imaging showed that NANOG- and REX1-expressing NPCs continuously changed morphology...

Comparison of different artificial neural network architectures in modeling of Chlorella sp. flocculation.

Science.gov (United States)

Zenooz, Alireza Moosavi; Ashtiani, Farzin Zokaee; Ranjbar, Reza; Nikbakht, Fatemeh; Bolouri, Oberon

2017-07-03

Biodiesel production from microalgae feedstock should be performed after growth and harvesting of the cells, and the most feasible method for harvesting and dewatering of microalgae is flocculation. Flocculation modeling can be used for evaluation and prediction of its performance under different affective parameters. However, the modeling of flocculation in microalgae is not simple and has not performed yet, under all experimental conditions, mostly due to different behaviors of microalgae cells during the process under different flocculation conditions. In the current study, the modeling of microalgae flocculation is studied with different neural network architectures. Microalgae species, Chlorella sp., was flocculated with ferric chloride under different conditions and then the experimental data modeled using artificial neural network. Neural network architectures of multilayer perceptron (MLP) and radial basis function architectures, failed to predict the targets successfully, though, modeling was effective with ensemble architecture of MLP networks. Comparison between the performances of the ensemble and each individual network explains the ability of the ensemble architecture in microalgae flocculation modeling.

Neural network expert system for X-ray analysis of welded joints

Science.gov (United States)

Kozlov, V. V.; Lapik, N. V.; Popova, N. V.

2018-03-01

The use of intelligent technologies for the automated analysis of product quality is one of the main trends in modern machine building. At the same time, rapid development in various spheres of human activity is experienced by methods associated with the use of artificial neural networks, as the basis for building automated intelligent diagnostic systems. Technologies of machine vision allow one to effectively detect the presence of certain regularities in the analyzed designation, including defects of welded joints according to radiography data.

The Neuroscience of Growth Mindset and Intrinsic Motivation.

Science.gov (United States)

Ng, Betsy

2018-01-26

Our actions can be triggered by intentions, incentives or intrinsic values. Recent neuroscientific research has yielded some results about the growth mindset and intrinsic motivation. With the advances in neuroscience and motivational studies, there is a global need to utilize this information to inform educational practice and research. Yet, little is known about the neuroscientific interplay between growth mindset and intrinsic motivation. This paper attempts to draw on the theories of growth mindset and intrinsic motivation, together with contemporary ideas in neuroscience, outline the potential for neuroscientific research in education. It aims to shed light on the relationship between growth mindset and intrinsic motivation in terms of supporting a growth mindset to facilitate intrinsic motivation through neural responses. Recent empirical research from the educational neuroscience perspective that provides insights into the interplay between growth mindset and intrinsic motivation will also be discussed.

Rapid structural and compositional change in an old-growth subtropical forest: using plant traits to identify probable drivers.

Science.gov (United States)

Malizia, Agustina; Easdale, Tomás A; Grau, H Ricardo

2013-01-01

Recent studies have shown directional changes in old-growth tropical forests, but changes are complex and diverse, and their drivers unclear. Here, we report rapid net structural and compositional changes in an old-growth subtropical forest and we assess the functional nature of these changes to test hypothetical drivers including recovery from past disturbances, reduction in ungulate browsing, CO2 fertilization, and increases in rainfall and temperature. The study relies on 15 years of demographic monitoring within 8 ha of subtropical montane forest in Argentina. Between 1992 and 2007, stem density markedly increased by 50% (12 stems ha(-1) y(-1)) and basal area by 6% (0.13 m(2) ha(-1) y(-1)). Increased stem density resulted from enhanced recruitment of understory treelets (Piper tucumanum, Eugenia uniflora, Allophylus edulis) into small size classes. Among 27 common tree species, net population growth was negatively correlated with maximum tree size and longevity, and positively correlated with leaf size and leaf nutrient content, especially so when initial population size was controlled for. Changes were inconsistent with predictions derived from past disturbances (no increase in shade-tolerant or long-lived late-succesional species), rainfall or temperature increase (no increase in evergreen or deciduous species, respectively). However, the increase in nutrient-rich soft-leaved species was consistent with exclusion of large herbivores two decades before monitoring started; and CO2 fertilization could help explain the disproportionate increase in small stems. Reductions in populations of large vertebrates have been observed in many otherwise undisturbed tropical forests, and our results suggest they can have important structural and functional repercussions in these forests.

Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

Science.gov (United States)

Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

2012-06-01

This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

Directory of Open Access Journals (Sweden)

Alexander eHuk

2012-10-01

Full Text Available A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP. In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1 empirical questions not yet answered by existing data; (2 implementation issues related to how neural circuits could actually implement the mechanisms suggested by both physiology and psychology; and (3 ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general encoding-decoding framework that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions.

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

Directory of Open Access Journals (Sweden)

Chernoded Andrey

2017-01-01

Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

Growth of the skull in young children in Baotou, China.

Science.gov (United States)

Hou, Hai-dong; Liu, Ming; Gong, Ke-rui; Shao, Guo; Zhang, Chun-Yang

2014-09-01

There are some controversies about the optimal time to perform skull repair in very young Chinese children because of the rapid skull growth in this stage of life. The purpose of this current study is to describe the characteristics of skull growth and to discuss the optimal time for skull repair in young Chinese children with skull defects. A total of 112 children born in the First Affiliated Hospital of Baotou Medical College were measured for six consecutive years starting in 2006. Cranial length (CL, linear distance between the eyebrows to the pillow tuberosity), cranial width (CW, double-sided linear distance of connection of external auditory canal), ear over the top line (EOTL), the eyebrows-the posterior tuberosity line (EPTL), and head circumference (HC) were measured to describe the skull growth. The most rapid period of skull growth occurs during the first year of life. The second and third most rapid periods are the second and third years, respectively. Then, the skull growth slowed and the values of the skull growth index of 6-year-old children were close to those of adults. Children 0-1 years old should not receive skull repair due to their rapid skull growth. The indexes of children 3 years old or older were close to those of the adult; therefore, 3 years old or older may receive skull repair.

Neural Tube Defects

Science.gov (United States)

Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication.

Science.gov (United States)

Symons, Ashley E; El-Deredy, Wael; Schwartze, Michael; Kotz, Sonja A

2016-01-01

Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples

Fabrication of bioactive conduits containing the fibroblast growth factor 1 and neural stem cells for peripheral nerve regeneration across a 15 mm critical gap

International Nuclear Information System (INIS)

Ni, Hsiao-Chiang; Tseng, Ting-Chen; Hsu, Shan-hui; Chen, Jeng-Rung; Chiu, Ing-Ming

2013-01-01

Nerve conduits are often used in combination with bioactive molecules and stem cells to enhance peripheral nerve regeneration. In this study, the acidic fibroblast growth factor 1 (FGF1) was immobilized onto the microporous/micropatterned poly (D, L-lactic acid) (PLA) nerve conduits after open air plasma treatment. PLA substrates grafted with chitosan in the presence of a small amount of gold nanoparticles (nano Au) showed a protective effect on the activity of the immobilized FGF1 in vitro. Different conduits were tested for their ability to bridge a 15 mm critical gap defect in a rat sciatic nerve injury model. Axon regeneration and functional recovery were evaluated by histology, walking track analysis and electrophysiology. Among different conduits, PLA conduits grafted with chitosan–nano Au and the FGF1 after plasma activation had the greatest regeneration capacity and functional recovery in the experimental animals. When the above conduit was seeded with aligned neural stem cells, the efficacy was further enhanced and it approached that of the autograft group. This work suggested that microporous/micropatterned nerve conduits containing bioactive growth factors may be successfully fabricated by micropatterning techniques, open plasma activation, and immobilization, which, combined with aligned stem cells, may synergistically contribute to the regeneration of the severely damaged peripheral nerve. (paper)

Employment and Growth | Page 36 | IDRC - International ...

International Development Research Centre (IDRC) Digital Library (Canada)

As an engine of economic growth, private enterprise plays an important role in combatting ... In helping developing countries pursue private sector development ... India's rapid economic growth has reduced extreme poverty in the country.

Aeroelasticity of morphing wings using neural networks

Science.gov (United States)

Natarajan, Anand

In this dissertation, neural networks are designed to effectively model static non-linear aeroelastic problems in adaptive structures and linear dynamic aeroelastic systems with time varying stiffness. The use of adaptive materials in aircraft wings allows for the change of the contour or the configuration of a wing (morphing) in flight. The use of smart materials, to accomplish these deformations, can imply that the stiffness of the wing with a morphing contour changes as the contour changes. For a rapidly oscillating body in a fluid field, continuously adapting structural parameters may render the wing to behave as a time variant system. Even the internal spars/ribs of the aircraft wing which define the wing stiffness can be made adaptive, that is, their stiffness can be made to vary with time. The immediate effect on the structural dynamics of the wing, is that, the wing motion is governed by a differential equation with time varying coefficients. The study of this concept of a time varying torsional stiffness, made possible by the use of active materials and adaptive spars, in the dynamic aeroelastic behavior of an adaptable airfoil is performed here. Another type of aeroelastic problem of an adaptive structure that is investigated here, is the shape control of an adaptive bump situated on the leading edge of an airfoil. Such a bump is useful in achieving flow separation control for lateral directional maneuverability of the aircraft. Since actuators are being used to create this bump on the wing surface, the energy required to do so needs to be minimized. The adverse pressure drag as a result of this bump needs to be controlled so that the loss in lift over the wing is made minimal. The design of such a "spoiler bump" on the surface of the airfoil is an optimization problem of maximizing pressure drag due to flow separation while minimizing the loss in lift and energy required to deform the bump. One neural network is trained using the CFD code FLUENT to

Neural networks and wavelet analysis in the computer interpretation of pulse oximetry data

Energy Technology Data Exchange (ETDEWEB)

Dowla, F.U.; Skokowski, P.G.; Leach, R.R. Jr.

1996-03-01

Pulse oximeters determine the oxygen saturation level of blood by measuring the light absorption of arterial blood. The sensor consists of red and infrared light sources and photodetectors. A method based on neural networks and wavelet analysis is developed for improved saturation estimation in the presence of sensor motion. Spectral and correlation functions of the dual channel oximetry data are used by a backpropagation neural network to characterize the type of motion. Amplitude ratios of red to infrared signals as a function of time scale are obtained from the multiresolution wavelet decomposition of the two-channel data. Motion class and amplitude ratios are then combined to obtain a short-time estimate of the oxygen saturation level. A final estimate of oxygen saturation is obtained by applying a 15 s smoothing filter on the short-time measurements based on 3.5 s windows sampled every 1.75 s. The design employs two backpropagation neural networks. The first neural network determines the motion characteristics and the second network determines the saturation estimate. Our approach utilizes waveform analysis in contrast to the standard algorithms that are based on the successful detection of peaks and troughs in the signal. The proposed algorithm is numerically efficient and has stable characteristics with a reduced false alarm rate with a small loss in detection. The method can be rapidly developed on a digital signal processing platform.

Semantic Congruence Accelerates the Onset of the Neural Signals of Successful Memory Encoding.

Science.gov (United States)

Packard, Pau A; Rodríguez-Fornells, Antoni; Bunzeck, Nico; Nicolás, Berta; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

2017-01-11

As the stream of experience unfolds, our memory system rapidly transforms current inputs into long-lasting meaningful memories. A putative neural mechanism that strongly influences how input elements are transformed into meaningful memory codes relies on the ability to integrate them with existing structures of knowledge or schemas. However, it is not yet clear whether schema-related integration neural mechanisms occur during online encoding. In the current investigation, we examined the encoding-dependent nature of this phenomenon in humans. We showed that actively integrating words with congruent semantic information provided by a category cue enhances memory for words and increases false recall. The memory effect of such active integration with congruent information was robust, even with an interference task occurring right after each encoding word list. In addition, via electroencephalography, we show in 2 separate studies that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. That the neural signals of successful encoding of congruent and incongruent information followed similarly ∼200 ms later suggests that this earlier neural response contributed to memory formation. We propose that the encoding of events that are congruent with readily available contextual semantics can trigger an accelerated onset of the neural mechanisms, supporting the integration of semantic information with the event input. This faster onset would result in a long-lasting and meaningful memory trace for the event but, at the same time, make it difficult to distinguish it from plausible but never encoded events (i.e., related false memories). Conceptual or schema congruence has a strong influence on long-term memory. However, the question of whether schema-related integration neural mechanisms occur during online encoding has yet to be clarified. We investigated the neural mechanisms reflecting how the active

A rapid, reliable method of evaluating growth and viability of intraerythrocytic protozoan hemoparasites using fluorescence flow cytometry.

Science.gov (United States)

Davis, W C; Wyatt, C R; Hamilton, M J; Goff, W L

1992-01-01

Fluorescence flow cytometry was employed to assess the potential of a vital dye, hydroethidine, for use in the detection and monitoring of the viability of hemoparasites in infected erythrocytes, using Babesia bovis as a model parasite. The studies demonstrated that hydroethidine is taken up by B. bovis and metabolically converted to the DNA binding fluorochrome, ethidium. Following uptake of the dye, erythrocytes containing viable parasites were readily distinguished and quantitated. Timed studies with the parasiticidal drug, Ganaseg, showed that it is possible to use the fluorochrome assay to monitor the effects of the drug on the rate of replication and viability of B. bovis in culture. The assay provides a rapid method for evaluation of the in vitro effect of drugs on hemoparasites and for analysis of the effect of various components of the immune response, such as lymphokines, monocyte products, antibodies, and effector cells (T, NK, LAK, ADCC) on the growth and viability of intraerythrocytic parasites.

A rapid, reliable method of evaluating growth and viability of intraerythrocytic protozoan hemoparasites using fluorescence flow cytometry

Directory of Open Access Journals (Sweden)

W. C. Davis

1992-01-01

Full Text Available Fluorescence flow cytometry was employed to assess the potential of a vital dye, hydroethiedine, for use in the detection and monitoring of the viability of hemoparasites in infected erythrocytes, using Babesia bovis as a model parasite. The studies demonstrated that hydroethidine is taken up by B. bovis and metabolically converted to the DNA binding fluorochrone, ethidium. Following uptake of the dye, erythrocytes contamine viable parasites were readily distinguished and quantitated. Timed studies with the parasiticidal drug, Ganaseg, showed that it is possible to use the fluorochrome assay to monitor the effects of the drug on the rate of replication and viability of B. bovis in culture. The assay provides a rapid method for evaluation of the in vitro effect of drugs on hemoparasites and for analysis of the effect of various components of the immune response, such as lymphokines, monocyte products, antibodies, and effector cells (T, NK, LAK, ADCC on the growth and viability of intraerythrocytic parasites.

Calculations of dose distributions using a neural network model

International Nuclear Information System (INIS)

Mathieu, R; Martin, E; Gschwind, R; Makovicka, L; Contassot-Vivier, S; Bahi, J

2005-01-01

The main goal of external beam radiotherapy is the treatment of tumours, while sparing, as much as possible, surrounding healthy tissues. In order to master and optimize the dose distribution within the patient, dosimetric planning has to be carried out. Thus, for determining the most accurate dose distribution during treatment planning, a compromise must be found between the precision and the speed of calculation. Current techniques, using analytic methods, models and databases, are rapid but lack precision. Enhanced precision can be achieved by using calculation codes based, for example, on Monte Carlo methods. However, in spite of all efforts to optimize speed (methods and computer improvements), Monte Carlo based methods remain painfully slow. A newer way to handle all of these problems is to use a new approach in dosimetric calculation by employing neural networks. Neural networks (Wu and Zhu 2000 Phys. Med. Biol. 45 913-22) provide the advantages of those various approaches while avoiding their main inconveniences, i.e., time-consumption calculations. This permits us to obtain quick and accurate results during clinical treatment planning. Currently, results obtained for a single depth-dose calculation using a Monte Carlo based code (such as BEAM (Rogers et al 2003 NRCC Report PIRS-0509(A) rev G)) require hours of computing. By contrast, the practical use of neural networks (Mathieu et al 2003 Proceedings Journees Scientifiques Francophones, SFRP) provides almost instant results and quite low errors (less than 2%) for a two-dimensional dosimetric map

Stress affects the neural ensemble for integrating new information and prior knowledge.

Science.gov (United States)

Vogel, Susanne; Kluen, Lisa Marieke; Fernández, Guillén; Schwabe, Lars

2018-06-01

Prior knowledge, represented as a schema, facilitates memory encoding. This schema-related learning is assumed to rely on the medial prefrontal cortex (mPFC) that rapidly integrates new information into the schema, whereas schema-incongruent or novel information is encoded by the hippocampus. Stress is a powerful modulator of prefrontal and hippocampal functioning and first studies suggest a stress-induced deficit of schema-related learning. However, the underlying neural mechanism is currently unknown. To investigate the neural basis of a stress-induced schema-related learning impairment, participants first acquired a schema. One day later, they underwent a stress induction or a control procedure before learning schema-related and novel information in the MRI scanner. In line with previous studies, learning schema-related compared to novel information activated the mPFC, angular gyrus, and precuneus. Stress, however, affected the neural ensemble activated during learning. Whereas the control group distinguished between sets of brain regions for related and novel information, stressed individuals engaged the hippocampus even when a relevant schema was present. Additionally, stressed participants displayed aberrant functional connectivity between brain regions involved in schema processing when encoding novel information. The failure to segregate functional connectivity patterns depending on the presence of prior knowledge was linked to impaired performance after stress. Our results show that stress affects the neural ensemble underlying the efficient use of schemas during learning. These findings may have relevant implications for clinical and educational settings. Copyright © 2018 Elsevier Inc. All rights reserved.

A neural flow estimator

DEFF Research Database (Denmark)

Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

1995-01-01

This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

Hidden neural networks

DEFF Research Database (Denmark)

Krogh, Anders Stærmose; Riis, Søren Kamaric

1999-01-01

A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

Slit/Robo1 signaling regulates neural tube development by balancing neuroepithelial cell proliferation and differentiation

Energy Technology Data Exchange (ETDEWEB)

Wang, Guang; Li, Yan; Wang, Xiao-yu [Key Laboratory for Regenerative Medicine of The Ministry of Education, Department of Histology and Embryology, School of Medicine, Jinan University, Guangzhou 510632 (China); Han, Zhe [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Chuai, Manli [College of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH (United Kingdom); Wang, Li-jing [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Ho Lee, Kenneth Ka [Stem Cell and Regeneration Thematic Research Programme, School of Biomedical Sciences, Chinese University of Hong Kong, Shatin (Hong Kong); Geng, Jian-guo, E-mail: jgeng@umich.edu [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Department of Biologic and Materials Sciences, University of Michigan School of Dentistry, Ann Arbor, MI 48109 (United States); Yang, Xuesong, E-mail: yang_xuesong@126.com [Key Laboratory for Regenerative Medicine of The Ministry of Education, Department of Histology and Embryology, School of Medicine, Jinan University, Guangzhou 510632 (China)

2013-05-01

Formation of the neural tube is the morphological hallmark for development of the embryonic central nervous system (CNS). Therefore, neural tube development is a crucial step in the neurulation process. Slit/Robo signaling was initially identified as a chemo-repellent that regulated axon growth cone elongation, but its role in controlling neural tube development is currently unknown. To address this issue, we investigated Slit/Robo1 signaling in the development of chick neCollege of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH, UKural tube and transgenic mice over-expressing Slit2. We disrupted Slit/Robo1 signaling by injecting R5 monoclonal antibodies into HH10 neural tubes to block the Robo1 receptor. This inhibited the normal development of the ventral body curvature and caused the spinal cord to curl up into a S-shape. Next, Slit/Robo1 signaling on one half-side of the chick embryo neural tube was disturbed by electroporation in ovo. We found that the morphology of the neural tube was dramatically abnormal after we interfered with Slit/Robo1 signaling. Furthermore, we established that silencing Robo1 inhibited cell proliferation while over-expressing Robo1 enhanced cell proliferation. We also investigated the effects of altering Slit/Robo1 expression on Sonic Hedgehog (Shh) and Pax7 expression in the developing neural tube. We demonstrated that over-expressing Robo1 down-regulated Shh expression in the ventral neural tube and resulted in the production of fewer HNK-1{sup +} migrating neural crest cells (NCCs). In addition, Robo1 over-expression enhanced Pax7 expression in the dorsal neural tube and increased the number of Slug{sup +} pre-migratory NCCs. Conversely, silencing Robo1 expression resulted in an enhanced Shh expression and more HNK-1{sup +} migrating NCCs but reduced Pax7 expression and fewer Slug{sup +} pre-migratory NCCs were observed. In conclusion, we propose that Slit/Robo1 signaling is involved in regulating neural tube

Effects of task-switching on neural representations of ambiguous sound input.

Science.gov (United States)

Sussman, Elyse S; Bregman, Albert S; Lee, Wei-Wei

2014-11-01

The ability to perceive discrete sound streams in the presence of competing sound sources relies on multiple mechanisms that organize the mixture of the auditory input entering the ears. Many studies have focused on mechanisms that contribute to integrating sounds that belong together into one perceptual stream (integration) and segregating those that come from different sound sources (segregation). However, little is known about mechanisms that allow us to perceive individual sound sources within a dynamically changing auditory scene, when the input may be ambiguous, and heard as either integrated or segregated. This study tested the question of whether focusing on one of two possible sound organizations suppressed representation of the alternative organization. We presented listeners with ambiguous input and cued them to switch between tasks that used either the integrated or the segregated percept. Electrophysiological measures indicated which organization was currently maintained in memory. If mutual exclusivity at the neural level was the rule, attention to one of two possible organizations would preclude neural representation of the other. However, significant MMNs were elicited to both the target organization and the unattended, alternative organization, along with the target-related P3b component elicited only to the designated target organization. Results thus indicate that both organizations (integrated and segregated) were simultaneously maintained in memory regardless of which task was performed. Focusing attention to one aspect of the sounds did not abolish the alternative, unattended organization when the stimulus input was ambiguous. In noisy environments, such as walking on a city street, rapid and flexible adaptive processes are needed to help facilitate rapid switching to different sound sources in the environment. Having multiple representations available to the attentive system would allow for such flexibility, needed in everyday situations to

Statistical Modeling and Prediction for Tourism Economy Using Dendritic Neural Network.

Science.gov (United States)

Yu, Ying; Wang, Yirui; Gao, Shangce; Tang, Zheng

2017-01-01

With the impact of global internationalization, tourism economy has also been a rapid development. The increasing interest aroused by more advanced forecasting methods leads us to innovate forecasting methods. In this paper, the seasonal trend autoregressive integrated moving averages with dendritic neural network model (SA-D model) is proposed to perform the tourism demand forecasting. First, we use the seasonal trend autoregressive integrated moving averages model (SARIMA model) to exclude the long-term linear trend and then train the residual data by the dendritic neural network model and make a short-term prediction. As the result showed in this paper, the SA-D model can achieve considerably better predictive performances. In order to demonstrate the effectiveness of the SA-D model, we also use the data that other authors used in the other models and compare the results. It also proved that the SA-D model achieved good predictive performances in terms of the normalized mean square error, absolute percentage of error, and correlation coefficient.

Reconstruction of three-dimensional porous media using generative adversarial neural networks

Science.gov (United States)

Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

2017-10-01

To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions.

Science.gov (United States)

Li, Shuhui; Fairbank, Michael; Johnson, Cameron; Wunsch, Donald C; Alonso, Eduardo; Proaño, Julio L

2014-04-01

Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using back-propagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

Anesthetics rapidly promote synaptogenesis during a critical period of brain development.

Directory of Open Access Journals (Sweden)

Mathias De Roo

Full Text Available Experience-driven activity plays an essential role in the development of brain circuitry during critical periods of early postnatal life, a process that depends upon a dynamic balance between excitatory and inhibitory signals. Since general anesthetics are powerful pharmacological modulators of neuronal activity, an important question is whether and how these drugs can affect the development of synaptic networks. To address this issue, we examined here the impact of anesthetics on synapse growth and dynamics. We show that exposure of young rodents to anesthetics that either enhance GABAergic inhibition or block NMDA receptors rapidly induce a significant increase in dendritic spine density in the somatosensory cortex and hippocampus. This effect is developmentally regulated; it is transient but lasts for several days and is also reproduced by selective antagonists of excitatory receptors. Analyses of spine dynamics in hippocampal slice cultures reveals that this effect is mediated through an increased rate of protrusions formation, a better stabilization of newly formed spines, and leads to the formation of functional synapses. Altogether, these findings point to anesthesia as an important modulator of spine dynamics in the developing brain and suggest the existence of a homeostatic process regulating spine formation as a function of neural activity. Importantly, they also raise concern about the potential impact of these drugs on human practice, when applied during critical periods of development in infants.

Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

Directory of Open Access Journals (Sweden)

Siebler Mario

2009-08-01

Full Text Available Abstract Background The present work was performed to investigate the ability of two different embryonic stem (ES cell-derived neural precursor populations to generate functional neuronal networks in vitro. The first ES cell-derived neural precursor population was cultivated as free-floating neural aggregates which are known to form a developmental niche comprising different types of neural cells, including neural precursor cells (NPCs, progenitor cells and even further matured cells. This niche provides by itself a variety of different growth factors and extracellular matrix proteins that influence the proliferation and differentiation of neural precursor and progenitor cells. The second population was cultivated adherently in monolayer cultures to control most stringently the extracellular environment. This population comprises highly homogeneous NPCs which are supposed to represent an attractive way to provide well-defined neuronal progeny. However, the ability of these different ES cell-derived immature neural cell populations to generate functional neuronal networks has not been assessed so far. Results While both precursor populations were shown to differentiate into sufficient quantities of mature NeuN+ neurons that also express GABA or vesicular-glutamate-transporter-2 (vGlut2, only aggregate-derived neuronal populations exhibited a synchronously oscillating network activity 2–4 weeks after initiating the differentiation as detected by the microelectrode array technology. Neurons derived from homogeneous NPCs within monolayer cultures did merely show uncorrelated spiking activity even when differentiated for up to 12 weeks. We demonstrated that these neurons exhibited sparsely ramified neurites and an embryonic vGlut2 distribution suggesting an inhibited terminal neuronal maturation. In comparison, neurons derived from heterogeneous populations within neural aggregates appeared as fully mature with a dense neurite network and punctuated

The Neuroscience of Growth Mindset and Intrinsic Motivation

Directory of Open Access Journals (Sweden)

Betsy Ng

2018-01-01

Full Text Available Our actions can be triggered by intentions, incentives or intrinsic values. Recent neuroscientific research has yielded some results about the growth mindset and intrinsic motivation. With the advances in neuroscience and motivational studies, there is a global need to utilize this information to inform educational practice and research. Yet, little is known about the neuroscientific interplay between growth mindset and intrinsic motivation. This paper attempts to draw on the theories of growth mindset and intrinsic motivation, together with contemporary ideas in neuroscience, outline the potential for neuroscientific research in education. It aims to shed light on the relationship between growth mindset and intrinsic motivation in terms of supporting a growth mindset to facilitate intrinsic motivation through neural responses. Recent empirical research from the educational neuroscience perspective that provides insights into the interplay between growth mindset and intrinsic motivation will also be discussed.

The neural substrates of cognitive flexibility are related to individual differences in preschool irritability: A fNIRS investigation

Directory of Open Access Journals (Sweden)

Yanwei Li

2017-06-01

Full Text Available Preschool (age 3–5 is a phase of rapid development in both cognition and emotion, making this a period in which the neurodevelopment of each domain is particularly sensitive to that of the other. During this period, children rapidly learn how to flexibly shift their attention between competing demands and, at the same time, acquire critical emotion regulation skills to respond to negative affective challenges. The integration of cognitive flexibility and individual differences in irritability may be an important developmental process of early childhood maturation. However, at present it is unclear if they share common neural substrates in early childhood. Our main goal was to examine the neural correlates of cognitive flexibility in preschool children and test for associations with irritability. Forty-six preschool aged children completed a novel, child-appropriate, Stroop task while dorsolateral prefrontal cortex (DLPFC activation was recorded using functional Near Infrared Spectroscopy (fNIRS. Parents rated their child’s irritability. Results indicated that left DLPFC activation was associated with cognitive flexibility and positively correlated with irritability. Right DLPFC activation was also positively correlated with irritability. Results suggest the entwined nature of cognitive and emotional neurodevelopment during a developmental period of rapid and mutual acceleration.

Catch-up Growth Followed by Stagnation: Mexico 1950–2008

OpenAIRE

Timothy Kehoe; Felipe Meza

2011-01-01

In 1950 Mexico entered an economic takeoff and grew rapidly for more than 30 years. Growth stopped during the crises of 1982-1995, despite major reforms, including liberalization of foreign trade and investment. Since then growth has been modest. We analyze the economic history of Mexico 1877-2010. We conclude that the growth 1950-1981 was driven by urbanization, industrialization, and education and that Mexico would have grown even more rapidly if trade and investment had been liberalized so...

Global Mittag-Leffler stability analysis of fractional-order impulsive neural networks with one-side Lipschitz condition.

Science.gov (United States)

Zhang, Xinxin; Niu, Peifeng; Ma, Yunpeng; Wei, Yanqiao; Li, Guoqiang

2017-10-01

This paper is concerned with the stability analysis issue of fractional-order impulsive neural networks. Under the one-side Lipschitz condition or the linear growth condition of activation function, the existence of solution is analyzed respectively. In addition, the existence, uniqueness and global Mittag-Leffler stability of equilibrium point of the fractional-order impulsive neural networks with one-side Lipschitz condition are investigated by the means of contraction mapping principle and Lyapunov direct method. Finally, an example with numerical simulation is given to illustrate the validity and feasibility of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cadmium-induced neural tube defects and fetal growth restriction: Association with disturbance of placental folate transport

International Nuclear Information System (INIS)

Zhang, Gui-Bin; Wang, Hua; Hu, Jun; Guo, Min-Yin; Wang, Ying; Zhou, Yan; Yu, Zhen; Fu, Lin; Chen, Yuan-Hua; Xu, De-Xiang

2016-01-01

Previous studies found that maternal Cd exposure on gestational day (GD)9 caused forelimb ectrodactyly and tail deformity, the characteristic malformations. The aim of the present study was to investigate whether maternal Cd exposure on GD8 induces fetal neural tube defects (NTDs). Pregnant mice were intraperitoneally injected with CdCl 2 (2.5 or 5.0 mg/kg) on GD8. Neither forelimb ectrodactyly nor tail deformity was observed in mice injected with CdCl 2 on GD8. Instead, maternal Cd exposure on GD8 resulted in the incidence of NTDs. Moreover, maternal Cd exposure on GD8 resulted in fetal growth restriction. In addition, maternal Cd exposure on GD8 reduced placental weight and diameter. The internal space of maternal and fetal blood vessels in the labyrinth layer was decreased in the placentas of mice treated with CdCl 2 . Additional experiment showed that placental PCFT protein and mRNA, a critical folate transporter, was persistently decreased when dams were injected with CdCl 2 on GD8. Correspondingly, embryonic folate content was markedly decreased in mice injected with CdCl 2 on GD8, whereas Cd had little effect on folate content in maternal serum. Taken together, these results suggest that maternal Cd exposure during organogenesis disturbs transport of folate from maternal circulation to the fetuses through down-regulating placental folate transporters. - Highlights: • Maternal Cd exposure during organogenesis causes NTDs and FGR. • Maternal Cd exposure during organogenesis impairs placental development. • Cd disturbs transport of folate by down-regulating placental folate transporters.

Cadmium-induced neural tube defects and fetal growth restriction: Association with disturbance of placental folate transport

Energy Technology Data Exchange (ETDEWEB)

Zhang, Gui-Bin; Wang, Hua, E-mail: wanghuadev@126.com; Hu, Jun; Guo, Min-Yin; Wang, Ying; Zhou, Yan; Yu, Zhen; Fu, Lin; Chen, Yuan-Hua; Xu, De-Xiang, E-mail: xudex@126.com

2016-09-01

Previous studies found that maternal Cd exposure on gestational day (GD)9 caused forelimb ectrodactyly and tail deformity, the characteristic malformations. The aim of the present study was to investigate whether maternal Cd exposure on GD8 induces fetal neural tube defects (NTDs). Pregnant mice were intraperitoneally injected with CdCl{sub 2} (2.5 or 5.0 mg/kg) on GD8. Neither forelimb ectrodactyly nor tail deformity was observed in mice injected with CdCl{sub 2} on GD8. Instead, maternal Cd exposure on GD8 resulted in the incidence of NTDs. Moreover, maternal Cd exposure on GD8 resulted in fetal growth restriction. In addition, maternal Cd exposure on GD8 reduced placental weight and diameter. The internal space of maternal and fetal blood vessels in the labyrinth layer was decreased in the placentas of mice treated with CdCl{sub 2}. Additional experiment showed that placental PCFT protein and mRNA, a critical folate transporter, was persistently decreased when dams were injected with CdCl{sub 2} on GD8. Correspondingly, embryonic folate content was markedly decreased in mice injected with CdCl{sub 2} on GD8, whereas Cd had little effect on folate content in maternal serum. Taken together, these results suggest that maternal Cd exposure during organogenesis disturbs transport of folate from maternal circulation to the fetuses through down-regulating placental folate transporters. - Highlights: • Maternal Cd exposure during organogenesis causes NTDs and FGR. • Maternal Cd exposure during organogenesis impairs placental development. • Cd disturbs transport of folate by down-regulating placental folate transporters.

Engineering Biomaterials to Influence Oligodendroglial Growth, Maturation, and Myelin Production.

Science.gov (United States)

Russell, Lauren N; Lampe, Kyle J

2016-01-01

Millions of people suffer from damage or disease to the nervous system that results in a loss of myelin, such as through a spinal cord injury or multiple sclerosis. Diminished myelin levels lead to further cell death in which unmyelinated neurons die. In the central nervous system, a loss of myelin is especially detrimental because of its poor ability to regenerate. Cell therapies such as stem or precursor cell injection have been investigated as stem cells are able to grow and differentiate into the damaged cells; however, stem cell injection alone has been unsuccessful in many areas of neural regeneration. Therefore, researchers have begun exploring combined therapies with biomaterials that promote cell growth and differentiation while localizing cells in the injured area. The regrowth of myelinating oligodendrocytes from neural stem cells through a biomaterials approach may prove to be a beneficial strategy following the onset of demyelination. This article reviews recent advancements in biomaterial strategies for the differentiation of neural stem cells into oligodendrocytes, and presents new data indicating appropriate properties for oligodendrocyte precursor cell growth. In some cases, an increase in oligodendrocyte differentiation alongside neurons is further highlighted for functional improvements where the biomaterial was then tested for increased myelination both in vitro and in vivo. © 2016 S. Karger AG, Basel.

Testing mechanistic models of growth in insects.

Science.gov (United States)

Maino, James L; Kearney, Michael R

2015-11-22

Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes. © 2015 The Author(s).

Visual Perceptual Echo Reflects Learning of Regularities in Rapid Luminance Sequences.

Science.gov (United States)

Chang, Acer Y-C; Schwartzman, David J; VanRullen, Rufin; Kanai, Ryota; Seth, Anil K

2017-08-30

A novel neural signature of active visual processing has recently been described in the form of the "perceptual echo", in which the cross-correlation between a sequence of randomly fluctuating luminance values and occipital electrophysiological signals exhibits a long-lasting periodic (∼100 ms cycle) reverberation of the input stimulus (VanRullen and Macdonald, 2012). As yet, however, the mechanisms underlying the perceptual echo and its function remain unknown. Reasoning that natural visual signals often contain temporally predictable, though nonperiodic features, we hypothesized that the perceptual echo may reflect a periodic process associated with regularity learning. To test this hypothesis, we presented subjects with successive repetitions of a rapid nonperiodic luminance sequence, and examined the effects on the perceptual echo, finding that echo amplitude linearly increased with the number of presentations of a given luminance sequence. These data suggest that the perceptual echo reflects a neural signature of regularity learning.Furthermore, when a set of repeated sequences was followed by a sequence with inverted luminance polarities, the echo amplitude decreased to the same level evoked by a novel stimulus sequence. Crucially, when the original stimulus sequence was re-presented, the echo amplitude returned to a level consistent with the number of presentations of this sequence, indicating that the visual system retained sequence-specific information, for many seconds, even in the presence of intervening visual input. Altogether, our results reveal a previously undiscovered regularity learning mechanism within the human visual system, reflected by the perceptual echo. SIGNIFICANCE STATEMENT How the brain encodes and learns fast-changing but nonperiodic visual input remains unknown, even though such visual input characterizes natural scenes. We investigated whether the phenomenon of "perceptual echo" might index such learning. The perceptual echo is a

Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

Science.gov (United States)

Gros, Claudius

2007-02-01

The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

Towards a neural basis of music perception.

Science.gov (United States)

Koelsch, Stefan; Siebel, Walter A

2005-12-01

Music perception involves complex brain functions underlying acoustic analysis, auditory memory, auditory scene analysis, and processing of musical syntax and semantics. Moreover, music perception potentially affects emotion, influences the autonomic nervous system, the hormonal and immune systems, and activates (pre)motor representations. During the past few years, research activities on different aspects of music processing and their neural correlates have rapidly progressed. This article provides an overview of recent developments and a framework for the perceptual side of music processing. This framework lays out a model of the cognitive modules involved in music perception, and incorporates information about the time course of activity of some of these modules, as well as research findings about where in the brain these modules might be located.

Rapid population growth and environmental degradation: ultimate versus proximate factors.

Science.gov (United States)

Shaw, R P

1989-01-01

This philosophical review of 2 arguments about responsibility for and solutions to environmental degradation concludes that both sides are correct: the ultimate and the proximal causes. Ultimate causes of pollution are defined as the technology responsible for a given type of pollution, such as burning fossil fuel; proximate causes are defined as situation-specific factors confounding the problem, such as population density or rate of growth. Commoner and others argue that developed countries with low or negative population growth rates are responsible for 80% of world pollution, primarily in polluting technologies such as automobiles, power generation, plastics, pesticides, toxic wastes, garbage, warfaring, and nuclear weapons wastes. Distortionary policies also contribute; examples are agricultural trade protection, land mismanagement, urban bias in expenditures, and institutional rigidity., Poor nations are responsible for very little pollution because poverty allows little waste or expenditures for polluting, synthetic technologies. The proximal causes of pollution include numbers and rate of growth of populations responsible for the pollution. Since change in the ultimate cause of pollution remains out of reach, altering the numbers of polluters can make a difference. Predictions are made for proportions of the world's total waste production, assuming current 1.6 tons/capita for developed countries and 0.17 tons/capita for developing countries. If developing countries grow at current rates and become more wealthy, they will be emitting half the world's waste by 2025. ON the other hand, unsustainable population growth goes along with inadequate investment in human capital: education, health, employment, infrastructure. The solution is to improve farming technologies in the 117 non-self-sufficient countries, fund development in the most unsustainable enclaves of growing countries, break institutionalized socio-political rigidity in these enclaves, and focus on

Collagen-embedded hydroxylapatite-beta-tricalcium phosphate-silicon dioxide bone substitute granules assist rapid vascularization and promote cell growth

Energy Technology Data Exchange (ETDEWEB)

Ghanaati, Shahram M; Thimm, Benjamin W; Unger, Ronald E; Orth, Carina; Barbeck, Mike; Kirkpatrick, C James [Institute of Pathology, Johannes Gutenberg-University Mainz, Langenbeckstr.1, 55101 Mainz (Germany); Kohler, Thomas; Mueller, Ralph, E-mail: ghanaati@uni-mainz.d [Institute for Biomechanics, ETH Zuerich, Wolfgang-Pauli-Str.10, 8093 Zuerich (Switzerland)

2010-04-15

In the present study we assessed the biocompatibility in vitro and in vivo of a low-temperature sol-gel-manufactured SiO{sub 2}-based bone graft substitute. Human primary osteoblasts and the osteoblastic cell line, MG63, cultured on the SiO{sub 2} biomatrix in monoculture retained their osteoblastic morphology and cellular functionality in vitro. The effect of the biomaterial in vivo and its vascularization potential was tested subcutaneously in Wistar rats and demonstrated both rapid vascularization and good integration within the peri-implant tissue. Scaffold degradation was progressive during the first month after implantation, with tartrate-resistant acid phosphatase-positive macrophages being present and promoting scaffold degradation from an early stage. This manuscript describes successful osteoblastic growth promotion in vitro and a promising biomaterial integration and vasculogenesis in vivo for a possible therapeutic application of this biomatrix in future clinical studies.

Neural Networks: Implementations and Applications

OpenAIRE

Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

1996-01-01

Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

Nonstimulated human uncommitted mesenchymal stem cells express cell markers of mesenchymal and neural lineages.

Science.gov (United States)

Minguell, José J; Fierro, Fernando A; Epuñan, María J; Erices, Alejandro A; Sierralta, Walter D

2005-08-01

Ex vivo cultures of human bone marrow-derived mesenchymal stem cells (MSCs) contain subsets of progenitors exhibiting dissimilar properties. One of these subsets comprises uncommitted progenitors displaying distinctive features, such as morphology, a quiescent condition, growth factor production, and restricted tissue biodistribution after transplantation. In this study, we assessed the competence of these cells to express, in the absence of differentiation stimuli, markers of mesoderm and ectodermic (neural) cell lineages. Fluorescence microscopy analysis showed a unique pattern of expression of osteogenic, chondrogenic, muscle, and neural markers. The depicted "molecular signature" of these early uncommitted progenitors, in the absence of differentiation stimuli, is consistent with their multipotentiality and plasticity as suggested by several in vitro and in vivo studies.

Neural network control of focal position during time-lapse microscopy of cells.

Science.gov (United States)

Wei, Ling; Roberts, Elijah

2018-05-09

Live-cell microscopy is quickly becoming an indispensable technique for studying the dynamics of cellular processes. Maintaining the specimen in focus during image acquisition is crucial for high-throughput applications, especially for long experiments or when a large sample is being continuously scanned. Automated focus control methods are often expensive, imperfect, or ill-adapted to a specific application and are a bottleneck for widespread adoption of high-throughput, live-cell imaging. Here, we demonstrate a neural network approach for automatically maintaining focus during bright-field microscopy. Z-stacks of yeast cells growing in a microfluidic device were collected and used to train a convolutional neural network to classify images according to their z-position. We studied the effect on prediction accuracy of the various hyperparameters of the neural network, including downsampling, batch size, and z-bin resolution. The network was able to predict the z-position of an image with ±1 μm accuracy, outperforming human annotators. Finally, we used our neural network to control microscope focus in real-time during a 24 hour growth experiment. The method robustly maintained the correct focal position compensating for 40 μm of focal drift and was insensitive to changes in the field of view. About ~100 annotated z-stacks were required to train the network making our method quite practical for custom autofocus applications.

Cortical bone growth and maturational changes in dwarf rats induced by recombinant human growth hormone

Science.gov (United States)

Martinez, D. A.; Orth, M. W.; Carr, K. E.; Vanderby, R. Jr; Vailas, A. C.

1996-01-01

The growth hormone (GH)-deficient dwarf rat was used to investigate recombinant human (rh) GH-induced bone formation and to determine whether rhGH facilitates simultaneous increases in bone formation and bone maturation during rapid growth. Twenty dwarf rats, 37 days of age, were randomly assigned to dwarf plus rhGH (GH; n = 10) and dwarf plus vehicle (n = 10) groups. The GH group received 1.25 mg rhGH/kg body wt two times daily for 14 days. Biochemical, morphological, and X-ray diffraction measurements were performed on the femur middiaphysis. rhGH stimulated new bone growth in the GH group, as demonstrated by significant increases (P bone length (6%), middiaphyseal cross-sectional area (20%), and the amount of newly accreted bone collagen (28%) in the total pool of middiaphyseal bone collagen. Cortical bone density, mean hydroxyapatite crystal size, and the calcium and collagen contents (microgram/mm3) were significantly smaller in the GH group (P bone collagen maturation, and mean hydroxyapatite crystal size may be independently regulated during rapid growth.

The Chinese-born immigrant infant feeding and growth hypothesis

Directory of Open Access Journals (Sweden)

Kristy A. Bolton

2016-10-01

Full Text Available Abstract Background Rapid growth in the first six months of life is a well-established risk factor for childhood obesity, and child feeding practices (supplementation or substitution of breast milk with formula and early introduction of solids have been reported to predict this. The third largest immigrant group in Australia originate from China. Case-studies reported from Victorian Maternal and Child Health nurses suggest that rapid growth trajectories in the infants of Chinese parents is common place. Furthermore, these nurses report that high value is placed by this client group on rapid growth and a fatter child; that rates of breastfeeding are low and overfeeding of infant formula is high. There are currently no studies which describe infant growth or its correlates among this immigrant group. Presentation of hypothesis We postulate that in Australia, Chinese-born immigrant mothers will have different infant feeding practices compared to non-immigrant mothers and this will result in different growth trajectories and risk of overweight. We present the Chinese-born immigrant infant feeding and growth hypothesis - that less breastfeeding, high formula feeding and early introduction of solids in infants of Chinese-born immigrant mothers living in Australia will result in a high protein intake and subsequent rapid growth trajectory and increased risk of overweight and obesity. Testing the hypothesis Three related studies will be conducted to investigate the hypothesis. These will include two quantitative studies (one cross-sectional, one longitudinal and a qualitative study. The quantitative studies will investigate differences in feeding practices in Chinese-born immigrant compared to non-immigrant mothers and infants; and the growth trajectories over the first 3.5 years of life. The qualitative study will provide more in-depth understanding of the influencing factors on feeding practices in Chinese-born immigrant mothers. Implications of the

A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm

Directory of Open Access Journals (Sweden)

Yu-xin Zhao

2014-01-01

Full Text Available This paper presents a novel wavelet kernel neural network (WKNN with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID controller, which could handle time delay problem of the complex control system. Combining the wavelet function and the kernel function, the wavelet kernel function is adopted and validated the availability for neural network. Compared to the conservative wavelet neural network, the most innovative character of the WKNN is its rapid convergence and high precision in parameters updating process. Furthermore, the integrated pressurized water reactor (IPWR system is established by RELAP5, and a novel control strategy combining WKNN and fuzzy logic rule is proposed for shortening controlling time and utilizing the experiential knowledge sufficiently. Finally, experiment results verify that the control strategy and controller proposed have the practicability and reliability in actual complicated system.

Maximizing performance of fuel cell using artificial neural network approach for smart grid applications

International Nuclear Information System (INIS)

Bicer, Y.; Dincer, I.; Aydin, M.

2016-01-01

This paper presents an artificial neural network (ANN) approach of a smart grid integrated proton exchange membrane (PEM) fuel cell and proposes a neural network model of a 6 kW PEM fuel cell. The data required to train the neural network model are generated by a model of 6 kW PEM fuel cell. After the model is trained and validated, it is used to analyze the dynamic behavior of the PEM fuel cell. The study results demonstrate that the model based on neural network approach is appropriate for predicting the outlet parameters. Various types of training methods, sample numbers and sample distribution methods are utilized to compare the results. The fuel cell stack efficiency considerably varies between 20% and 60%, according to input variables and models. The rapid changes in the input variables can be recovered within a short time period, such as 10 s. The obtained response graphs point out the load tracking features of ANN model and the projected changes in the input variables are controlled quickly in the study. - Highlights: • An ANN approach of a proton exchange membrane (PEM) fuel cell is proposed. • Dynamic behavior of the PEM fuel cell is analyzed. • The effects of various variables on model accuracy are investigated. • Response curves indicate the load following characteristics of the model.

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

Science.gov (United States)

Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

2002-01-01

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic

Integrative analysis of genes and miRNA alterations in human embryonic stem cells-derived neural cells after exposure to silver nanoparticles.

Science.gov (United States)

Oh, Jung-Hwa; Son, Mi-Young; Choi, Mi-Sun; Kim, Soojin; Choi, A-Young; Lee, Hyang-Ae; Kim, Ki-Suk; Kim, Janghwan; Song, Chang Woo; Yoon, Seokjoo

2016-05-15

Given the rapid growth of engineered and customer products made of silver nanoparticles (Ag NPs), understanding their biological and toxicological effects on humans is critically important. The molecular developmental neurotoxic effects associated with exposure to Ag NPs were analyzed at the physiological and molecular levels, using an alternative cell model: human embryonic stem cell (hESC)-derived neural stem/progenitor cells (NPCs). In this study, the cytotoxic effects of Ag NPs (10-200μg/ml) were examined in these hESC-derived NPCs, which have a capacity for neurogenesis in vitro, at 6 and 24h. The results showed that Ag NPs evoked significant toxicity in hESC-derived NPCs at 24h in a dose-dependent manner. In addition, Ag NPs induced cell cycle arrest and apoptosis following a significant increase in oxidative stress in these cells. To further clarify the molecular mechanisms of the toxicological effects of Ag NPs at the transcriptional and post-transcriptional levels, the global expression profiles of genes and miRNAs were analyzed in hESC-derived NPCs after Ag NP exposure. The results showed that Ag NPs induced oxidative stress and dysfunctional neurogenesis at the molecular level in hESC-derived NPCs. Based on this hESC-derived neural cell model, these findings have increased our understanding of the molecular events underlying developmental neurotoxicity induced by Ag NPs in humans. Copyright © 2015 Elsevier Inc. All rights reserved.

Neurophysiology and neural engineering: a review.

Science.gov (United States)

Prochazka, Arthur

2017-08-01

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

NARCIS (Netherlands)

D. Zambrano (Davide); S.M. Bohte (Sander)

2016-01-01

textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

Alterations of Growth Factors in Autism and Attention-Deficit/Hyperactivity Disorder

Directory of Open Access Journals (Sweden)

Alma Y. Galvez-Contreras

2017-07-01

Full Text Available Growth factors (GFs are cytokines that regulate the neural development. Recent evidence indicates that alterations in the expression level of GFs during embryogenesis are linked to the pathophysiology and clinical manifestations of attention-deficit/hyperactivity disorder (ADHD and autism spectrum disorders (ASD. In this concise review, we summarize the current evidence that supports the role of brain-derived neurotrophic factor, insulin-like growth factor 2, hepatocyte growth factor (HGF, glial-derived neurotrophic factor, nerve growth factor, neurotrophins 3 and 4, and epidermal growth factor in the pathogenesis of ADHD and ASD. We also highlight the potential use of these GFs as clinical markers for diagnosis and prognosis of these neurodevelopmental disorders.

Alterations of Growth Factors in Autism and Attention-Deficit/Hyperactivity Disorder

Science.gov (United States)

Galvez-Contreras, Alma Y.; Campos-Ordonez, Tania; Gonzalez-Castaneda, Rocio E.; Gonzalez-Perez, Oscar

2017-01-01

Growth factors (GFs) are cytokines that regulate the neural development. Recent evidence indicates that alterations in the expression level of GFs during embryogenesis are linked to the pathophysiology and clinical manifestations of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD). In this concise review, we summarize the current evidence that supports the role of brain-derived neurotrophic factor, insulin-like growth factor 2, hepatocyte growth factor (HGF), glial-derived neurotrophic factor, nerve growth factor, neurotrophins 3 and 4, and epidermal growth factor in the pathogenesis of ADHD and ASD. We also highlight the potential use of these GFs as clinical markers for diagnosis and prognosis of these neurodevelopmental disorders. PMID:28751869

Generation of Regionally Specified Neural Progenitors and Functional Neurons from Human Embryonic Stem Cells under Defined Conditions

Directory of Open Access Journals (Sweden)

Agnete Kirkeby

2012-06-01

Full Text Available To model human neural-cell-fate specification and to provide cells for regenerative therapies, we have developed a method to generate human neural progenitors and neurons from human embryonic stem cells, which recapitulates human fetal brain development. Through the addition of a small molecule that activates canonical WNT signaling, we induced rapid and efficient dose-dependent specification of regionally defined neural progenitors ranging from telencephalic forebrain to posterior hindbrain fates. Ten days after initiation of differentiation, the progenitors could be transplanted to the adult rat striatum, where they formed neuron-rich and tumor-free grafts with maintained regional specification. Cells patterned toward a ventral midbrain (VM identity generated a high proportion of authentic dopaminergic neurons after transplantation. The dopamine neurons showed morphology, projection pattern, and protein expression identical to that of human fetal VM cells grafted in parallel. VM-patterned but not forebrain-patterned neurons released dopamine and reversed motor deficits in an animal model of Parkinson's disease.

Portable Diagnostics and Rapid Germination

Energy Technology Data Exchange (ETDEWEB)

Dunn, Zachary Spencer [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-12-01

In the Bioenergy and Defense Department of Sandia National Laboratories, characterization of the BaDx (Bacillus anthracis diagnostic cartridge) was performed and rapid germination chemistry was investigated. BaDx was tested with complex sample matrixes inoculated with Bacillus anthracis, and the trials proved that BaDx will detect Bacillus anthracis in a variety of the medium, such as dirt, serum, blood, milk, and horse fluids. The dimensions of the device were altered to accommodate an E. coli or Listeria lateral flow immunoassay, and using a laser printer, BaDx devices were manufactured to identify E. coli and Listeria. Initial testing with E. coli versions of BaDx indicate that the device will be viable as a portable diagnostic cartridge. The device would be more effective with faster bacteria germination; hence studies were performed the use of rapid germination chemistry. Trials with calcium dipicolinic acid displayed increased cell germination, as shown by control studies using a microplate reader. Upon lyophilization the rapid germination chemistry failed to change growth patterns, indicating that the calcium dipicolinic acid was not solubilized under the conditions tested. Although incompatible with the portable diagnostic device, the experiments proved that the rapid germination chemistry was effective in increasing cell germination.

A role for adult TLX-positive neural stem cells in learning and behaviour.

Science.gov (United States)

Zhang, Chun-Li; Zou, Yuhua; He, Weimin; Gage, Fred H; Evans, Ronald M

2008-02-21

Neurogenesis persists in the adult brain and can be regulated by a plethora of external stimuli, such as learning, memory, exercise, environment and stress. Although newly generated neurons are able to migrate and preferentially incorporate into the neural network, how these cells are molecularly regulated and whether they are required for any normal brain function are unresolved questions. The adult neural stem cell pool is composed of orphan nuclear receptor TLX-positive cells. Here, using genetic approaches in mice, we demonstrate that TLX (also called NR2E1) regulates adult neural stem cell proliferation in a cell-autonomous manner by controlling a defined genetic network implicated in cell proliferation and growth. Consequently, specific removal of TLX from the adult mouse brain through inducible recombination results in a significant reduction of stem cell proliferation and a marked decrement in spatial learning. In contrast, the resulting suppression of adult neurogenesis does not affect contextual fear conditioning, locomotion or diurnal rhythmic activities, indicating a more selective contribution of newly generated neurons to specific cognitive functions.

Ferritin nanoparticles for improved self-renewal and differentiation of human neural stem cells.

Science.gov (United States)

Lee, Jung Seung; Yang, Kisuk; Cho, Ann-Na; Cho, Seung-Woo

2018-01-01

Biomaterials that promote the self-renewal ability and differentiation capacity of neural stem cells (NSCs) are desirable for improving stem cell therapy to treat neurodegenerative diseases. Incorporation of micro- and nanoparticles into stem cell culture has gained great attention for the control of stem cell behaviors, including proliferation and differentiation. In this study, ferritin, an iron-containing natural protein nanoparticle, was applied as a biomaterial to improve the self-renewal and differentiation of NSCs and neural progenitor cells (NPCs). Ferritin nanoparticles were added to NSC or NPC culture during cell growth, allowing for incorporation of ferritin nanoparticles during neurosphere formation. Compared to neurospheres without ferritin treatment, neurospheres with ferritin nanoparticles showed significantly promoted self-renewal and cell-cell interactions. When spontaneous differentiation of neurospheres was induced during culture without mitogenic factors, neuronal differentiation was enhanced in the ferritin-treated neurospheres. In conclusion, we found that natural nanoparticles can be used to improve the self-renewal ability and differentiation potential of NSCs and NPCs, which can be applied in neural tissue engineering and cell therapy for neurodegenerative diseases.

Artificial neural networks in NDT

International Nuclear Information System (INIS)

Abdul Aziz Mohamed

2001-01-01

Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

Connective-Tissue Growth Factor (CTGF/CCN2 Induces Astrogenesis and Fibronectin Expression of Embryonic Neural Cells In Vitro.

Directory of Open Access Journals (Sweden)

Fabio A Mendes

Full Text Available Connective-tissue growth factor (CTGF is a modular secreted protein implicated in multiple cellular events such as chondrogenesis, skeletogenesis, angiogenesis and wound healing. CTGF contains four different structural modules. This modular organization is characteristic of members of the CCN family. The acronym was derived from the first three members discovered, cysteine-rich 61 (CYR61, CTGF and nephroblastoma overexpressed (NOV. CTGF is implicated as a mediator of important cell processes such as adhesion, migration, proliferation and differentiation. Extensive data have shown that CTGF interacts particularly with the TGFβ, WNT and MAPK signaling pathways. The capacity of CTGF to interact with different growth factors lends it an important role during early and late development, especially in the anterior region of the embryo. ctgf knockout mice have several cranio-facial defects, and the skeletal system is also greatly affected due to an impairment of the vascular-system development during chondrogenesis. This study, for the first time, indicated that CTGF is a potent inductor of gliogenesis during development. Our results showed that in vitro addition of recombinant CTGF protein to an embryonic mouse neural precursor cell culture increased the number of GFAP- and GFAP/Nestin-positive cells. Surprisingly, CTGF also increased the number of Sox2-positive cells. Moreover, this induction seemed not to involve cell proliferation. In addition, exogenous CTGF activated p44/42 but not p38 or JNK MAPK signaling, and increased the expression and deposition of the fibronectin extracellular matrix protein. Finally, CTGF was also able to induce GFAP as well as Nestin expression in a human malignant glioma stem cell line, suggesting a possible role in the differentiation process of gliomas. These results implicate ctgf as a key gene for astrogenesis during development, and suggest that its mechanism may involve activation of p44/42 MAPK signaling

[Effect of antepartum taurine supplementation in regulating the activity of Rho family factors and promoting the proliferation of neural stem cells in neonatal rats with fetal growth restriction].

Science.gov (United States)

Li, Xiang-Wen; Li, Fang; Liu, Jing; Wang, Yan; Fu, Wei

2016-11-01

To study the possible effect of antepartum taurine supplementation in regulating the activity of Rho family factors and promoting the proliferation of neural stem cells in neonatal rats with fetal growth restriction (FGR), and to provide a basis for antepartum taurine supplementation to promote brain development in children with FGR. A total of 24 pregnant Sprague-Dawley rats were randomly divided into three groups: control, FGR, and taurine (n=8 each ). A rat model of FGR was established by food restriction throughout pregnancy. RT-PCR, immunohistochemistry, and Western blot were used to measure the expression of the specific intracellular markers for neural stem cells fatty acid binding protein 7 (FABP7), Rho-associated coiled-coil containing protein kinase 2 (ROCK2), ras homolog gene family, member A (RhoA), and Ras-related C3 botulinum toxin substrate (Rac). The FGR group had significantly lower OD value of FABP7-positive cells and mRNA and protein expression of FABP7 than the control group, and the taurine group had significantly higher OD value of FABP7-positive cells and mRNA and protein expression of FABP7 than the FGR group (Ptaurine group had significantly higher mRNA expression of RhoA and ROCK2 than the control group and significantly lower expression than the FGR group (Ptaurine group had significantly higher mRNA expression of Rac than the FGR and control groups (Ptaurine group had significantly lower protein expression of RhoA and ROCK2 than the FGR group (Ptaurine supplementation can promote the proliferation of neural stem cells in rats with FGR, and its mechanism may be related to the regulation of the activity of Rho family factors.

Uncooled infrared sensors: rapid growth and future perspective

Science.gov (United States)

Balcerak, Raymond S.

2000-07-01

The uncooled infrared cameras are now available for both the military and commercial markets. The current camera technology incorporates the fruits of many years of development, focusing on the details of pixel design, novel material processing, and low noise read-out electronics. The rapid insertion of cameras into systems is testimony to the successful completion of this 'first phase' of development. In the military market, the first uncooled infrared cameras will be used for weapon sights, driver's viewers and helmet mounted cameras. Major commercial applications include night driving, security, police and fire fighting, and thermography, primarily for preventive maintenance and process control. The technology for the next generation of cameras is even more demanding, but within reach. The paper outlines the technology program planned for the next generation of cameras, and the approaches to further enhance performance, even to the radiation limit of thermal detectors.

Integration of Neural Networks and Cellular Automata for Urban Planning

Institute of Scientific and Technical Information of China (English)

Anthony Gar-on Yeh; LI Xia

2004-01-01

This paper presents a new type of cellular automata (CA) model for the simulation of alternative land development using neural networks for urban planning. CA models can be regarded as a planning tool because they can generate alternative urban growth. Alternative development patterns can be formed by using different sets of parameter values in CA simulation. A critical issue is how to define parameter values for realistic and idealized simulation. This paper demonstrates that neural networks can simplify CA models but generate more plausible results. The simulation is based on a simple three-layer network with an output neuron to generate conversion probability. No transition rules are required for the simulation. Parameter values are automatically obtained from the training of network by using satellite remote sensing data. Original training data can be assessed and modified according to planning objectives. Alternative urban patterns can be easily formulated by using the modified training data sets rather than changing the model.

Inverse Solutionof BP Neural Network for Laser Ｒemelting Parameters

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LIU Li-jun

2017-06-01

Full Text Available Aim at highly nonlinear mapping relationship between the laser processing parameters and the melting cell body’s transverse size，a method of reverse engineering laser melting parameters by back － propagation ( BP neural network was put forward． The model was constructed by BP neural network，and the prediction error was reduced to less than 3% after training for many times． The DIEVAＲ die steel was melted by reverse engineering laser parameters，and the results show that the error was 1． 33% between the transverse dimensions of the melting cell body and the expected，the expected precision can be met well． Thermal fatigue property of the melted and non － melted DIEVAＲ die steel has been studied． The analysis about cracks growth presents that thermal fatigue property of DIEVAＲ die steel melted by the reverse engineering parameters has been greatly improved． The melting cell body could block crack effectively．

Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

Science.gov (United States)

Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

2017-10-01

This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

Eye size at birth in prosimian primates: life history correlates and growth patterns.

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Joshua R Cummings

Full Text Available BACKGROUND: Primates have large eyes relative to head size, which profoundly influence the ontogenetic emergence of facial form. However, growth of the primate eye is only understood in a narrow taxonomic perspective, with information biased toward anthropoids. METHODOLOGY/PRINCIPAL FINDINGS: We measured eye and bony orbit size in perinatal prosimian primates (17 strepsirrhine taxa and Tarsius syrichta to infer the extent of prenatal as compared to postnatal eye growth. In addition, multiple linear regression was used to detect relationships of relative eye and orbit diameter to life history variables. ANOVA was used to determine if eye size differed according to activity pattern. In most of the species, eye diameter at birth measures more than half of that for adults. Two exceptions include Nycticebus and Tarsius, in which more than half of eye diameter growth occurs postnatally. Ratios of neonate/adult eye and orbit diameters indicate prenatal growth of the eye is actually more rapid than that of the orbit. For example, mean neonatal transverse eye diameter is 57.5% of the adult value (excluding Nycticebus and Tarsius, compared to 50.8% for orbital diameter. If Nycticebus is excluded, relative gestation age has a significant positive correlation with relative eye diameter in strepsirrhines, explaining 59% of the variance in relative transverse eye diameter. No significant differences were found among species with different activity patterns. CONCLUSIONS/SIGNIFICANCE: The primate developmental strategy of relatively long gestations is probably tied to an extended period of neural development, and this principle appears to apply to eye growth as well. Our findings indicate that growth rates of the eye and bony orbit are disassociated, with eyes growing faster prenatally, and the growth rate of the bony orbit exceeding that of the eyes after birth. Some well-documented patterns of orbital morphology in adult primates, such as the enlarged orbits

Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

Science.gov (United States)

Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

2015-01-01

Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

A new perspective on behavioral inconsistency and neural noise in aging: Compensatory speeding of neural communication

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S. Lee Hong

2012-09-01

Full Text Available This paper seeks to present a new perspective on the aging brain. Here, we make connections between two key phenomena of brain aging: 1 increased neural noise or random background activity; and 2 slowing of brain activity. Our perspective proposes the possibility that the slowing of neural processing due to decreasing nerve conduction velocities leads to a compensatory speeding of neuron firing rates. These increased firing rates lead to a broader distribution of power in the frequency spectrum of neural oscillations, which we propose, can just as easily be interpreted as neural noise. Compensatory speeding of neural activity, as we present, is constrained by the: A availability of metabolic energy sources; and B competition for frequency bandwidth needed for neural communication. We propose that these constraints lead to the eventual inability to compensate for age-related declines in neural function that are manifested clinically as deficits in cognition, affect, and motor behavior.

Colorimetry provides a rapid objective measurement of de novo hair growth rate in mice.

Science.gov (United States)

Tzung, Tien-Yi; Yang, Chia-Yi; Huang, Yung-Chang; Kao, Fu-Jen

2009-11-01

Depilated mice have been used as a test platform for hair growth-regulating agents. However, currently available assessment tools for hair growth in mice are less than ideal. Tristimulus colorimetry of the fur color of depilated agouti, albino, and black mice with L*, a*, and b* values were performed daily until the full growth of pelage. Using light-emitting diode (LED) irradiation (650 and 890 nm) with a daily dose of 3.5 J/cm(2) as hair growth regulators, the hair growth rates observed by the global assessment were compared with those derived from colorimetry. In contrast to a* and b* values, L* values changed more drastically over time in the anagen phase regardless of fur color. Unlike the inhibitory effect of 650 nm irradiation, LED of 890 nm promoted de novo hair regrowth in mice. The difference in hair growth rates detected by colorimetry paralleled the observation made by the global assessment. The L* value of fur color obtained by tristimulus colorimetry was a sensitive yet quantitative indicator of de novo hair growth, and could be used to project the hair growth rate in mice.

Episodic Memory Retrieval Functionally Relies on Very Rapid Reactivation of Sensory Information.

Science.gov (United States)

Waldhauser, Gerd T; Braun, Verena; Hanslmayr, Simon

2016-01-06

Episodic memory retrieval is assumed to rely on the rapid reactivation of sensory information that was present during encoding, a process termed "ecphory." We investigated the functional relevance of this scarcely understood process in two experiments in human participants. We presented stimuli to the left or right of fixation at encoding, followed by an episodic memory test with centrally presented retrieval cues. This allowed us to track the reactivation of lateralized sensory memory traces during retrieval. Successful episodic retrieval led to a very early (∼100-200 ms) reactivation of lateralized alpha/beta (10-25 Hz) electroencephalographic (EEG) power decreases in the visual cortex contralateral to the visual field at encoding. Applying rhythmic transcranial magnetic stimulation to interfere with early retrieval processing in the visual cortex led to decreased episodic memory performance specifically for items encoded in the visual field contralateral to the site of stimulation. These results demonstrate, for the first time, that episodic memory functionally relies on very rapid reactivation of sensory information. Remembering personal experiences requires a "mental time travel" to revisit sensory information perceived in the past. This process is typically described as a controlled, relatively slow process. However, by using electroencephalography to measure neural activity with a high time resolution, we show that such episodic retrieval entails a very rapid reactivation of sensory brain areas. Using transcranial magnetic stimulation to alter brain function during retrieval revealed that this early sensory reactivation is causally relevant for conscious remembering. These results give first neural evidence for a functional, preconscious component of episodic remembering. This provides new insight into the nature of human memory and may help in the understanding of psychiatric conditions that involve the automatic intrusion of unwanted memories. Copyright

Growth and Growth hormone - Insulin Like Growth Factor -I (GH-IGF-I) Axis in Chronic Anemias.

Science.gov (United States)

Soliman, Ashraf T; De Sanctis, Vincenzo; Yassin, Mohamed; Adel, Ashraf

2017-04-28

Anaemia is a global public health problem affecting both developing and developed countries with major consequences for human health as well as social and economic development. It occurs at all stages of the life cycle, but is more prevalent in pregnant women and young children. Iron deficiency anaemia (IDA) was considered to be among the most important contributing factors to the global burden of disease. Prolonged and/or chronic anemia has a negative effect on linear growth especially during the rapid phases (infancy and puberty). Additionally infants with chronic IDA have delayed cognitive, motor, and affective development that may be long-lasting. In view of the significant impact of chronic anemias on growth, pediatricians endocrinologists and hematologists should advocate primary prevention and screening for growth disturbance in these forms of anemias. The extent of the negative effect of different forms of chronic anemias on linear growth and its possible reversibilty is addressed in this review. The possible mechanisms that may impair growth in the different forms of anemias are addressed with special attention to their effect on the growth hormone (GH) - insulin like growth factor -I (IGF-I).

Sequential neural models with stochastic layers

DEFF Research Database (Denmark)

Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

2016-01-01

How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

Isolation, characterization, and differentiation of multipotent neural progenitor cells from human cerebrospinal fluid in fetal cystic myelomeningocele

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Mario Marotta

2017-07-01

Full Text Available Despite benefits of prenatal in utero repair of myelomeningocele, a severe type of spina bifida aperta, many of these patients will still suffer mild to severe impairment. One potential source of stem cells for new regenerative medicine-based therapeutic approaches for spinal cord injury repair is neural progenitor cells (NPCs in cerebrospinal fluid (CSF. To this aim, we extracted CSF from the cyst surrounding the exposed neural placode during the surgical repair of myelomeningocele in 6 fetuses (20 to 26 weeks of gestation. In primary cultured CSF-derived cells, neurogenic properties were confirmed by in vitro differentiation into various neural lineage cell types, and NPC markers expression (TBR2, CD15, SOX2 were detected by immunofluorescence and RT-PCR analysis. Differentiation into three neural lineages was corroborated by arbitrary differentiation (depletion of growths factors or explicit differentiation as neuronal, astrocyte, or oligodendrocyte cell types using specific induction mediums. Differentiated cells showed the specific expression of neural differentiation markers (βIII-tubulin, GFAP, CNPase, oligo-O1. In myelomeningocele patients, CSF-derived cells could become a potential source of NPCs with neurogenic capacity. Our findings support the development of innovative stem-cell-based therapeutics by autologous transplantation of CSF-derived NPCs in damaged spinal cords, such as myelomeningocele, thus promoting neural tissue regeneration in fetuses.

Implantable liquid metal-based flexible neural microelectrode array and its application in recovering animal locomotion functions

Science.gov (United States)

Guo, Rui; Liu, Jing

2017-10-01

With significant advantages in rapidly restoring the nerve function, electrical stimulation of nervous tissue is a crucial treatment of peripheral nerve injuries leading to common movement disorder. However, the currently available stimulating electrodes generally based on rigid conductive materials would cause a potential mechanical mismatch with soft neural tissues which thus reduces long-term effects of electrical stimulation. Here, we proposed and fabricated a flexible neural microelectrode array system based on the liquid metal GaIn alloy (75.5% Ga and 24.5% In by weight) and via printing approach. Such an alloy with a unique low melting point (10.35 °C) owns excellent electrical conductivity and high compliance, which are beneficial to serve as implantable flexible neural electrodes. The flexible neural microelectrode array embeds four liquid metal electrodes and stretchable interconnects in a PDMS membrane (500 µm in thickness) that possess a lower elastic modulus (1.055 MPa), which is similar to neural tissues with elastic moduli in the 0.1-1.5 MPa range. The electrical experiments indicate that the liquid metal interconnects could sustain over 7000 mechanical stretch cycles with resistance approximately staying at 4 Ω. Over the conceptual experiments on animal sciatic nerve electrical stimulation, the dead bullfrog implanted with flexible neural microelectrode array could even rhythmically contract and move its lower limbs under the electrical stimulations from the implant. This demonstrates a highly efficient way for quickly recovering biological nerve functions. Further, the good biocompatibility of the liquid metal material was justified via a series of biological experiments. This liquid metal modality for neural stimulation is expected to play important roles as biologic electrodes to overcome the fundamental mismatch in mechanics between biological tissues and electronic devices in the coming time.

Implantable liquid metal-based flexible neural microelectrode array and its application in recovering animal locomotion functions

International Nuclear Information System (INIS)

Guo, Rui; Liu, Jing

2017-01-01

With significant advantages in rapidly restoring the nerve function, electrical stimulation of nervous tissue is a crucial treatment of peripheral nerve injuries leading to common movement disorder. However, the currently available stimulating electrodes generally based on rigid conductive materials would cause a potential mechanical mismatch with soft neural tissues which thus reduces long-term effects of electrical stimulation. Here, we proposed and fabricated a flexible neural microelectrode array system based on the liquid metal GaIn alloy (75.5% Ga and 24.5% In by weight) and via printing approach. Such an alloy with a unique low melting point (10.35 °C) owns excellent electrical conductivity and high compliance, which are beneficial to serve as implantable flexible neural electrodes. The flexible neural microelectrode array embeds four liquid metal electrodes and stretchable interconnects in a PDMS membrane (500 µ m in thickness) that possess a lower elastic modulus (1.055 MPa), which is similar to neural tissues with elastic moduli in the 0.1–1.5 MPa range. The electrical experiments indicate that the liquid metal interconnects could sustain over 7000 mechanical stretch cycles with resistance approximately staying at 4 Ω. Over the conceptual experiments on animal sciatic nerve electrical stimulation, the dead bullfrog implanted with flexible neural microelectrode array could even rhythmically contract and move its lower limbs under the electrical stimulations from the implant. This demonstrates a highly efficient way for quickly recovering biological nerve functions. Further, the good biocompatibility of the liquid metal material was justified via a series of biological experiments. This liquid metal modality for neural stimulation is expected to play important roles as biologic electrodes to overcome the fundamental mismatch in mechanics between biological tissues and electronic devices in the coming time. (paper)

Electricity, growth and development in India

International Nuclear Information System (INIS)

Debeir, Jean-Claude

2014-01-01

In India, the revenue generated by rapid economic growth have been used neither to relieve the enormous social injustices affecting the oppressed, nor to develop the physical-and especially electric power-infrastructure in a determined and planned way. This growth has not reduced poverty, and it has caused huge ecological degradations

Rapid detection of small oscillation faults via deterministic learning.

Science.gov (United States)

Wang, Cong; Chen, Tianrui

2011-08-01

Detection of small faults is one of the most important and challenging tasks in the area of fault diagnosis. In this paper, we present an approach for the rapid detection of small oscillation faults based on a recently proposed deterministic learning (DL) theory. The approach consists of two phases: the training phase and the test phase. In the training phase, the system dynamics underlying normal and fault oscillations are locally accurately approximated through DL. The obtained knowledge of system dynamics is stored in constant radial basis function (RBF) networks. In the diagnosis phase, rapid detection is implemented. Specially, a bank of estimators are constructed using the constant RBF neural networks to represent the training normal and fault modes. By comparing the set of estimators with the test monitored system, a set of residuals are generated, and the average L(1) norms of the residuals are taken as the measure of the differences between the dynamics of the monitored system and the dynamics of the training normal mode and oscillation faults. The occurrence of a test oscillation fault can be rapidly detected according to the smallest residual principle. A rigorous analysis of the performance of the detection scheme is also given. The novelty of the paper lies in that the modeling uncertainty and nonlinear fault functions are accurately approximated and then the knowledge is utilized to achieve rapid detection of small oscillation faults. Simulation studies are included to demonstrate the effectiveness of the approach.

Influence of catch-up growth on abdominal fat distribution in very low birth weight children - cohort study.

Science.gov (United States)

Alves, João Guilherme; Vasconcelos, Sarita Amorim; de Almeida, Tais Sá; Lages, Raquel; Just, Eduardo

2015-01-01

A rapid catch-up growth in very low birth weight has been associated both with a higher height growth and a higher risk to metabolic disturbances, including insulin resistance and its consequences. Abdominal fat distribution in early postnatal life may play a role in these outcomes and can help in addressing this neonatal dilemma. This study aimed to compare abdominal fat distribution among very low birth weight (VLBW) children with and without rapid catch-up growth. A cohort study followed 86 VLBW (children born in Brazil, during the first 3 years of life. Rapid catch-up growth was considered as an increased in length >2 Z score during the first year of life. Abdominal subcutaneous and preperitoneal fat thickness was determined by ultrasound. χ²-Test and Student's t-test were used to compare the groups. A total of 79 VLBW children completed the study, of whom 22 (27.8%) showed rapid catch-up growth. Abdominal subcutaneous and preperitoneal fat thickness showed no differences among children with or without rapid catch-up growth at 3.3 mm vs. 3.8 mm, respectively (p=0.79) and 4.0 mm vs. 4.0 mm (p=0.55), respectively. VLBW children with rapid catch-up growth were also taller. Rapid catch-up growth during the first year of life in VLBW children does not seem to change abdominal fat distribution until the third year of life.

Embracing the River: Smart Growth Strategies for Assisting in Cedar Rapids' Recovery

Science.gov (United States)

This report from an EPA-FEMA technical assistance project with Cedar Rapids, IA, offers ideas to encourage infill development, make development more resilient to floods, and improve stormwater management.

Ictal SPECT in patients with rapid eye movement sleep behaviour disorder.

Science.gov (United States)

Mayer, Geert; Bitterlich, Marion; Kuwert, Torsten; Ritt, Philipp; Stefan, Hermann

2015-05-01

-the neural activity generating movement during episodes of rapid eye movement sleep behaviour disorder bypasses the basal ganglia, a mechanism that is shared by patients with idiopathic rapid eye movement sleep behaviour disorder and narcolepsy patients with rapid eye movement sleep behaviour disorder. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Galaxy interactions trigger rapid black hole growth: An unprecedented view from the Hyper Suprime-Cam survey

Science.gov (United States)

Goulding, Andy D.; Greene, Jenny E.; Bezanson, Rachel; Greco, Johnny; Johnson, Sean; Leauthaud, Alexie; Matsuoka, Yoshiki; Medezinski, Elinor; Price-Whelan, Adrian M.

2018-01-01

Collisions and interactions between gas-rich galaxies are thought to be pivotal stages in their formation and evolution, causing the rapid production of new stars, and possibly serving as a mechanism for fueling supermassive black holes (BHs). Harnessing the exquisite spatial resolution (˜0{^''.}5) afforded by the first ˜170 deg2 of the Hyper Suprime-Cam (HSC) survey, we present our new constraints on the importance of galaxy-galaxy major mergers (1 : 4) in growing BHs throughout the last ˜8 Gyr. Utilizing mid-infrared observations in the WISE all-sky survey, we robustly select active galactic nuclei (AGN) and mass-matched control galaxy samples, totaling ˜140000 spectroscopically confirmed systems at i based on our comparison of AGN fractions in mass-matched samples, we determine that the most luminous AGN population (LAGN ≳ 1045 erg s-1) systematically reside in merging systems over non-interacting galaxies. Our findings show that galaxy-galaxy interactions do, on average, trigger luminous AGN activity substantially more often than in secularly evolving non-interacting galaxies, and we further suggest that the BH growth rate may be closely tied to the dynamical time of the merger system.

Growth Factor Inhibiting PKC Sensor in E-coli Environment Using Classification Technique and ANN Method

Directory of Open Access Journals (Sweden)

T. K. BASAK

2011-03-01

Full Text Available Protein kinease C plays an important role in angiogenesis and apoptosis in cancer. During the phase of angiogenesis the growth factor is up regulated where as during apoptosis the growth factor is down regulated. For down regulation of growth factor the pH environment of intra-cellular fluid has a specific range in the alkaline medium. Protein kinease C along with E-coli through interaction of Selenometabolite is able to maintain that alkaline environment for the apoptosis of the cancer cell with inhibition of the growth factor related to antioxidant/oxidant ratio. The present paper through implementation of Artificial Neural Network and Decision Tree has focused on metastasis linked with Capacitance Relaxation phenomena and down regulation of growth factor (VGEF. In this paper a distributed neural network has been applied to a data mining problem for classification of cancer stages inorder to have proper diagnosis of patient with PKC sensor. The Network was trained off line using 270 patterns each of 6 inputs. Using the weight obtained during training, fresh patterns were tested for accuracy in diagnosis linked with the stages of cancer.

Growing adaptive machines combining development and learning in artificial neural networks

CERN Document Server

Bredeche, Nicolas; Doursat, René

2014-01-01

The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

Science.gov (United States)

Rubaai, Ahmed

1996-01-01

A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

Intrinsic gain modulation and adaptive neural coding.

Directory of Open Access Journals (Sweden)

Sungho Hong

2008-07-01

Full Text Available In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate versus current (f-I curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.

Flower Power: Sunflowers as a Model for Logistic Growth

Science.gov (United States)

Fernandez, Eileen; Geist, Kristi A.

2011-01-01

Logistic growth displays an interesting pattern: It starts fast, exhibiting the rapid growth characteristic of exponential models. As time passes, it slows in response to constraints such as limited resources or reallocation of energy. The growth continues to slow until it reaches a limit, called capacity. When the growth describes a population,…

Efecto del retardo prenatal de crecimiento y la subnutrición postnatal en el crecimiento craneofacial / Craneofacial effect of prenatal growth retardation and postnatal undernutrition in craniofacial growth

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María Eugenia Luna

2016-03-01

Full Text Available El objetivo fue analizar en animales con retardo prenatal de crecimiento (RPC el efecto de la subnutrición proteico-calórica lactacional y postlactacional sobre la morfología craneofacial, particularizando en el crecimiento de los componentes funcionales neural y facial. Ratas Wistar fueron divididas en los grupos: Control, RPC (inducido por ligamiento parcial de ambas arterias uterinas el día 15 de gestación y Sham-operado (con igual técnica quirúrgica que RPC aunque sin ligamiento de las arterias. A su vez, el grupo RPC se dividió en: (a crías lactantes de madres con nutrición normal y a partir del destete alimentadas ad-libitum y (b crías lactantes de madres con restricción alimentaria del 25% y a partir del destete alimentadas con el 50% de lo consumido por un animal control. Se tomaron radiografías a las edades 1, 21, 42, 63 y 84 y se midieron longitud, ancho y altura de los componentes neural y facial. Se calcularon los índices volumétricos neural y facial y morfométrico neurofacial. Se aplicaron ANOVA y pruebas post-hoc y se calcularon diferencias porcentuales entre medias. Los resultados permitieron concluir que el estrés primario ocurrido durante la vida intrauterina resulta crítico en lo inmediato y en la vida postnatal, ya que aun mediando normonutrición postnatal el retardo de crecimiento perdura. Además, cuando al estrés prenatal le continúa restricción nutricional postnatal los efectos adversos son aditivos provocando retardo del crecimiento aún mayor. Finalmente, mientras que el componente neural es más resistente a las deficiencias nutricionales, el facial presenta mayor plasticidad, hecho que se evidencia en cambios de forma. Palabras clave: crecimiento craneofacial; desnutrición pre y postnatal; craneometría funcional    The aim of the study was to analyze the effect of protein-calorie malnutrition during lactation and post-lactation on craniofacial morphology in intrauterine growth-retarded (IUGR

Quantum Entanglement in Neural Network States

Directory of Open Access Journals (Sweden)

Dong-Ling Deng

2017-05-01

Full Text Available Machine learning, one of today’s most rapidly growing interdisciplinary fields, promises an unprecedented perspective for solving intricate quantum many-body problems. Understanding the physical aspects of the representative artificial neural-network states has recently become highly desirable in the applications of machine-learning techniques to quantum many-body physics. In this paper, we explore the data structures that encode the physical features in the network states by studying the quantum entanglement properties, with a focus on the restricted-Boltzmann-machine (RBM architecture. We prove that the entanglement entropy of all short-range RBM states satisfies an area law for arbitrary dimensions and bipartition geometry. For long-range RBM states, we show by using an exact construction that such states could exhibit volume-law entanglement, implying a notable capability of RBM in representing quantum states with massive entanglement. Strikingly, the neural-network representation for these states is remarkably efficient, in the sense that the number of nonzero parameters scales only linearly with the system size. We further examine the entanglement properties of generic RBM states by randomly sampling the weight parameters of the RBM. We find that their averaged entanglement entropy obeys volume-law scaling, and the meantime strongly deviates from the Page entropy of the completely random pure states. We show that their entanglement spectrum has no universal part associated with random matrix theory and bears a Poisson-type level statistics. Using reinforcement learning, we demonstrate that RBM is capable of finding the ground state (with power-law entanglement of a model Hamiltonian with a long-range interaction. In addition, we show, through a concrete example of the one-dimensional symmetry-protected topological cluster states, that the RBM representation may also be used as a tool to analytically compute the entanglement spectrum. Our

Parallel consensual neural networks.

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Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

1997-01-01

A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

SOCIAL INEQUALITY IN CHINA AS A RESULT OF THE RAPID ECONOMIC GROWTH

Directory of Open Access Journals (Sweden)

Вероника Игоревна Шехурдина

2013-12-01

Full Text Available Since the period of openness in China, laid the foundation for more than 30 years ago, he has made remarkable progress in increasing incomes and reducing absolute poverty. However, they are caused by rising inequality. It should be noted that the rise in inequality was seen almost everywhere in the world over the past two decades. Growing dissatisfaction with the quality of economic growth is often seen in favor of certain groups more than the general population. This is clearly reflected in the growth of inequality between different groups - the rich are getting richer faster than the poor. The economic literature attributes this mainly to globalization, technological change, skills-based, and reduce the "power" of the workers. Growth model, which accompanies the last three decades to China, included a trade-off between high growth (and subsequent reduction of absolute poverty and worsening inequality. The government of China has recognized this problem and taken active steps to reduce the gap incomes and standards of living in the city and rural areas, which have already brought the first results.DOI: http://dx.doi.org/10.12731/2218-7405-2013-10-16

Creative-Dynamics Approach To Neural Intelligence

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Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

VEGF-mediated angiogenesis stimulates neural stem cell proliferation and differentiation in the premature brain

International Nuclear Information System (INIS)

Sun, Jinqiao; Sha, Bin; Zhou, Wenhao; Yang, Yi

2010-01-01

This study investigated the effects of angiogenesis on the proliferation and differentiation of neural stem cells in the premature brain. We observed the changes in neurogenesis that followed the stimulation and inhibition of angiogenesis by altering vascular endothelial growth factor (VEGF) expression in a 3-day-old rat model. VEGF expression was overexpressed by adenovirus transfection and down-regulated by siRNA interference. Using immunofluorescence assays, Western blot analysis, and real-time PCR methods, we observed angiogenesis and the proliferation and differentiation of neural stem cells. Immunofluorescence assays showed that the number of vWF-positive areas peaked at day 7, and they were highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at every time point. The number of neural stem cells, neurons, astrocytes, and oligodendrocytes in the subventricular zone gradually increased over time in the VEGF up-regulation group. Among the three groups, the number of these cells was highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at the same time point. Western blot analysis and real-time PCR confirmed these results. These data suggest that angiogenesis may stimulate the proliferation of neural stem cells and differentiation into neurons, astrocytes, and oligodendrocytes in the premature brain.

NADPH promotes the rapid growth of the tumor

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Hao Sheng

2018-04-01

Full Text Available NADPH oxidase is the main source of intracellular reactive oxygen species (ROS. ROS plays an important role in a variety of tumor types. The ROS mediated by NADPH oxidase increases the expression of hypoxia-inducible factor alpha (HIF-α through multiple signaling pathways in tumor, and HIF-α could be regulated and controlled by downstream multiple targeted genes such as vascular endothelial growth factor, glucose transporter to promote tumor angiogenesis, cell energy metabolism reprogram and tumor metastasis. Meanwhile, HIF-α can also regulate the expression of NADPH oxidase by ROS, thus further promoting development of tumor. In this review, we summarized the functions of NADPH in tumorigenesis and discussed their potential implications in cancer therapy.

Footprint analysis during the growth period.

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Volpon, J B

1994-01-01

Static footprints were obtained from 672 healthy white subjects ranging in age from newborn to 15 years. The length of the footprint was measured and the medial longitudinal arch was evaluated. The findings showed that the feet grew most rapidly up to 3 years of age. From age 3 onward, the feet maintained an almost constant growth rate, which was the same for both sexes until age 12 years, when girls' feet stopped growing, but boys' feet exhibited further growth. From birth up to 2 years of age, there was a higher incidence of flat feet. Rapid progression of plantar arch development was observed between 2 and 6 years of age.

Ultra-nanocrystalline diamond electrodes: optimization towards neural stimulation applications.

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Garrett, David J; Ganesan, Kumaravelu; Stacey, Alastair; Fox, Kate; Meffin, Hamish; Prawer, Steven

2012-02-01

Diamond is well known to possess many favourable qualities for implantation into living tissue including biocompatibility, biostability, and for some applications hardness. However, conducting diamond has not, to date, been exploited in neural stimulation electrodes due to very low electrochemical double layer capacitance values that have been previously reported. Here we present electrochemical characterization of ultra-nanocrystalline diamond electrodes grown in the presence of nitrogen (N-UNCD) that exhibit charge injection capacity values as high as 163 µC cm(-2) indicating that N-UNCD is a viable material for microelectrode fabrication. Furthermore, we show that the maximum charge injection of N-UNCD can be increased by tailoring growth conditions and by subsequent electrochemical activation. For applications requiring yet higher charge injection, we show that N-UNCD electrodes can be readily metalized with platinum or iridium, further increasing charge injection capacity. Using such materials an implantable neural stimulation device fabricated from a single piece of bio-permanent material becomes feasible. This has significant advantages in terms of the physical stability and hermeticity of a long-term bionic implant.

Orthopedic treatment of Class III malocclusion with rapid maxillary expansion combined with a face mask: a cephalometric assessment of craniofacial growth patterns

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Daniella Torres Tagawa

2012-06-01

Full Text Available OBJECTIVE: The aim of this prospective study was to assess potential changes in the cephalometric craniofacial growth pattern of 17 children presenting Angle Class III malocclusion treated with a Haas-type expander combined with a face mask. METHODS: Lateral cephalometric radiographs were taken at beginning (T1 and immediately after removal of the appliances (T2, average of 11 months of treatment. Linear and angular measurements were used to evaluate the cranial base, dentoskeletal changes and facial growth pattern. RESULTS: The length of the anterior cranial base experienced a reduction while the posterior cranial base assumed a more vertical position at T1. Some maxillary movement occurred, there was no rotation of the palatal plane, there was a slight clockwise rotation of the mandible, although not significant. The ANB angle increased, thereby improving the relationship between the jaws; dentoalveolar compensation was more evident in the lower incisors. Five out of 12 cases (29.41% showed the following changes: In one case the pattern became more horizontal and in four cases more vertical. CONCLUSIONS: It was concluded after a short-term assessment that treatment with rapid maxillary expansion (RME associated with a face mask was effective in the correction of Class III malocclusion despite the changes in facial growth pattern observed in a few cases.

World pipeline work set for rapid growth

International Nuclear Information System (INIS)

Anon.

1992-01-01

This paper reports on international pipeline construction which has entered a fast-growth period, accelerated by the new political and economic realities around the world and increasing demand for natural gas, crude oil and refined petroleum products. Many projects are under way or in planning for completion in the mid- to late 1990s in Europe, South America, Asia and the Middle East. Pipeline And Gas Journal's projection calls for construction or other work on 30,700 miles of new natural gas, crude oil and refined products pipelines in the 1992-93 period outside Canada and the U.S. These projects will cost an estimated $30 billion-plus. Natural gas pipelines will comprise most of the mileage, accounting for almost 23,000 miles at an estimated cost of $26.3 billion. Products pipelines, planned or under construction, will add another 5,800 miles at a cost of $2.8 billion. Crude oil pipelines, at a minimum, will total 1,900 new miles at a cost of slightly under $1 billion

The Biology and Economics of Coral Growth

NARCIS (Netherlands)

Osinga, R.; Schutter, M.; Griffioen, B.; Wijffels, R.H.; Verreth, J.A.J.; Shafit, S.; Henard, S.; Taruffi, M.; Gili, C.; Lavorano, S.

2011-01-01

To protect natural coral reefs, it is of utmost importance to understand how the growth of the main reef-building organisms-the zooxanthellate scleractinian corals-is controlled. Understanding coral growth is also relevant for coral aquaculture, which is a rapidly developing business. This review

EDITORIAL: Why we need a new journal in neural engineering

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Durand, Dominique M.

2004-03-01

The field of neural engineering crystallizes for many engineers and scientists an area of research at the interface between neuroscience and engineering. For the last 15 years or so, the discipline of neural engineering (neuroengineering) has slowly appeared at conferences as a theme or track. The first conference devoted entirely to this area was the 1st International IEEE EMBS Conference on Neural Engineering which took place in Capri, Italy in 2003. Understanding how the brain works is considered the ultimate frontier and challenge in science. The complexity of the brain is so great that understanding even the most basic functions will require that we fully exploit all the tools currently at our disposal in science and engineering and simultaneously develop new methods of analysis. While neuroscientists and engineers from varied fields such as brain anatomy, neural development and electrophysiology have made great strides in the analysis of this complex organ, there remains a great deal yet to be uncovered. The potential for applications and remedies deriving from scientific discoveries and breakthroughs is extremely high. As a result of the growing availability of micromachining technology, research into neurotechnology has grown relatively rapidly in recent years and appears to be approaching a critical mass. For example, by understanding how neuronal circuits process and store information, we could design computers with capabilities beyond current limits. By understanding how neurons develop and grow, we could develop new technologies for spinal cord repair or central nervous system repair following neurological disorders. Moreover, discoveries related to higher-level cognitive function and consciousness could have a profound influence on how humans make sense of their surroundings and interact with each other. The ability to successfully interface the brain with external electronics would have enormous implications for our society and facilitate a

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

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Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more

Application of back-propagation artificial neural network (ANN) to predict crystallite size and band gap energy of ZnO quantum dots

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Pelicano, Christian Mark; Rapadas, Nick; Cagatan, Gerard; Magdaluyo, Eduardo

2017-12-01

Herein, the crystallite size and band gap energy of zinc oxide (ZnO) quantum dots were predicted using artificial neural network (ANN). Three input factors including reagent ratio, growth time, and growth temperature were examined with respect to crystallite size and band gap energy as response factors. The generated results from neural network model were then compared with the experimental results. Experimental crystallite size and band gap energy of ZnO quantum dots were measured from TEM images and absorbance spectra, respectively. The Levenberg-Marquardt (LM) algorithm was used as the learning algorithm for the ANN model. The performance of the ANN model was then assessed through mean square error (MSE) and regression values. Based on the results, the ANN modelling results are in good agreement with the experimental data.

Rapid antibiotic susceptibility testing in a microfluidic pH sensor.

Science.gov (United States)

Tang, Yanyan; Zhen, Li; Liu, Jingqing; Wu, Jianmin