WorldWideScience

Sample records for neural system defects

  1. 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 ...

  2. Surface Casting Defects Inspection Using Vision System and Neural Network Techniques

    Directory of Open Access Journals (Sweden)

    Świłło S.J.

    2013-12-01

    Full Text Available The paper presents a vision based approach and neural network techniques in surface defects inspection and categorization. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks and pores that greatly influence the material’s properties Since the human visual inspection for the surface is slow and expensive, a computer vision system is an alternative solution for the online inspection. The authors present the developed vision system uses an advanced image processing algorithm based on modified Laplacian of Gaussian edge detection method and advanced lighting system. The defect inspection algorithm consists of several parameters that allow the user to specify the sensitivity level at which he can accept the defects in the casting. In addition to the developed image processing algorithm and vision system apparatus, an advanced learning process has been developed, based on neural network techniques. Finally, as an example three groups of defects were investigated demonstrates automatic selection and categorization of the measured defects, such as blowholes, shrinkage porosity and shrinkage cavity.

  3. A comparison of neural tube defects identified by two independent routine recording systems for congenital malformations in Northern Ireland.

    Science.gov (United States)

    Nevin, N C; McDonald, J R; Walby, A L

    1978-12-01

    The efficiency of two systems for recording congenital malformations has been compared; one system, the Registrar General's Congenital Malformation Notification, is based on registering all malformed infants, and the other, the Child Health System, records all births. In Northern Ireland for three years [1974--1976], using multiple sources of ascertainment, a total of 686 infants with neural tube defects was identified among 79 783 live and stillbirths. The incidence for all neural tube defects in 8 60 per 1 000 births. The Registrar General's Congenital Malformation Notification System identified 83.6% whereas the Child Health System identified only 63.3% of all neural tube defects. Both systems together identified 86.2% of all neural tube defects. The two systems are suitable for monitoring of malformations and the addition of information from the Genetic Counselling Clinics would enhance the data for epidemiological studies.

  4. Development of automated system based on neural network algorithm for detecting defects on molds installed on casting machines

    Science.gov (United States)

    Bazhin, V. Yu; Danilov, I. V.; Petrov, P. A.

    2018-05-01

    During the casting of light alloys and ligatures based on aluminum and magnesium, problems of the qualitative distribution of the metal and its crystallization in the mold arise. To monitor the defects of molds on the casting conveyor, a camera with a resolution of 780 x 580 pixels and a shooting rate of 75 frames per second was selected. Images of molds from casting machines were used as input data for neural network algorithm. On the preparation of a digital database and its analytical evaluation stage, the architecture of the convolutional neural network was chosen for the algorithm. The information flow from the local controller is transferred to the OPC server and then to the SCADA system of foundry. After the training, accuracy of neural network defect recognition was about 95.1% on a validation split. After the training, weight coefficients of the neural network were used on testing split and algorithm had identical accuracy with validation images. The proposed technical solutions make it possible to increase the efficiency of the automated process control system in the foundry by expanding the digital database.

  5. Neural Tube Defects and Pregnancy

    Directory of Open Access Journals (Sweden)

    Emine Çoşar

    2009-09-01

    Full Text Available OBJECTIVE: Neural tube defects are congenital malformations those mostly causing life-long morbidities. They are prevented by the periconseptional folic acid usage and prenatal diagnostic methods. MATERIALS-METHODS: Pregnants from Afyonkarahisar and neighbourhood cities applied to our hospital and determined NTD, were investigated. RESULTS: In our obstetrics clinic 1403 delivery were made and 43 of them had fetus with NTD. Among these fetuses 41.3% had meningomyelocel, 17.4% had meningocel, 21.7% had encephalocel, 8.7% had unencephali and 4.3% had iniencephali. CONCLUSION: Incidence of NTD is high in our region and geographic region, nutrition and other socioeconomic factors may be related to the high incidence. Education of the mother and periconceptional folic acid usage may reduce teh incidence of NTD.

  6. Radioactive fallout and neural tube defects

    Directory of Open Access Journals (Sweden)

    Nejat Akar

    2015-10-01

    Full Text Available Possible link between radioactivity and the occurrence of neural tube defects is a long lasting debate since the Chernobyl nuclear fallout in 1986. A recent report on the incidence of neural defects in the west coast of USA, following Fukushima disaster, brought another evidence for effect of radioactive fallout on the occurrence of NTD’s. Here a literature review was performed focusing on this special subject.

  7. [Folic acid: Primary prevention of neural tube defects. Literature Review].

    Science.gov (United States)

    Llamas Centeno, M J; Miguélez Lago, C

    2016-03-01

    Neural tube defects (NTD) are the most common congenital malformations of the nervous system, they have a multifactorial etiology, are caused by exposure to chemical, physical or biological toxic agents, factors deficiency, diabetes, obesity, hyperthermia, genetic alterations and unknown causes. Some of these factors are associated with malnutrition by interfering with the folic acid metabolic pathway, the vitamin responsible for neural tube closure. Its deficit produce anomalies that can cause abortions, stillbirths or newborn serious injuries that cause disability, impaired quality of life and require expensive treatments to try to alleviate in some way the alterations produced in the embryo. Folic acid deficiency is considered the ultimate cause of the production of neural tube defects, it is clear the reduction in the incidence of Espina Bifida after administration of folic acid before conception, this leads us to want to further study the action of folic acid and its application in the primary prevention of neural tube defects. More than 40 countries have made the fortification of flour with folate, achieving encouraging data of decrease in the prevalence of neural tube defects. This paper attempts to make a literature review, which clarify the current situation and future of the prevention of neural tube defects.

  8. 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.

  9. Assessing the prevalence of spina bifida and encephalocele in a Kenyan hospital from 2005–2010: implications for a neural tube defects surveillance system

    Science.gov (United States)

    Githuku, Jane N; Azofeifa, Alejandro; Valencia, Diana; Ao, Trong; Hamner, Heather; Amwayi, Samuel; Gura, Zeinab; Omolo, Jared; Albright, Leland; Guo, Jing; Arvelo, Wences

    2014-01-01

    Introduction Neural tube defects such as anencephaly, spina bifida, and encephalocele are congenital anomalies of the central nervous system. Data on the prevalence of neural tube defects in Kenya are limited. This study characterizes and estimates the prevalence of spina bifida and encephalocele reported in a referral hospital in Kenya from 2005-2010. Methods Cases were defined as a diagnosis of spina bifida or encephalocele. Prevalence was calculated as the number of cases by year and province of residence divided by the total number of live-births per province. Results From a total of 6,041 surgical records; 1,184 (93%) had reported diagnosis of spina bifida and 88 (7%) of encephalocele. Estimated prevalence of spina bifida and encephalocele from 2005-2010 was 3.3 [95% Confidence Interval (CI): 3.1-3.5] cases per 10,000 live-births. The highest prevalence of cases were reported in 2007 with 4.4 (95% CI: 3.9-5.0) cases per 10,000 live-births. Rift Valley province had the highest prevalence of spina bifida and encephalocele at 6.9 (95% CI: 6.3-7.5) cases per 10,000 live-births from 2005-2010. Conclusion Prevalence of spina bifida and encephalocele is likely underestimated, as only patients seeking care at the hospital were included. Variations in regional prevalence could be due to referral patterns and healthcare access. Implementation of a neural tube defects surveillance system would provide a more thorough assessment of the burden of neural tube defects in Kenya. PMID:26113894

  10. Assessing the prevalence of spina bifida and encephalocele in a Kenyan hospital from 2005-2010: implications for a neural tube defects surveillance system.

    Science.gov (United States)

    Githuku, Jane N; Azofeifa, Alejandro; Valencia, Diana; Ao, Trong; Hamner, Heather; Amwayi, Samuel; Gura, Zeinab; Omolo, Jared; Albright, Leland; Guo, Jing; Arvelo, Wences

    2014-01-01

    Neural tube defects such as anencephaly, spina bifida, and encephalocele are congenital anomalies of the central nervous system. Data on the prevalence of neural tube defects in Kenya are limited. This study characterizes and estimates the prevalence of spina bifida and encephalocele reported in a referral hospital in Kenya from 2005-2010. Cases were defined as a diagnosis of spina bifida or encephalocele. Prevalence was calculated as the number of cases by year and province of residence divided by the total number of live-births per province. From a total of 6,041 surgical records; 1,184 (93%) had reported diagnosis of spina bifida and 88 (7%) of encephalocele. Estimated prevalence of spina bifida and encephalocele from 2005-2010 was 3.3 [95% Confidence Interval (CI): 3.1-3.5] cases per 10,000 live-births. The highest prevalence of cases were reported in 2007 with 4.4 (95% CI: 3.9-5.0) cases per 10,000 live-births. Rift Valley province had the highest prevalence of spina bifida and encephalocele at 6.9 (95% CI: 6.3-7.5) cases per 10,000 live-births from 2005-2010. Prevalence of spina bifida and encephalocele is likely underestimated, as only patients seeking care at the hospital were included. Variations in regional prevalence could be due to referral patterns and healthcare access. Implementation of a neural tube defects surveillance system would provide a more thorough assessment of the burden of neural tube defects in Kenya.

  11. Neural Tube Defects, Folic Acid and Methylation

    Science.gov (United States)

    Imbard, Apolline; Benoist, Jean-François; Blom, Henk J.

    2013-01-01

    Neural tube defects (NTDs) are common complex congenital malformations resulting from failure of the neural tube closure during embryogenesis. It is established that folic acid supplementation decreases the prevalence of NTDs, which has led to national public health policies regarding folic acid. To date, animal studies have not provided sufficient information to establish the metabolic and/or genomic mechanism(s) underlying human folic acid responsiveness in NTDs. However, several lines of evidence suggest that not only folates but also choline, B12 and methylation metabolisms are involved in NTDs. Decreased B12 vitamin and increased total choline or homocysteine in maternal blood have been shown to be associated with increased NTDs risk. Several polymorphisms of genes involved in these pathways have also been implicated in risk of development of NTDs. This raises the question whether supplementation with B12 vitamin, betaine or other methylation donors in addition to folic acid periconceptional supplementation will further reduce NTD risk. The objective of this article is to review the role of methylation metabolism in the onset of neural tube defects. PMID:24048206

  12. Defect detection on videos using neural network

    Directory of Open Access Journals (Sweden)

    Sizyakin Roman

    2017-01-01

    Full Text Available In this paper, we consider a method for defects detection in a video sequence, which consists of three main steps; frame compensation, preprocessing by a detector, which is base on the ranking of pixel values, and the classification of all pixels having anomalous values using convolutional neural networks. The effectiveness of the proposed method shown in comparison with the known techniques on several frames of the video sequence with damaged in natural conditions. The analysis of the obtained results indicates the high efficiency of the proposed method. The additional use of machine learning as postprocessing significantly reduce the likelihood of false alarm.

  13. Radioactive fallout and neural tube defects | Akar | Egyptian Journal ...

    African Journals Online (AJOL)

    Possible link between radioactivity and the occurrence of neural tube defects is a long lasting debate since the Chernobyl nuclear fallout in 1986. A recent report on the incidence of neural defects in the west coast of USA, following Fukushima disaster, brought another evidence for effect of radioactive fallout on the ...

  14. Preventing neural tube defects in Europe : A missed opportunity

    NARCIS (Netherlands)

    Busby, A; Armstrong, B; Dolk, H; Armstrong, N; Haeusler, M; Berghold, A; Gillerot, Y; Baguette, A; Gjerga, R; Barisic, [No Value; Christiansen, M; Goujard, J; Steinbicker, [No Value; Rosch, C; McDonnell, R; Scarano, G; Calzolari, E; Neville, A; Cocchi, G; Bianca, S; Gatt, M; De Walle, H; Braz, P; Latos-Bielenska, A; Gener, B; Portillor, [No Value; Addor, MC; Abramsky, L; Ritvanen, A; Robert-Gnansia, E; Daltveit, AK; Aneren, G; Olars, B; Edwards, G

    2005-01-01

    Each year, more than 4500 pregnancies in the European Union are affected by neural tube defects (NTD). Unambiguous evidence of the effectiveness of peri conceptional folic acid in preventing the majority of neural tube defects has been available since 1991. We report on trends in the total

  15. Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects.

    Science.gov (United States)

    Tan, Shing Chiang; Watada, Junzo; Ibrahim, Zuwairie; Khalid, Marzuki

    2015-05-01

    Wafer defect detection using an intelligent system is an approach of quality improvement in semiconductor manufacturing that aims to enhance its process stability, increase production capacity, and improve yields. Occasionally, only few records that indicate defective units are available and they are classified as a minority group in a large database. Such a situation leads to an imbalanced data set problem, wherein it engenders a great challenge to deal with by applying machine-learning techniques for obtaining effective solution. In addition, the database may comprise overlapping samples of different classes. This paper introduces two models of evolutionary fuzzy ARTMAP (FAM) neural networks to deal with the imbalanced data set problems in a semiconductor manufacturing operations. In particular, both the FAM models and hybrid genetic algorithms are integrated in the proposed evolutionary artificial neural networks (EANNs) to classify an imbalanced data set. In addition, one of the proposed EANNs incorporates a facility to learn overlapping samples of different classes from the imbalanced data environment. The classification results of the proposed evolutionary FAM neural networks are presented, compared, and analyzed using several classification metrics. The outcomes positively indicate the effectiveness of the proposed networks in handling classification problems with imbalanced data sets.

  16. Prevalence of neural tube defect and hydrocephalus in Northern ...

    African Journals Online (AJOL)

    All the cases reported in this study were open neural tube defect (NTD). The most common defect was hydrocephalus occurring in 33 patients representing 57.9%, with spinal bifida occurring in 21 patients representing 38.6%. Encephalocele or cranium bifida occurred in only 5.3% (3 patients). Among the spinal bifida cases ...

  17. Topological defects control collective dynamics in neural progenitor cell cultures

    Science.gov (United States)

    Kawaguchi, Kyogo; Kageyama, Ryoichiro; Sano, Masaki

    2017-04-01

    Cultured stem cells have become a standard platform not only for regenerative medicine and developmental biology but also for biophysical studies. Yet, the characterization of cultured stem cells at the level of morphology and of the macroscopic patterns resulting from cell-to-cell interactions remains largely qualitative. Here we report on the collective dynamics of cultured murine neural progenitor cells (NPCs), which are multipotent stem cells that give rise to cells in the central nervous system. At low densities, NPCs moved randomly in an amoeba-like fashion. However, NPCs at high density elongated and aligned their shapes with one another, gliding at relatively high velocities. Although the direction of motion of individual cells reversed stochastically along the axes of alignment, the cells were capable of forming an aligned pattern up to length scales similar to that of the migratory stream observed in the adult brain. The two-dimensional order of alignment within the culture showed a liquid-crystalline pattern containing interspersed topological defects with winding numbers of +1/2 and -1/2 (half-integer due to the nematic feature that arises from the head-tail symmetry of cell-to-cell interaction). We identified rapid cell accumulation at +1/2 defects and the formation of three-dimensional mounds. Imaging at the single-cell level around the defects allowed us to quantify the velocity field and the evolving cell density; cells not only concentrate at +1/2 defects, but also escape from -1/2 defects. We propose a generic mechanism for the instability in cell density around the defects that arises from the interplay between the anisotropic friction and the active force field.

  18. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  19. 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.

  20. Radioactive fallout and neural tube defects

    African Journals Online (AJOL)

    Nejat Akar

    2015-07-10

    Jul 10, 2015 ... It is a prenatal failure of the embryonic neural tube to close over the ... and the ability of radioisotopes to attach to cells, tissues, and ... The Egyptian Journal of Medical Human Genetics .... Stem Cells 1997;15(Suppl 2):255–60.

  1. Deep convolutional neural networks for detection of rail surface defects

    NARCIS (Netherlands)

    Faghih Roohi, S.; Hajizadeh, S.; Nunez Vicencio, Alfredo; Babuska, R.; De Schutter, B.H.K.; Estevez, Pablo A.; Angelov, Plamen P.; Del Moral Hernandez, Emilio

    2016-01-01

    In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings. This huge amount of data makes it impossible to manually inspect the images and

  2. Cutaneous vascular anomalies associated with neural tube defects: nomenclature and pathology revisited.

    Science.gov (United States)

    Maugans, Todd; Sheridan, Rachel M; Adams, Denise; Gupta, Anita

    2011-07-01

    Lumbosacral cutaneous vascular anomalies associated with neural tube defects are frequently described in the literature as "hemangiomas." The classification system for pediatric vascular anomalies developed by the International Society for the Study of Vascular Anomalies provides a framework to accurately diagnose these lesions. To apply this classification to vascular cutaneous anomalies overlying myelodysplasias. A retrospective analysis of patients with neural tube defects and lumbosacral cutaneous vascular lesions was performed. All eligible patients had detailed histopathologic analysis of skin and spinal cord/placode lesions. Clinical and radiologic features were analyzed. Conventional histology and GLUT-1 immunostaining were performed to differentiate infantile capillary hemangiomas from capillary vascular malformations. Ten cases with cutaneous lesions associated with neural tube defects were reviewed. Five lesions were diagnosed as infantile capillary hemangiomas based upon histology and positive GLUT-1 endothelial reactivity. These lesions had a strong association with dermal sinus tracts. No reoperations were required for residual intraspinal vascular lesions, and overlying cutaneous vascular anomalies involuted with time. The remaining 5 lesions were diagnosed as capillary malformations. These occurred with both open and closed neural tube defects, did not involute, and demonstrated enlargement and darkening due to vascular congestion. The International Society for the Study of Vascular Anomalies scheme should be used to describe the cutaneous vascular lesions associated with neural tube defects: infantile capillary hemangiomas and capillary malformations. We advocate that these lesions be described as "vascular anomalies" or "stains" pending accurate diagnosis by clinical, histological, and immunohistochemical evaluations.

  3. Global Burden of Neural Tube Defects, Risk Factors, and Prevention

    Directory of Open Access Journals (Sweden)

    Joseph E

    2014-11-01

    Full Text Available Neural tube defects (NTDs, serious birth defects of the brain and spine usually resulting in death or paralysis, affect an estimated 300,000 births each year worldwide. Although the majority of NTDs are preventable with adequate folic acid consumption during the preconception period and throughout the first few weeks of gestation, many populations, in particular those in low and middle resource settings, do not have access to fortified foods or vitamin supplements containing folic acid. Further, accurate birth defects surveillance data, which could help inform mandatory fortification and other NTD prevention initiatives, are lacking in many of these settings. The burden of birth defects in South East Asia is among the highest in the world. Expanding global neural tube defects prevention initiatives can support the achievement of the United Nations Millennium Development Goal 4 to reduce child mortality, a goal which many countries in South East Asia are currently not poised to reach, and the 63rd World Health Assembly Resolution on birth defects. More work is needed to develop and implement mandatory folic acid fortification policies, as well as supplementation programs in countries where the reach of fortification is limited.

  4. Antenatal Diagnosis of a Rare Neural Tube Defect: Sincipital Encephalocele

    Directory of Open Access Journals (Sweden)

    Mehdi Kehila

    2015-01-01

    Full Text Available Context. Fetal sincipital encephalocele is one of the most serious congenital neural tube defects with a high risk of mortality and neonatal morbidity. Prenatal diagnosis of this malformation is important in fetal medicine. Case Report. We report a case of prenatal diagnosis of sincipital encephalocele using ultrasound and MRI imaging. The diagnosis was done at 25 weeks of gestation by identifying an anterior cephalic protrusion through a defect in the skull. Conclusion. Through this case, we discuss the differential diagnosis, management, and prognosis of such lesions.

  5. Neural tube defects – recent advances, unsolved questions and controversies

    Science.gov (United States)

    Copp, Andrew J.; Stanier, Philip; Greene, Nicholas D. E.

    2014-01-01

    Neural tube defects (NTDs) are severe congenital malformations affecting around 1 in every 1000 pregnancies. Here we review recent advances and currently unsolved issues in the NTD field. An innovation in clinical management has come from the demonstration that closure of open spina bifida lesions in utero can diminish neurological dysfunction in children. Primary prevention by folic acid has been enhanced through introduction of mandatory food fortification in some countries, although not yet in UK. Genetic predisposition comprises the majority of NTD risk, and genes that regulate folate one-carbon metabolism and planar cell polarity have been strongly implicated. The sequence of human neural tube closure events remains controversial, but study of mouse NTD models shows that anencephaly, open spina bifida and craniorachischisis result from failure of primary neurulation, while skin-covered spinal dysraphism results from defective secondary neurulation. Other ‘NTD’ malformations, such as encephalocele, are likely to be post-neurulation disorders. PMID:23790957

  6. Preventing neural tube defects in Europe: a missed opportunity.

    Science.gov (United States)

    Busby, Araceli; Abramsky, Lenore; Dolk, Helen; Armstrong, Ben; Addor, Marie-Claude; Anneren, Goran; Armstrong, Nicola; Baguette, Andre; Barisic, Ingeborg; Berghold, Andrea; Bianca, Sebastiano; Braz, Paula; Calzolari, Elisa; Christiansen, Marianne; Cocchi, Guido; Daltveit, Anne Kjersti; De Walle, Hermien; Edwards, Grace; Gatt, Miriam; Gener, Blanca; Gillerot, Yves; Gjergja, Romana; Goujard, Janine; Haeusler, Martin; Latos-Bielenska, Anna; McDonnell, Robert; Neville, Amanda; Olars, Birgitta; Portillo, Isabel; Ritvanen, Annukka; Robert-Gnansia, Elizabeth; Rösch, Christine; Scarano, Gioacchino; Steinbicker, Volker

    2005-01-01

    Each year, more than 4500 pregnancies in the European Union are affected by neural tube defects (NTD). Unambiguous evidence of the effectiveness of periconceptional folic acid in preventing the majority of neural tube defects has been available since 1991. We report on trends in the total prevalence of neural tube defects up to 2002, in the context of a survey in 18 European countries of periconceptional folic acid supplementation (PFAS) policies and their implementation. EUROCAT is a network of population-based registries in Europe collaborating in the epidemiological surveillance of congenital anomalies. Representatives from 18 participating countries provided information about policy, health education campaigns and surveys of PFAS uptake. The yearly total prevalence of neural tube defects including livebirths, stillbirths and terminations of pregnancy was calculated from 1980 to 2002 for 34 registries, with UK and Ireland estimated separately from the rest of Europe. A meta-analysis of changes in NTD total prevalence between 1989-1991 and 2000-2002 according to PFAS policy was undertaken for 24 registries. By 2005, 13 countries had a government recommendation that women planning a pregnancy should take 0.4mg folic acid supplement daily, accompanied in 7 countries by government-led health education initiatives. In the UK and Ireland, countries with PFAS policy, there was a 30% decline in NTD total prevalence (95% CI 16-42%) but it was difficult to distinguish this from the pre-existing strong decline. In other European countries with PFAS policy, there was virtually no decline in NTD total prevalence whether a policy was in place by 1999 (2%, 95% CI 28% reduction to 32% increase) or not (8%, 95% CI 26% reduction to 16% increase). The potential for preventing NTDs by periconceptional folic acid supplementation is still far from being fulfilled in Europe. Only a public health policy including folic acid fortification of staple foods is likely to result in large

  7. Diagnosis of fetal neural tube defects by MRI

    International Nuclear Information System (INIS)

    Dong Suzhen; Zhu Ming; Zhong Yumin; Zhang Hong; Pan Huihong

    2010-01-01

    Objective: To explore the diagnostic value of MRI on fetal neural tube defects. Methods: Ten pregnant women, aged from 25 to 35 years (average 28 years) and with gestation from 20-39 weeks (average 33 weeks) were studied with a 1.5 T superconductive MR unit within 24 to 48 hours after ultrasound (US) studies. The imaging protocol included fast-imaging employing steady-state acquisition, single-shot FSE and T 1 -weighted fast inversion recovery motion insensitive sequences in the axial, fromtal, and sagittal planes relative to the fetal brain, thorax, abdomen, and spines. Prenatal US and MRI findings were compared with postnatal MRI diagnoses (3 fetuses) or autopsy (7 fetuses). Results: Ten pregnant women (9 with a single fetus and 1 with twin fetuses) were examined. For all cases, the diagnoses established by MRI were correct when compared with postnatal diagnosis or autopsy. In 7 cases, US and MRI findings were in complete agreement with postnatal diagnoses. US missed the diagnosis in 1 cases and misdiagnosed in 2 cases. Ten neural tube defects in this study included anencephaly (1 case), exencephaly (1 case), meningoencephalocele associated with amniotic band sequence (1 case), meningocele (1 case), thoracic myelomeningocele (1 case), lumbar spinal bifida (1 case), sacroiliac myelomeningocele (2 cases), sacroiliac large cystic spinal meningocele (1 case), sacroiliac spinal bifida (1 case). Conclusions: Prenatal MRI is effective in the assessment of fetal neural tube defects. It can exactly discriminate herniated contents and locate the spinal lesion level. (authors)

  8. Periconceptional Folate Deficiency and Implications in Neural Tube Defects

    Directory of Open Access Journals (Sweden)

    J. Safi

    2012-01-01

    Full Text Available Nutritional deficiencies are preventable etiological and epigenetic factors causing congenital abnormalities, first cause of infant mortality. Folate deficiency has a well-established teratogenic effect, leading to an increasing risk of neural tube defects. This paper highlights the most recent medical literature about folate deficiency, be it maternal or paternal. It then focuses on associated deficiencies as nutritional deficiencies are multiple and interrelated. Observational and interventional studies have all been consistent with a 50–70% protective effect of adequate women consumption of folates on neural tube defects. Since strategies to modify women’s dietary habits and vitamin use have achieved little progress, scientific as well as political effort is mandatory in order to implement global preventive public health strategies aimed at improving the alimentation of women in reproductive age, especially folic acid supplementation. Even with the recent breakthrough of fetal surgery for myelomeningocele, the emphasis should still be on prevention as the best practice rather than treatment of neural tube defects.

  9. Professor John Scott, folate and neural tube defects.

    Science.gov (United States)

    Hoffbrand, A Victor

    2014-02-01

    John Scott (1940-2013) was born in Dublin where he was to spend the rest of his career, both as an undergraduate and subsequently Professor of Biochemistry and Nutrition at Trinity College. His research with the talented group of scientists and clinicians that he led has had a substantial impact on our understanding of folate metabolism, mechanisms of its catabolism and deficiency. His research established the leading theory of folate involvement with vitamin B12 in the pathogenesis of vitamin B12 neuropathy. He helped to establish the normal daily intake of folate and the increased requirements needed either in food or as a supplement before and during pregnancy to prevent neural tube defects. He also suggested a dietary supplement of vitamin B12 before and during pregnancy to reduce the risk of neural tube defects. It would be an appropriate epitaph if fortification of food with folic acid became mandatory in the UK and Ireland, as it is in over 70 other countries. © 2013 John Wiley & Sons Ltd.

  10. Epidemiology of neural tube defects in Saudi Arabia.

    Science.gov (United States)

    AlShail, Essam; De Vol, Edward; Yassen, Ahsan; Elgamal, Essam A

    2014-12-01

    To evaluate the distribution and pattern of neural tube defects in Saudi Arabia by creating a hospital based registry. All cases registered in the King Faisal Specialist Hospital and Research Center (KFSH&RC) neural tube defect (NTD) registry since it was established in October 2000 until December 2012 were studied through active surveillance comprising a registrar who collects NTD information by reviewing the patient's medical records, and interviewing patient's families. The total number of patients registered from October 2000 to December 2012 was 718 patients. There were more females (417, 58%) than males (301, 42%). Of 620 mothers who underwent antenatal ultrasonography; 392 (63%) were diagnosed at birth, and 204 (33%) were diagnosed with antenatal hydrocephalus. In our registry sample, most mothers (95%) did not take folic acid 3 months prior to pregnancy, and 76% did not take folic acid during the 3 months after conception with the affected child. Only 5% received folic acid prior to conception. The KFSH&RC-NTD registry has met its objectives as a source of data that may significantly contribute to the prevention of NTDs, and improving quality of care for NTD patients through active publication of registry findings and management approaches.

  11. NMDA Receptor Signaling Is Important for Neural Tube Formation and for Preventing Antiepileptic Drug-Induced Neural Tube Defects.

    Science.gov (United States)

    Sequerra, Eduardo B; Goyal, Raman; Castro, Patricio A; Levin, Jacqueline B; Borodinsky, Laura N

    2018-05-16

    Failure of neural tube closure leads to neural tube defects (NTDs), which can have serious neurological consequences or be lethal. Use of antiepileptic drugs (AEDs) during pregnancy increases the incidence of NTDs in offspring by unknown mechanisms. Here we show that during Xenopus laevis neural tube formation, neural plate cells exhibit spontaneous calcium dynamics that are partially mediated by glutamate signaling. We demonstrate that NMDA receptors are important for the formation of the neural tube and that the loss of their function induces an increase in neural plate cell proliferation and impairs neural cell migration, which result in NTDs. We present evidence that the AED valproic acid perturbs glutamate signaling, leading to NTDs that are rescued with varied efficacy by preventing DNA synthesis, activating NMDA receptors, or recruiting the NMDA receptor target ERK1/2. These findings may prompt mechanistic identification of AEDs that do not interfere with neural tube formation. SIGNIFICANCE STATEMENT Neural tube defects are one of the most common birth defects. Clinical investigations have determined that the use of antiepileptic drugs during pregnancy increases the incidence of these defects in the offspring by unknown mechanisms. This study discovers that glutamate signaling regulates neural plate cell proliferation and oriented migration and is necessary for neural tube formation. We demonstrate that the widely used antiepileptic drug valproic acid interferes with glutamate signaling and consequently induces neural tube defects, challenging the current hypotheses arguing that they are side effects of this antiepileptic drug that cause the increased incidence of these defects. Understanding the mechanisms of neurotransmitter signaling during neural tube formation may contribute to the identification and development of antiepileptic drugs that are safer during pregnancy. Copyright © 2018 the authors 0270-6474/18/384762-12$15.00/0.

  12. Methodology for automatic process of the fired ceramic tile's internal defect using IR images and artificial neural network

    OpenAIRE

    Andrade, Roberto Márcio de; Eduardo, Alexandre Carlos

    2011-01-01

    In the ceramic industry, rarely testing systems were employed to on-line detect the presence of defects in ceramic tiles. This paper is concerned with the problem of automatic inspection of ceramic tiles using Infrared Images and Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally from laboratory and on line tile samples. It has been performed system for IR image processing and, utilizing an Artificial Neural Network (ANN), det...

  13. Spinal neural tube defects on in utero MRI

    International Nuclear Information System (INIS)

    Williams, F.; Griffiths, P.D.

    2013-01-01

    Spinal neural tube defects are a heterogeneous group of disorders, which remain relatively common, with a prevalence of 1–2 per 1000 live births despite advances in maternal antenatal care. They range from mild disorders with limited neurodevelopmental sequelae to extensive abnormalities with significant morbidity and mortality. The advent of in utero magnetic resonance imaging has enabled accurate anatomical characterization of an increasing number of abnormalities with increasing confidence. Recognition of the salient radiological features of these disorders and their relationship to the embryogenesis of the spinal cord and its coverings is now possible. This review describes the radiological appearances of these disorders with examples from Fetal Imaging Unit, University of Sheffield to illustrate the key anatomical and radiological features to aid the radiologist in their recognition

  14. Chromosomal Abnormalities Associated with Neural Tube Defects (I: Full Aneuploidy

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2007-12-01

    Full Text Available Fetuses with neural tube defects (NTDs carry a risk of chromosomal abnormalities. The risk varies with maternal age, gestational age at diagnosis, association with other structural abnormalities, and family history of chromosome aberrations. This article provides an overview of chromosomal abnormalities associated with NTDs in embryos, fetuses, and newborn patients, and a comprehensive review of numerical chromosomal abnormalities associated with NTDs, such as trisomy 18, trisomy 13, triploidy, trisomy 9, trisomy 2, trisomy 21, trisomy 7, trisomy 8, trisomy 14, trisomy 15, trisomy 16, trisomy 5 mosaicism, trisomy 11 mosaicism, trisomy 20 mosaicism, monosomy X, and tetraploidy. NTDs may be associated with aneuploidy. Perinatal identification of NTDs should alert one to the possibility of chromosomal abnormalities and prompt a thorough cytogenetic investigation and genetic counseling.

  15. 21 CFR 101.79 - Health claims: Folate and neural tube defects.

    Science.gov (United States)

    2010-04-01

    ... pregnancy had a reduced risk of having a child with a neural tube defect. (Products containing this level of... neural tube defect, those with insulin-dependent diabetes mellitus, and women with seizure disorders who... mcg) when labeled for use by adults and children 4 or more years of age, or 800 mcg when labeled for...

  16. Epidemiology of neural tube defects in the world and Iran

    International Nuclear Information System (INIS)

    Farhud, D.; Hadavi, V.; Sadighi, H.

    2000-01-01

    Statistical data from 1996 till 1995, showed that Neural tube defects, in the American continent, Venezuela had the highest prevalence of 38.9 and some Latin American countries showed the low of 7.7. In Europe, Norway had the highest prevalence of 68, and Denmark the lowest, 5.8. In Asia, India had the highest of 181.8 and Japan the lowest of 10. In Africa, Nigeria had the highest of 70 and negroes of South Africa had the lowest of 9.9. In Australia the figure was 20.05. According to the statistics available of the years 1967 till 1996, anencephaly in China had the highest prevalence of 87. In the American continent, state of Michigan in the USA had the highest of 10.5 and Jamaica, in Central American, had the lowest of 2.6. In Europe, Turkey with 16.4 and Italy with 2.73; in Asia, China with 87 and Iran with 0.8 had the highest and the lowest pre valences, respectively. In Africa, Nigeria with 3.5, and in Oceania, New zealand with 7.8 in 10000, were reported. Data available on spin a bifida, from the years 1968 till 1991 showed, the highest prevalence in China with 36, and the lowest in the Alps mountains with 0.55 in 10000 individuals. In the American continent, state of Arkansas with 7.8 and California with 3.87; in Europe, England with 23.1 and Rein-Alp with 0.55 in 10000 had the highest and the lowest pre valences. Finally, in China this rate was 36, in Australia 10, in New zealand 9.4, and in Nigeria 7/10000. In a study carried out in Tehran, from 1969 till 1978 by the authors, out of 13037 birth, (17.6 in 10000) newborns had neural tube defects, with anencephaly 0.8 and spin a bifida 3.8/10000. In a new study on 8585 deliveries (1991-1997) in Hamadan (a north west Providence of Iran), Pre valences of total Nds was 50.1/10000, anencephaly 15.6 and spinabifida 6.98

  17. Neural Tube Defect in Alive Neonates: Incidence Rate and Predisposing Factors

    Directory of Open Access Journals (Sweden)

    F Haghollahi

    2008-06-01

    Full Text Available Background: Neural Tube Defect (NTD characterized by failure of neural tube to close properly be the second most common born defect after congenital heart disease. The most prevalent forms of NTD are Anencephaly and Spinal-bifida. Many factors are involved in this anomaly. New researches suggest environmental factors like radiation, hyperthermia, Vitamin A and acid folic deficiency, anti epileptic drug like Carbamazepine, Phenobarbital, phenytoin, Folic acid antagonist like Sulfasalazine, Triametherine and systemic disease like diabet mellitus, obesity, genetic factors, the most schance 40 to 70 percentages.Methods: In this survey cross sectional study was conducted in five hospitals depend to Tehran university during three years. Study subject identified through review of admission and discharge at major hospital through regular contact with newborn nurseries and birth hospital.Results: In 38473 reported cases, 143 cases have neural tube defect. Among NTD cases, 11.9% of mothers had medical diseases in their previous history such as diabetes mellitus, epilepsy-psychiatric, and disorder-heart diseases. In this study group, 5.6% have preclampsia during pregnancy period. The most common NTD anomaly in this study was anencephaly and meningomyelocele that was different from studies in literature.Conclusion: NTD result from failure of neural tube close threats fetus health up to 28 days after conception. When is often prior to the recognition of pregnancy since many pregnancy are unplanned NTD prevention is best achieve by adequate daily folic acid intake thought of reproductive ages .educational effort to promote daily intake of folic acid supplemental by women of reproductive age and NTD risk factor should be done. Early diagnostic procedure for high risk pregnancy advised.

  18. International retrospective cohort study of neural tube defects in relation to folic acid recommendations : are the recommendations working?

    NARCIS (Netherlands)

    Botto, LD; Lisi, A; Robert-Gnansia, E; Erickson, JD; Vollset, SE; Mastroiacovo, P; Botting, B; Cocchi, G; de Vigan, C; de Walle, H; Feijoo, M; Irgens, LM; McDonnell, B; Merlob, P; Ritvanen, A; Scarano, G; Siffel, C; Metneki, J; Stoll, C; Smithells, R; Goujard, J

    2005-01-01

    Objective To evaluate the effectiveness of policies and recommendations on folic acid aimed at reducing the occurrence of neural tube defects. Design Retrospective cohort study of births monitored by birth defect registries. Setting 13 birth defects registries monitoring rates of neural tube defects

  19. Genetic, chromosomal, and syndromic causes of neural tube defects

    Science.gov (United States)

    Seidahmed, Mohammed Z.; Abdelbasit, Omer B.; Shaheed, Meeralebbae M.; Alhussein, Khalid A.; Miqdad, Abeer M.; Samadi, Abdulmohsen S.; Khalil, Mohammed I.; Al-Mardawi, Elham; Salih, Mustafa A.

    2014-01-01

    Objective: To ascertain the incidence, and describe the various forms of neural tube defects (NTDs) due to genetic, chromosomal, and syndromic causes. Methods: We carried out a retrospective analysis of data retrieved from the medical records of newborn infants admitted to the Neonatal Intensive Care Unit with NTDs and their mothers spanning 14 years (1996-2009) at the Security Forces Hospital, Riyadh, Saudi Arabia. The cases were ascertained by a perinatologist, neonatologist, geneticist, radiologist, and neurologist. The literature was reviewed via a MEDLINE search. Only liveborn babies were included. Permission from the Educational Committee at the Security Forces Hospital was obtained prior to the collection of data. Results: Out of 103 infants with NTDs admitted during this period, 20 (19.4%) were found to have an underlying genetic syndromic, chromosomal and/or other anomalies. There were 5 cases of Meckel-Gruber syndrome, 2 Joubert syndrome, one Waardenburg syndrome, one Walker-Warburg syndrome, 2 chromosomal disorders, 2 caudal regression, one amniotic band disruption sequence, one associated with omphalocele, one with diaphragmatic hernia, and 4 with multiple congenital anomalies. Conclusions: There is a high rate of underlying genetic syndromic and/or chromosomal causes of NTDs in the Saudi Arabian population due to the high consanguinity rate. Identification of such association can lead to more accurate provisions of genetic counseling to the family including preimplantation genetic diagnosis or early termination of pregnancies associated with lethal conditions. PMID:25551112

  20. Genetic, chromosomal, and syndromic causes of neural tube defects.

    Science.gov (United States)

    Seidahmed, Mohammed Z; Abdelbasit, Omer B; Shaheed, Meeralebbae M; Alhussein, Khalid A; Miqdad, Abeer M; Samadi, Abdulmohsen S; Khalil, Mohammed I; Al-Mardawi, Elham; Salih, Mustafa A

    2014-12-01

    To ascertain the incidence, and describe the various forms of neural tube defects (NTDs) due to genetic, chromosomal, and syndromic causes. We carried out a retrospective analysis of data retrieved from the medical records of newborn infants admitted to the Neonatal Intensive Care Unit with NTDs and their mothers spanning 14 years (1996-2009) at the Security Forces Hospital, Riyadh, Saudi Arabia. The cases were ascertained by a perinatologist, neonatologist, geneticist, radiologist, and neurologist. The literature was reviewed via a MEDLINE search. Only liveborn babies were included. Permission from the Educational Committee at the Security Forces Hospital was obtained prior to the collection of data. Out of 103 infants with NTDs admitted during this period, 20 (19.4%) were found to have an underlying genetic syndromic, chromosomal and/or other anomalies. There were 5 cases of Meckel-Gruber syndrome, 2 Joubert syndrome, one Waardenburg syndrome, one Walker-Warburg syndrome, 2 chromosomal disorders, 2 caudal regression, one amniotic band disruption sequence, one associated with omphalocele, one with diaphragmatic hernia, and 4 with multiple congenital anomalies. There is a high rate of underlying genetic syndromic and/or chromosomal causes of NTDs in the Saudi Arabian population due to the high consanguinity rate. Identification of such association can lead to more accurate provisions of genetic counseling to the family including preimplantation genetic diagnosis or early termination of pregnancies associated with lethal conditions.

  1. neural control system

    International Nuclear Information System (INIS)

    Elshazly, A.A.E.

    2002-01-01

    Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior

  2. The Application of Helicopter Rotor Defect Detection Using Wavelet Analysis and Neural Network Technique

    Directory of Open Access Journals (Sweden)

    Jin-Li Sun

    2014-06-01

    Full Text Available When detect the helicopter rotor beam with ultrasonic testing, it is difficult to realize the noise removing and quantitative testing. This paper used the wavelet analysis technique to remove the noise among the ultrasonic detection signal and highlight the signal feature of defect, then drew the curve of defect size and signal amplitude. Based on the relationship of defect size and signal amplitude, a BP neural network was built up and the corresponding estimated value of the simulate defect was obtained by repeating training. It was confirmed that the wavelet analysis and neural network technique met the requirements of practical testing.

  3. Fetal Alcohol Spectrum Disorder (FASD) Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets.

    Science.gov (United States)

    Muralidharan, Pooja; Sarmah, Swapnalee; Zhou, Feng C; Marrs, James A

    2013-06-19

    Fetal alcohol spectrum disorder (FASD), caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.

  4. Fetal Alcohol Spectrum Disorder (FASD Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets

    Directory of Open Access Journals (Sweden)

    James A. Marrs

    2013-06-01

    Full Text Available Fetal alcohol spectrum disorder (FASD, caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.

  5. Feature selection for neural network based defect classification of ceramic components using high frequency ultrasound.

    Science.gov (United States)

    Kesharaju, Manasa; Nagarajah, Romesh

    2015-09-01

    The motivation for this research stems from a need for providing a non-destructive testing method capable of detecting and locating any defects and microstructural variations within armour ceramic components before issuing them to the soldiers who rely on them for their survival. The development of an automated ultrasonic inspection based classification system would make possible the checking of each ceramic component and immediately alert the operator about the presence of defects. Generally, in many classification problems a choice of features or dimensionality reduction is significant and simultaneously very difficult, as a substantial computational effort is required to evaluate possible feature subsets. In this research, a combination of artificial neural networks and genetic algorithms are used to optimize the feature subset used in classification of various defects in reaction-sintered silicon carbide ceramic components. Initially wavelet based feature extraction is implemented from the region of interest. An Artificial Neural Network classifier is employed to evaluate the performance of these features. Genetic Algorithm based feature selection is performed. Principal Component Analysis is a popular technique used for feature selection and is compared with the genetic algorithm based technique in terms of classification accuracy and selection of optimal number of features. The experimental results confirm that features identified by Principal Component Analysis lead to improved performance in terms of classification percentage with 96% than Genetic algorithm with 94%. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Syndromes and Disorders Associated with Omphalocele (III: Single Gene Disorders, Neural Tube Defects, Diaphragmatic Defects and Others

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2007-06-01

    Full Text Available Omphalocele can be associated with single gene disorders, neural tube defects, diaphragmatic defects, fetal valproate syndrome, and syndromes of unknown etiology. This article provides a comprehensive review of omphalocele-related disorders: otopalatodigital syndrome type II; Melnick–Needles syndrome; Rieger syndrome; neural tube defects; Meckel syndrome; Shprintzen–Goldberg omphalocele syndrome; lethal omphalocele-cleft palate syndrome; cerebro-costo-mandibular syndrome; fetal valproate syndrome; Marshall–Smith syndrome; fibrochondrogenesis; hydrolethalus syndrome; Fryns syndrome; omphalocele, diaphragmatic defects, radial anomalies and various internal malformations; diaphragmatic defects, limb deficiencies and ossification defects of skull; Donnai–Barrow syndrome; CHARGE syndrome; Goltz syndrome; Carpenter syndrome; Toriello–Carey syndrome; familial omphalocele; Cornelia de Lange syndrome; C syndrome; Elejalde syndrome; Malpuech syndrome; cervical ribs, Sprengel anomaly, anal atresia and urethral obstruction; hydrocephalus with associated malformations; Kennerknecht syndrome; lymphedema, atrial septal defect and facial changes; and craniosynostosis- mental retardation syndrome of Lin and Gettig. Perinatal identification of omphalocele should alert one to the possibility of omphalocele-related disorders and familial inheritance and prompt a thorough genetic counseling for these disorders.

  7. Identifying apple surface defects using principal components analysis and artifical neural networks

    Science.gov (United States)

    Artificial neural networks and principal components were used to detect surface defects on apples in near-infrared images. Neural networks were trained and tested on sets of principal components derived from columns of pixels from images of apples acquired at two wavelengths (740 nm and 950 nm). I...

  8. Histological evaluation of acute covering of an experimental neural tube defect with biomatrices in fetal sheep.

    NARCIS (Netherlands)

    Eggink, A.J.; Roelofs, L.A.J.; Lammens, M.M.Y.; Feitz, W.F.J.; Wijnen, R.M.H.; Mullaart, R.A.; Moerkerk, H.T.B. van; Kuppevelt, A.H.M.S.M. van; Crevels, A.J.; Hanssen, A.; Lotgering, F.K.; Berg, P.P. van den

    2006-01-01

    OBJECTIVE: The aim of the study was to determine the histological effect on the neural tissue of in utero covering of an experimental neural tube defect in fetal lambs, with the use of two different biomatrices. MATERIALS AND METHODS: In 23 fetal sheep, surgery was performed at 79 days' gestation.

  9. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  10. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  11. Mediterranean diet, folic acid, and neural tube defects.

    Science.gov (United States)

    Fischer, Maximilian; Stronati, Mauro; Lanari, Marcello

    2017-08-17

    The Mediterranean diet has been for a very long time the basis of food habits all over the countries of the Mediterranean basin, originally founded on rural models and low consumption of meat products and high-fat/high-processed foods. However, in the modern era, the traditional Mediterranean diet pattern is now progressively eroding due to the widespread dissemination of the Western-type economy, life-style, technology-driven culture, as well as the globalisation of food production, availability and consumption, with consequent homogenisation of food culture and behaviours. This transition process may affect many situations, including pregnancy and offspring's health. The problem of the diet during pregnancy and the proper intake of nutrients are nowadays a very current topic, arousing much debate. The Mediterranean dietary pattern, in particular, has been associated with the highest risk reduction of major congenital anomalies, like the heterogeneous class of neural tube defects (NTDs). NTDs constitute a major health burden (0.5-2/1000 pregnancies worldwide) and still remain a preventable cause of still birth, neonatal and infant death, or significant lifelong disabilities. Many studies support the finding that appropriate folate levels during pregnancy may confer protection against these diseases. In 1991 one randomised controlled trial (RCT) demonstrated for the first time that periconceptional supplementation of folic acid is able to prevent the recurrence of NTDs, finding confirmed by many other subsequent studies. Anyway, the high rate of unplanned/unintended pregnancies and births and other issues hindering the achievement of adequate folate levels in women in childbearing age, induced the US government and many other countries to institute mandatory food fortification with folic acid. The actual strategy adopted by European Countries (including Italy) suggests that women take 0,4 mg folic acid/die before conception. The main question is which intervention

  12. Application of artificial neural networks to evaluate weld defects of nuclear components

    International Nuclear Information System (INIS)

    Amin, E.S.

    2007-01-01

    Artificial neural networks (ANNs) are computational representations based on the biological neural architecture of the brain. ANNs have been successfully applied to a wide range of engineering and scientific applications, such as signal, image processing and data analysis. Although Radiographic testing is widely used for welding defects, it is unsuccessful in identifying some welding defects because of the nature of image formation and quality. Neoteric algorithms have been used for the purpose of weld defects identifications in radiographic images to replace the expert knowledge. The application of artificial neural networks in noise detection of radiographic films is used. Radial Basis (RB) and learning vector quantization (LVQ) were applied. The method shows good performance in weld defects recognition and classification problems.

  13. Genetic interactions between planar cell polarity genes cause diverse neural tube defects in mice

    Directory of Open Access Journals (Sweden)

    Jennifer N. Murdoch

    2014-10-01

    Full Text Available Neural tube defects (NTDs are among the commonest and most severe forms of developmental defect, characterized by disruption of the early embryonic events of central nervous system formation. NTDs have long been known to exhibit a strong genetic dependence, yet the identity of the genetic determinants remains largely undiscovered. Initiation of neural tube closure is disrupted in mice homozygous for mutations in planar cell polarity (PCP pathway genes, providing a strong link between NTDs and PCP signaling. Recently, missense gene variants have been identified in PCP genes in humans with NTDs, although the range of phenotypes is greater than in the mouse mutants. In addition, the sequence variants detected in affected humans are heterozygous, and can often be detected in unaffected individuals. It has been suggested that interactions between multiple heterozygous gene mutations cause the NTDs in humans. To determine the phenotypes produced in double heterozygotes, we bred mice with all three pairwise combinations of Vangl2Lp, ScribCrc and Celsr1Crsh mutations, the most intensively studied PCP mutants. The majority of double-mutant embryos had open NTDs, with the range of phenotypes including anencephaly and spina bifida, therefore reflecting the defects observed in humans. Strikingly, even on a uniform genetic background, variability in the penetrance and severity of the mutant phenotypes was observed between the different double-heterozygote combinations. Phenotypically, Celsr1Crsh;Vangl2Lp;ScribCrc triply heterozygous mutants were no more severe than doubly heterozygous or singly homozygous mutants. We propose that some of the variation between double-mutant phenotypes could be attributed to the nature of the protein disruption in each allele: whereas ScribCrc is a null mutant and produces no Scrib protein, Celsr1Crsh and Vangl2Lp homozygotes both express mutant proteins, consistent with dominant effects. The variable outcomes of these genetic

  14. Neural tube defects in Waardenburg syndrome: A case report and review of the literature.

    Science.gov (United States)

    Hart, Joseph; Miriyala, Kalpana

    2017-09-01

    Waardenburg syndrome type 1 (WS1) is an autosomal dominant genetic condition characterized by sensorineural deafness and pigment abnormalities, and is caused by variants in the PAX3 homeodomain. PAX3 variants have been associated with severe neural tube defects in mice and humans, but the frequency and clinical manifestations of this symptom remain largely unexplored in humans. Consequently, the role of PAX3 in human neural tube formation remains a study of interest, for clinical as well as research purposes. Though the association between spina bifida and WS1 is now well-documented, no study has attempted to characterize the range of spina bifida phenotypes seen in WS. Spina bifida encompasses several diagnoses with a wide scope of clinical severity, ranging from spina bifida occulta to myelomeningocele. We present a patient with Waardenburg syndrome type 1 caused by a novel missense variant in PAX3, presenting with myelomeningocele, Arnold-Chiari malformation, and hydrocephalus at birth. Additionally, we review 32 total cases of neural tube defects associated with WS. Including this report, there have been 15 published cases of myelomeningocele, 10 cases of unspecified spina bifida, 3 cases of sacral dimples, 0 cases of meningocele, and 4 cases of miscellaneous other neural tube defects. Though the true frequency of each phenotype cannot be determined from this collection of cases, these results demonstrate that Waardenburg syndrome type 1 carries a notable risk of severe neural tube defects, which has implications in prenatal and genetic counseling. © 2017 Wiley Periodicals, Inc.

  15. Digital detection system of surface defects for large aperture optical elements

    International Nuclear Information System (INIS)

    Fan Yong; Chen Niannian; Gao Lingling; Jia Yuan; Wang Junbo; Cheng Xiaofeng

    2009-01-01

    Based on the light defect images against the dark background in a scattering imaging system, a digital detection system of surface defects for large aperture optical elements has been presented. In the system, the image is segmented by a multi-area self-adaptive threshold segmentation method, then a pixel labeling method based on replacing arrays is adopted to extract defect features quickly, and at last the defects are classified through back-propagation neural networks. Experiment results show that the system can achieve real-time detection and classification. (authors)

  16. Intelligent neural network diagnostic system

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2010-01-01

    Recently, artificial neural network (ANN) has made a significant mark in the domain of diagnostic applications. Neural networks are used to implement complex non-linear mappings (functions) using simple elementary units interrelated through connections with adaptive weights. The performance of the ANN is mainly depending on their topology structure and weights. Some systems have been developed using genetic algorithm (GA) to optimize the topology of the ANN. But, they suffer from some limitations. They are : (1) The computation time requires for training the ANN several time reaching for the average weight required, (2) Slowness of GA for optimization process and (3) Fitness noise appeared in the optimization of ANN. This research suggests new issues to overcome these limitations for finding optimal neural network architectures to learn particular problems. This proposed methodology is used to develop a diagnostic neural network system. It has been applied for a 600 MW turbo-generator as a case of real complex systems. The proposed system has proved its significant performance compared to two common methods used in the diagnostic applications.

  17. A case of junctional neural tube defect associated with a lipoma of the filum terminale: a new subtype of junctional neural tube defect?

    Science.gov (United States)

    Florea, Simona Mihaela; Faure, Alice; Brunel, Hervé; Girard, Nadine; Scavarda, Didier

    2018-06-01

    The embryological development of the central nervous system takes place during the neurulation process, which includes primary and secondary neurulation. A new form of dysraphism, named junctional neural tube defect (JNTD), was recently reported, with only 4 cases described in the literature. The authors report a fifth case of JNTD. This 5-year-old boy, who had been operated on during his 1st month of life for a uretero-rectal fistula, was referred for evaluation of possible spinal dysraphism. He had urinary incontinence, clubfeet, and a history of delayed walking ability. MRI showed a spinal cord divided in two, with an upper segment ending at the T-11 level and a lower segment at the L5-S1 level, with a thickened filum terminale. The JNTDs represent a recently classified dysraphism caused by an error during junctional neurulation. The authors suggest that their patient should be included in this category as the fifth case reported in the literature and note that this would be the first reported case of JNTD in association with a lipomatous filum terminale.

  18. A spontaneous and novel Pax3 mutant mouse that models Waardenburg syndrome and neural tube defects.

    Science.gov (United States)

    Ohnishi, Tetsuo; Miura, Ikuo; Ohba, Hisako; Shimamoto, Chie; Iwayama, Yoshimi; Wakana, Shigeharu; Yoshikawa, Takeo

    2017-04-05

    Genes responsible for reduced pigmentation phenotypes in rodents are associated with human developmental defects, such as Waardenburg syndrome, where patients display congenital deafness along with various abnormalities mostly related to neural crest development deficiency. In this study, we identified a spontaneous mutant mouse line Rwa, which displays variable white spots on mouse bellies and white digits and tail, on a C57BL/6N genetic background. Curly tail and spina bifida were also observed, although at a lower penetrance. These phenotypes were dominantly inherited by offspring. We searched for the genetic mechanism of the observed phenotypes. We harnessed a rapid mouse gene mapping system newly developed in our laboratories to identify a responsible gene. We detected a region within chromosome 1 as a probable locus for the causal mutation. Dense mapping using interval markers narrowed the locus down to a 670-kbp region, containing four genes including Pax3, a gene known to be implicated in the types I and III Waardenburg syndrome. Extensive mutation screening of Pax3 detected an 841-bp deletion, spanning the promoter region and intron 1 of the gene. The defective allele of Pax3, named Pax3 Rwa , lacked the first coding exon and co-segregated perfectly with the phenotypes, confirming its causal nature. The genetic background of Rwa mice is almost identical to that of inbred C57BL/6N. These results highlight Pax3 Rwa mice as a beneficial tool for analyzing biological processes involving Pax3, in particular the development and migration of neural crest cells and melanocytes. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. A fast button surface defects detection method based on convolutional neural network

    Science.gov (United States)

    Liu, Lizhe; Cao, Danhua; Wu, Songlin; Wu, Yubin; Wei, Taoran

    2018-01-01

    Considering the complexity of the button surface texture and the variety of buttons and defects, we propose a fast visual method for button surface defect detection, based on convolutional neural network (CNN). CNN has the ability to extract the essential features by training, avoiding designing complex feature operators adapted to different kinds of buttons, textures and defects. Firstly, we obtain the normalized button region and then use HOG-SVM method to identify the front and back side of the button. Finally, a convolutional neural network is developed to recognize the defects. Aiming at detecting the subtle defects, we propose a network structure with multiple feature channels input. To deal with the defects of different scales, we take a strategy of multi-scale image block detection. The experimental results show that our method is valid for a variety of buttons and able to recognize all kinds of defects that have occurred, including dent, crack, stain, hole, wrong paint and uneven. The detection rate exceeds 96%, which is much better than traditional methods based on SVM and methods based on template match. Our method can reach the speed of 5 fps on DSP based smart camera with 600 MHz frequency.

  20. Folic acid supplementation influences the distribution of neural tube defect subtypes : A registry-based study

    NARCIS (Netherlands)

    Bergman, J. E. H.; Otten, E.; Verheij, J. B. G. M.; de Walle, H. E. K.

    Periconceptional folic acid (FA) reduces neural tube defect (NTD) risk, but seems to have a varying effect per NTD subtype. We aimed to study the effect of FA supplementation on NTD subtype distribution using data from EUROCAT Northern Netherlands. We included all birth types with non-syndromal NTDs

  1. Folic Acid for the Prevention of Neural Tube Defects : US Preventive Services Task Force Recommendation Statement

    NARCIS (Netherlands)

    Calonge, Ned; Petitti, Diana B.; DeWitt, Thomas G.; Dietrich, Allen J.; Gregory, Kimberly D.; Grossman, David; Isham, George; LeFevre, Michael L.; Leipzig, Rosanne M.; Marion, Lucy N.; Melnyk, Bernadette; Moyer, Virginia A.; Ockene, Judith K.; Sawaya, George F.; Schwartz, J. Sanford; Wilt, Timothy

    2009-01-01

    Description: In 1996, the U. S. Preventive Services Task Force (USPSTF) recommended that all women planning or capable of pregnancy take a multivitamin supplement containing folic acid for the prevention of neural tube defects. This recommendation is an update of the 1996 USPSTF recommendation.

  2. Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation

    CSIR Research Space (South Africa)

    Ngwangwa, HM

    2010-04-01

    Full Text Available -1 Journal of Terramechanics Volume 47, Issue 2, April 2010, Pages 97-111 Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation H.M. Ngwangwaa, P.S. Heynsa, , , F...

  3. Lack of association between folate-receptor autoantibodies and neural-tube defects.

    LENUS (Irish Health Repository)

    Molloy, Anne M

    2009-07-09

    BACKGROUND: A previous report described the presence of autoantibodies against folate receptors in 75% of serum samples from women with a history of pregnancy complicated by a neural-tube defect, as compared with 10% of controls. We sought to confirm this finding in an Irish population, which traditionally has had a high prevalence of neural-tube defects. METHODS: We performed two studies. Study 1 consisted of analysis of stored frozen blood samples collected from 1993 through 1994 from 103 mothers with a history of pregnancy complicated by a neural-tube defect (case mothers), 103 mothers with a history of pregnancy but no complication by a neural-tube defect (matched with regard to number of pregnancies and sampling dates), 58 women who had never been pregnant, and 36 men. Study 2, conducted to confirm that the storage of samples did not influence the folate-receptor autoantibodies, included fresh samples from 37 case mothers, 22 control mothers, 10 women who had never been pregnant, and 9 men. All samples were assayed for blocking and binding autoantibodies against folate receptors. RESULTS: In Study 1, blocking autoantibodies were found in 17% of case mothers, as compared with 13% of control mothers (odds ratio, 1.54; 95% confidence interval [CI], 0.70 to 3.39), and binding autoantibodies in 29%, as compared with 32%, respectively (odds ratio, 0.82; 95% CI, 0.44 to 1.50). Study 2 showed similar results, indicating that sample degradation was unlikely. CONCLUSIONS: The presence and titer of maternal folate-receptor autoantibodies were not significantly associated with a neural-tube defect-affected pregnancy in this Irish population.

  4. Expression of p53/HGF/c-met/STAT3 signal in fetuses with neural tube defects.

    Science.gov (United States)

    Trovato, Maria; D'Armiento, Maria; Lavra, Luca; Ulivieri, Alessandra; Dominici, Roberto; Vitarelli, Enrica; Grosso, Maddalena; Vecchione, Raffaella; Barresi, Gaetano; Sciacchitano, Salvatore

    2007-02-01

    Neural tube defects (NTD) are morphogenetic alterations due to a defective closure of neural tube. Hepatocyte growth factor (HGF)/c-met system plays a role in morphogenesis of nervous system, lung, and kidney. HGF/c-met morphogenetic effects are mediated by signal transducers and activators of transcription (STAT)3 and both HGF and c-met genes are regulated from p53. The aim of our study was to analyze mRNA and protein expressions of p53, HGF, c-met, and STAT3 in fetuses with NTD. By reverse transcriptase-polymerase chain reaction and immunohistochemistry, we analyzed neural tissues from four NTD fetuses and the corresponding non-malformed lungs, kidneys and placentas. We found a reduced mRNA expression of HGF/c-met/STAT3 pathway, in the malformed nervous systems and placentas. The reduced expression of this pathway correlated with the absence of p53 in all these samples. On the contrary, detectable expression levels of p53, HGF, c-met, and STAT3 were observed in non-malformed lungs and kidneys obtained from the same fetuses. Comparable results were obtained by immunohistochemistry, with the exception of p53, which was undetected in all fetal tissues. In conclusion, in NTD fetuses, both the defective neural tube tissue and the placenta have a reduction in all components of the p53/HGF/c-met/STAT3 cascade. This raises the possibility of using the suppression of these genes for early diagnosis of NTD especially on chorionic villus sampling.

  5. Air Pollution, Neighbourhood Socioeconomic Factors, and Neural Tube Defects in the San Joaquin Valley of California.

    Science.gov (United States)

    Padula, Amy M; Yang, Wei; Carmichael, Suzan L; Tager, Ira B; Lurmann, Frederick; Hammond, S Katharine; Shaw, Gary M

    2015-11-01

    Environmental pollutants and neighbourhood socioeconomic factors have been associated with neural tube defects, but the potential impact of interaction between ambient air pollution and neighbourhood socioeconomic factors on the risks of neural tube defects is not well understood. We used data from the California Center of the National Birth Defects Study and the Children's Health and Air Pollution Study to investigate whether associations between air pollutant exposure in early gestation and neural tube defects were modified by neighbourhood socioeconomic factors in the San Joaquin Valley of California, 1997-2006. There were 5 pollutant exposures, 3 outcomes, and 9 neighbourhood socioeconomic factors included for a total of 135 investigated associations. Estimates were adjusted for maternal race-ethnicity, education, and multivitamin use. We present below odds ratios (ORs) that exclude 1 and a chi-square test of homogeneity P-value of <0.05. We observed increased odds of spina bifida comparing the highest to lowest quartile of particulate matter <10 μm (PM10 ) among those living in a neighbourhood with: (i) median household income of less than $30 000 per year [OR 5.1, 95% confidence interval (CI) 1.7, 15.3]; (ii) more than 20% living below the federal poverty level (OR 2.6, 95% CI 1.1, 6.0); and (iii) more than 30% with less than or equal to a high school education (OR 3.2, 95% CI 1.4, 7.4). The ORs were not statistically significant among those higher socioeconomic status (SES) neighbourhoods. Our results demonstrate effect modification by neighbourhood socioeconomic factors in the association of particulate matter and neural tube defects in California. © 2015 John Wiley & Sons Ltd.

  6. Unjoined primary and secondary neural tubes: junctional neural tube defect, a new form of spinal dysraphism caused by disturbance of junctional neurulation.

    Science.gov (United States)

    Eibach, Sebastian; Moes, Greg; Hou, Yong Jin; Zovickian, John; Pang, Dachling

    2017-10-01

    Primary and secondary neurulation are the two known processes that form the central neuraxis of vertebrates. Human phenotypes of neural tube defects (NTDs) mostly fall into two corresponding categories consistent with the two types of developmental sequence: primary NTD features an open skin defect, an exposed, unclosed neural plate (hence an open neural tube defect, or ONTD), and an unformed or poorly formed secondary neural tube, and secondary NTD with no skin abnormality (hence a closed NTD) and a malformed conus caudal to a well-developed primary neural tube. We encountered three cases of a previously unrecorded form of spinal dysraphism in which the primary and secondary neural tubes are individually formed but are physically separated far apart and functionally disconnected from each other. One patient was operated on, in whom both the lumbosacral spinal cord from primary neurulation and the conus from secondary neurulation are each anatomically complete and endowed with functioning segmental motor roots tested by intraoperative triggered electromyography and direct spinal cord stimulation. The remarkable feature is that the two neural tubes are unjoined except by a functionally inert, probably non-neural band. The developmental error of this peculiar malformation probably occurs during the critical transition between the end of primary and the beginning of secondary neurulation, in a stage aptly called junctional neurulation. We describe the current knowledge concerning junctional neurulation and speculate on the embryogenesis of this new class of spinal dysraphism, which we call junctional neural tube defect.

  7. A novel inspection system for cosmetic defects

    Science.gov (United States)

    Hazra, S.; Roy, R.; Williams, D.; Aylmore, R.; Hollingdale, D.

    2013-12-01

    The appearance of automotive skin panels creates desirability for a product and differentiates it from the competition. Because of the importance of skin panels, considerable care is taken in minimizing defects such as the 'hollow' defect that occur around door-handle depressions. However, the inspection process is manual, subjective and time-consuming. This paper describes the development of an objective and inspection scheme for the 'hollow' defect. In this inspection process, the geometry of a panel is captured using a structured lighting system. The geometry data is subsequently analyzed by a purpose-built wavelet-based algorithm to identify the location of any defects that may be present and to estimate the perceived severity of the defects without user intervention. This paper describes and critically evaluates the behavior of this physically-based algorithm on an ideal and real geometry and compares its result to an actual audit. The results show that the algorithm is capable of objectively locating and classifying 'hollow' defects in actual panels.

  8. A neural network approach to discrimination between defects and calyces in oranges

    Directory of Open Access Journals (Sweden)

    Salvatore Ingrassia

    1993-11-01

    Full Text Available The problem of automatic discrimination among pictures concerning either defects or calyces in oranges is approached. The method here proposed is based on a statistical analysis of the grey-levels and the shape of calyces in the pictures. Some suitable statistical indices are considered and the discriminant function is designed by means of a neural network on the basis of a suitable vector representation of the images. Numerical experiments give 5 misclassifications in a set of 52 images, where only three defects have been classified as calyces.

  9. Risk of central nervous system defects in offspring of women with and without mental illness.

    Science.gov (United States)

    Ayoub, Aimina; Fraser, William D; Low, Nancy; Arbour, Laura; Healy-Profitós, Jessica; Auger, Nathalie

    2018-02-22

    We sought to determine the relationship between maternal mental illness and the risk of having an infant with a central nervous system defect. We analyzed a cohort of 654,882 women aged less than 20 years between 1989 and 2013 who later delivered a live born infant in any hospital in Quebec, Canada. The primary exposure was mental illness during pregnancy or hospitalization for mental illness before pregnancy. The outcomes were neural and non-neural tube defects of the central nervous system in any offspring. We computed risk ratios (RR) and 95% confidence intervals (CI) for the association between mental disorders and risk of central nervous system defects in log-binomial regression models adjusted for age at delivery, total parity, comorbidity, socioeconomic deprivation, place of residence, and time period. Maternal mental illness was associated with an increased risk of nervous system defects in offspring (RR 1.76, 95% CI 1.64-1.89). Hospitalization for any mental disorder was more strongly associated with non-neural tube (RR 1.84, 95% CI 1.71-1.99) than neural tube defects (RR 1.31, 95% CI 1.08-1.59). Women at greater risk of nervous system defects in offspring tended to be diagnosed with multiple mental disorders, have more than one hospitalization for mental disease, or be 17 or older at first hospitalization. A history of mental illness is associated with central nervous system defects in offspring. Women hospitalized for mental illness may merit counseling at first symptoms to prevent central nervous system defects at pregnancy.

  10. The LILARTI neural network system

    Energy Technology Data Exchange (ETDEWEB)

    Allen, J.D. Jr.; Schell, F.M.; Dodd, C.V.

    1992-10-01

    The material of this Technical Memorandum is intended to provide the reader with conceptual and technical background information on the LILARTI neural network system of detail sufficient to confer an understanding of the LILARTI method as it is presently allied and to facilitate application of the method to problems beyond the scope of this document. Of particular importance in this regard are the descriptive sections and the Appendices which include operating instructions, partial listings of program output and data files, and network construction information.

  11. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (IV)

    OpenAIRE

    Chen, Chih-Ping

    2008-01-01

    Fetuses with neural tube defects (NTDs) may be associated with maternal and fetal risk factors. This article provides a comprehensive review of maternal and fetal risk factors associated with NTDs, such as infertility, periconceptional clomiphene use and assisted reproductive technology, periconceptional folic acid deficiency and effects offolic acid supplementation and fortification on NTD rates, periconceptional vitamin B1 2 deficiency, single nucleotide polymorphisms and polymorphisms in g...

  12. Maternal bereavement in the antenathal period and Neural tube defect in the offspring

    DEFF Research Database (Denmark)

    Ingstrup, Katja Glejsted; Olsen, Jørn; Bech, Bodil Hammer

    2013-01-01

    Title: Maternal bereavement after death of a close relative and neural tube defect in the offspring Background: Neural tube defects are the second most common and often lethal congenital anomaly in the world leaving surviving children with life-long severe disabilities. A low intake of folic acid...... was seen (OR 1.61, 95% CI: 1.07; 2.41). Discussion: We only studied live born children but about 2/3 of children with spina bifida survive the birth or longer with corrective surgery. We did not adjust for folic acid, but a sub-analysis of approximately 85,000 mothers showed no difference in intake during...... all children born in Denmark from 1978-2008 and their mothers (n=1,734,190). In the time window of one year before pregnancy or during the first trimester of pregnancy 34,407 mothers were exposed to bereavement. Results: A total of 5,031 cases of neural tube defects were identified: 889 with spina...

  13. Development of test algorithm for semiconductor package with defects by using probabilistic neural network

    International Nuclear Information System (INIS)

    Kim, Jae Yeol; Sim, Jae Gi; Ko, Myoung Soo; Kim, Chang Hyun; Kim, Hun Cho

    2001-01-01

    In this study, researchers developing the estimative algorithm for artificial defects in semiconductor packages and performing it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Probabilistic Neural Network. Self-Organizing Map and Probabilistic Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages. This study presumes probability density function from a sample of learning and present which is automatically determine method. PNN can distinguish flaws very difficult distinction as well as. This can do parallel process to stand in a row we confirm that is very efficiently classifier if we applied many data real the process.

  14. The Drosophila Neurally Altered Carbohydrate Mutant Has a Defective Golgi GDP-fucose Transporter*

    Science.gov (United States)

    Geisler, Christoph; Kotu, Varshika; Sharrow, Mary; Rendić, Dubravko; Pöltl, Gerald; Tiemeyer, Michael; Wilson, Iain B. H.; Jarvis, Donald L.

    2012-01-01

    Studying genetic disorders in model organisms can provide insights into heritable human diseases. The Drosophila neurally altered carbohydrate (nac) mutant is deficient for neural expression of the HRP epitope, which consists of N-glycans with core α1,3-linked fucose residues. Here, we show that a conserved serine residue in the Golgi GDP-fucose transporter (GFR) is substituted by leucine in nac1 flies, which abolishes GDP-fucose transport in vivo and in vitro. This loss of function is due to a biochemical defect, not to destabilization or mistargeting of the mutant GFR protein. Mass spectrometry and HPLC analysis showed that nac1 mutants lack not only core α1,3-linked, but also core α1,6-linked fucose residues on their N-glycans. Thus, the nac1 Gfr mutation produces a previously unrecognized general defect in N-glycan core fucosylation. Transgenic expression of a wild-type Gfr gene restored the HRP epitope in neural tissues, directly demonstrating that the Gfr mutation is solely responsible for the neural HRP epitope deficiency in the nac1 mutant. These results validate the Drosophila nac1 mutant as a model for the human congenital disorder of glycosylation, CDG-IIc (also known as LAD-II), which is also the result of a GFR deficiency. PMID:22745127

  15. Defect detection and classification of galvanized stamping parts based on fully convolution neural network

    Science.gov (United States)

    Xiao, Zhitao; Leng, Yanyi; Geng, Lei; Xi, Jiangtao

    2018-04-01

    In this paper, a new convolution neural network method is proposed for the inspection and classification of galvanized stamping parts. Firstly, all workpieces are divided into normal and defective by image processing, and then the defective workpieces extracted from the region of interest (ROI) area are input to the trained fully convolutional networks (FCN). The network utilizes an end-to-end and pixel-to-pixel training convolution network that is currently the most advanced technology in semantic segmentation, predicts result of each pixel. Secondly, we mark the different pixel values of the workpiece, defect and background for the training image, and use the pixel value and the number of pixels to realize the recognition of the defects of the output picture. Finally, the defect area's threshold depended on the needs of the project is set to achieve the specific classification of the workpiece. The experiment results show that the proposed method can successfully achieve defect detection and classification of galvanized stamping parts under ordinary camera and illumination conditions, and its accuracy can reach 99.6%. Moreover, it overcomes the problem of complex image preprocessing and difficult feature extraction and performs better adaptability.

  16. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  17. Evaluation of the prenatal diagnosis of neural tube defects by fetal ultrasonographic examination in different centres across Europe

    NARCIS (Netherlands)

    Boyd, PA; Wellesley, DG; De Walle, HEK; Tenconi, R; Garcia-Minaur, S; Zandwijken, GRJ; Stoll, C; Clementi, M

    2000-01-01

    Objective-Evaluation of prenatal diagnosis of neural tube defects by ultrasound examination in unselected populations across Europe. Setting-Prenatal ultrasound units in areas that report to contributing congenital malformation registers. Methods-All cases with a suspected or confirmed neural tube

  18. Yarn-dyed fabric defect classification based on convolutional neural network

    Science.gov (United States)

    Jing, Junfeng; Dong, Amei; Li, Pengfei; Zhang, Kaibing

    2017-09-01

    Considering that manual inspection of the yarn-dyed fabric can be time consuming and inefficient, we propose a yarn-dyed fabric defect classification method by using a convolutional neural network (CNN) based on a modified AlexNet. CNN shows powerful ability in performing feature extraction and fusion by simulating the learning mechanism of human brain. The local response normalization layers in AlexNet are replaced by the batch normalization layers, which can enhance both the computational efficiency and classification accuracy. In the training process of the network, the characteristics of the defect are extracted step by step and the essential features of the image can be obtained from the fusion of the edge details with several convolution operations. Then the max-pooling layers, the dropout layers, and the fully connected layers are employed in the classification model to reduce the computation cost and extract more precise features of the defective fabric. Finally, the results of the defect classification are predicted by the softmax function. The experimental results show promising performance with an acceptable average classification rate and strong robustness on yarn-dyed fabric defect classification.

  19. Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.

    Science.gov (United States)

    Kumudha, P; Venkatesan, R

    Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

  20. Neural Control of the Immune System

    Science.gov (United States)

    Sundman, Eva; Olofsson, Peder S.

    2014-01-01

    Neural reflexes support homeostasis by modulating the function of organ systems. Recent advances in neuroscience and immunology have revealed that neural reflexes also regulate the immune system. Activation of the vagus nerve modulates leukocyte cytokine production and alleviates experimental shock and autoimmune disease, and recent data have…

  1. [Difficulties of the methods for studying environmental exposure and neural tube defects].

    Science.gov (United States)

    Borja-Aburto, V H; Bermúdez-Castro, O; Lacasaña-Navarro, M; Kuri, P; Bustamante-Montes, P; Torres-Meza, V

    1999-01-01

    To discuss the attitudes in the assessment of environmental exposures as risk factors associated with neural tube defects, and to present the main risk factors studied to date. Environmental exposures have been suggested to have a roll in the genesis of birth defects. However, studies conducted in human populations have found difficulties in the design and conduction to show such an association for neural tube defects (anencephaly, espina bifida and encephalocele) because of problems raised from: a) the frequency measures used to compare time trends and communities, b) the classification of heterogeneous malformations, c) the inclusion of maternal, paternal and fetal factors as an integrated process and, d) the assessment of environmental exposures. Hypothetically both maternal and paternal environmental exposures can produce damage before and after conception by direct action on the embryo and the fetus-placenta complex. Therefore, in the assessment of environmental exposures we need to take into account: a) both paternal and maternal exposures; b) the critical exposure period, three months before conception for paternal exposures and one month around the conceptional period for maternal exposures; c) quantitatively evaluate environmental exposures when possible, avoiding a dichotomous classification; d) the use of biological markers of exposure is highly recommended as well as markers of genetic susceptibility.

  2. Classification of Atrial Septal Defect and Ventricular Septal Defect with Documented Hemodynamic Parameters via Cardiac Catheterization by Genetic Algorithms and Multi-Layered Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Mustafa Yıldız

    2012-08-01

    Full Text Available Introduction: We aimed to develop a classification method to discriminate ventricular septal defect and atrial septal defect by using severalhemodynamic parameters.Patients and Methods: Forty three patients (30 atrial septal defect, 13 ventricular septal defect; 26 female, 17 male with documentedhemodynamic parameters via cardiac catheterization are included to study. Such parameters as blood pressure values of different areas,gender, age and Qp/Qs ratios are used for classification. Parameters, we used in classification are determined by divergence analysismethod. Those parameters are; i pulmonary artery diastolic pressure, ii Qp/Qs ratio, iii right atrium pressure, iv age, v pulmonary arterysystolic pressure, vi left ventricular sistolic pressure, vii aorta mean pressure, viii left ventricular diastolic pressure, ix aorta diastolicpressure, x aorta systolic pressure. Those parameters detected from our study population, are uploaded to multi-layered artificial neuralnetwork and the network was trained by genetic algorithm.Results: Trained cluster consists of 14 factors (7 atrial septal defect and 7 ventricular septal defect. Overall success ratio is 79.2%, andwith a proper instruction of artificial neural network this ratio increases up to 89%.Conclusion: Parameters, belonging to artificial neural network, which are needed to be detected by the investigator in classical methods,can easily be detected with the help of genetic algorithms. During the instruction of artificial neural network by genetic algorithms, boththe topology of network and factors of network can be determined. During the test stage, elements, not included in instruction cluster, areassumed as in test cluster, and as a result of this study, we observed that multi-layered artificial neural network can be instructed properly,and neural network is a successful method for aimed classification.

  3. Appling a Novel Cost Function to Hopfield Neural Network for Defects Boundaries Detection of Wood Image

    Directory of Open Access Journals (Sweden)

    Qi Dawei

    2010-01-01

    Full Text Available A modified Hopfield neural network with a novel cost function was presented for detecting wood defects boundary in the image. Different from traditional methods, the boundary detection problem in this paper was formulated as an optimization process that sought the boundary points to minimize a cost function. An initial boundary was estimated by Canny algorithm first. The pixel gray value was described as a neuron state of Hopfield neural network. The state updated till the cost function touches the minimum value. The designed cost function ensured that few neurons were activated except the neurons corresponding to actual boundary points and ensured that the activated neurons are positioned in the points which had greatest change in gray value. The tools of Matlab were used to implement the experiment. The results show that the noises of the image are effectively removed, and our method obtains more noiseless and vivid boundary than those of the traditional methods.

  4. Access to health care for children with neural tube defects: Experiences of mothers in Zambia

    Directory of Open Access Journals (Sweden)

    Micah M. Simpamba

    2016-12-01

    Full Text Available Introduction: In Zambia, all children born with neural tube defects requiring surgery need to be referred to a tertiary level hospital in Lusaka, the capital city, where the specialists are based. The aim of this study was to explore the experiences of mothers accessing health care who had recently given birth to a child with a neural tube defect. Methods and analysis: In-depth interviews were conducted with a purposively selected sample of 20 mothers at the tertiary level hospital. The interviews were audiotaped, transcribed verbatim and translated. Content analysis was used to identify codes, which were later collapsed into categories and themes. Findings: Five themes emerged: access to health care, access to transport, access to information, concerns about family and support needs. Discussion: Barriers to access to health care included geographical barriers and barriers linked to availability. Geographical barriers were related to distance between home and the health centre, and referral between health facilities. Barriers to availability included the lack of specialist health workers at various levels, and insufficient hospital vehicles to transport mothers and children to the tertiary level hospital. The main barrier to affordability was the cost of transport, which was alleviated by either family or government support. Acceptability of the health services was affected by a lack of information, incorrect advice, the attitude of health workers and the beliefs of the family. Conclusion: Access to health care by mothers of children with neural tube defects in Zambia is affected by geographical accessibility, availability, affordability and acceptability. The supply-side barriers and demand-side barriers require different interventions to address them. This suggests that health policy is needed which ensures access to surgery and follow-up care.

  5. Birth prevalence of neural tube defects and orofacial clefts in India: a systematic review and meta-analysis.

    Directory of Open Access Journals (Sweden)

    Komal Preet Allagh

    Full Text Available In the last two decades, India has witnessed a substantial decrease in infant mortality attributed to infectious disease and malnutrition. However, the mortality attributed to birth defects remains constant. Studies on the prevalence of birth defects such as neural tube defects and orofacial clefts in India have reported inconsistent results. Therefore, we conducted a systematic review of observational studies to document the birth prevalence of neural tube defects and orofacial clefts.A comprehensive literature search for observational studies was conducted in MEDLINE and EMBASE databases using key MeSH terms (neural tube defects OR cleft lip OR cleft palate AND Prevalence AND India. Two reviewers independently reviewed the retrieved studies, and studies satisfying the eligibility were included. The quality of included studies was assessed using selected criteria from STROBE statement.The overall pooled birth prevalence (random effect of neural tube defects in India is 4.5 per 1000 total births (95% CI 4.2 to 4.9. The overall pooled birth prevalence (random effect of orofacial clefts is 1.3 per 1000 total births (95% CI 1.1 to 1.5. Subgroup analyses were performed by region, time period, consanguinity, and gender of newborn.The overall prevalence of neural tube defects from India is high compared to other regions of the world, while that of orofacial clefts is similar to other countries. The majority of studies included in the review were hospital based. The quality of these studies ranged from low to moderate. Further well-designed, high quality community-based observational studies are needed to accurately estimate the burden of neural tube defects and orofacial clefts in India.

  6. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (II

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-03-01

    Full Text Available Fetuses with neural tube defects (NTDs maybe associated with syndromes, disorders, and maternal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal risk factors associated with NTDs, such as Currarino syndrome, sacral defect with anterior meningocele, Jarcho-Levin syndrome (spondylo-costal dysostosis, lateral meningocele syndrome, neurofibromatosis type I, Marfan syndrome, and hyperthermia. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders, and maternal risk factors may be different from those of non-syndromic multifactorial NTDs. Perinatal identification of NTDs should alert one to the syndromes, disorders, and maternal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling.

  7. Nanodiamonds with silicon vacancy defects for nontoxic photostable fluorescent labeling of neural precursor cells.

    Science.gov (United States)

    Merson, Tobias D; Castelletto, Stefania; Aharonovich, Igor; Turbic, Alisa; Kilpatrick, Trevor J; Turnley, Ann M

    2013-10-15

    Nanodiamonds (NDs) containing silicon vacancy (SiV) defects were evaluated as a potential biomarker for the labeling and fluorescent imaging of neural precursor cells (NPCs). SiV-containing NDs were synthesized using chemical vapor deposition and silicon ion implantation. Spectrally, SiV-containing NDs exhibited extremely stable fluorescence and narrow bandwidth emission with an excellent signal to noise ratio exceeding that of NDs containing nitrogen-vacancy centers. NPCs labeled with NDs exhibited normal cell viability and proliferative properties consistent with biocompatibility. We conclude that SiV-containing NDs are a promising biomedical research tool for cellular labeling and optical imaging in stem cell research.

  8. Describing the Prevalence of Neural Tube Defects Worldwide: A Systematic Literature Review.

    Science.gov (United States)

    Zaganjor, Ibrahim; Sekkarie, Ahlia; Tsang, Becky L; Williams, Jennifer; Razzaghi, Hilda; Mulinare, Joseph; Sniezek, Joseph E; Cannon, Michael J; Rosenthal, Jorge

    2016-01-01

    Folate-sensitive neural tube defects (NTDs) are an important, preventable cause of morbidity and mortality worldwide. There is a need to describe the current global burden of NTDs and identify gaps in available NTD data. We conducted a systematic review and searched multiple databases for NTD prevalence estimates and abstracted data from peer-reviewed literature, birth defects surveillance registries, and reports published between January 1990 and July 2014 that had greater than 5,000 births and were not solely based on mortality data. We classified countries according to World Health Organization (WHO) regions and World Bank income classifications. The initial search yielded 11,614 results; after systematic review we identified 160 full text manuscripts and reports that met the inclusion criteria. Data came from 75 countries. Coverage by WHO region varied in completeness (i.e., % of countries reporting) as follows: African (17%), Eastern Mediterranean (57%), European (49%), Americas (43%), South-East Asian (36%), and Western Pacific (33%). The reported NTD prevalence ranges and medians for each region were: African (5.2-75.4; 11.7 per 10,000 births), Eastern Mediterranean (2.1-124.1; 21.9 per 10,000 births), European (1.3-35.9; 9.0 per 10,000 births), Americas (3.3-27.9; 11.5 per 10,000 births), South-East Asian (1.9-66.2; 15.8 per 10,000 births), and Western Pacific (0.3-199.4; 6.9 per 10,000 births). The presence of a registry or surveillance system for NTDs increased with country income level: low income (0%), lower-middle income (25%), upper-middle income (70%), and high income (91%). Many WHO member states (120/194) did not have any data on NTD prevalence. Where data are collected, prevalence estimates vary widely. These findings highlight the need for greater NTD surveillance efforts, especially in lower-income countries. NTDs are an important public health problem that can be prevented with folic acid supplementation and fortification of staple foods.

  9. Describing the Prevalence of Neural Tube Defects Worldwide: A Systematic Literature Review.

    Directory of Open Access Journals (Sweden)

    Ibrahim Zaganjor

    Full Text Available Folate-sensitive neural tube defects (NTDs are an important, preventable cause of morbidity and mortality worldwide. There is a need to describe the current global burden of NTDs and identify gaps in available NTD data.We conducted a systematic review and searched multiple databases for NTD prevalence estimates and abstracted data from peer-reviewed literature, birth defects surveillance registries, and reports published between January 1990 and July 2014 that had greater than 5,000 births and were not solely based on mortality data. We classified countries according to World Health Organization (WHO regions and World Bank income classifications. The initial search yielded 11,614 results; after systematic review we identified 160 full text manuscripts and reports that met the inclusion criteria. Data came from 75 countries. Coverage by WHO region varied in completeness (i.e., % of countries reporting as follows: African (17%, Eastern Mediterranean (57%, European (49%, Americas (43%, South-East Asian (36%, and Western Pacific (33%. The reported NTD prevalence ranges and medians for each region were: African (5.2-75.4; 11.7 per 10,000 births, Eastern Mediterranean (2.1-124.1; 21.9 per 10,000 births, European (1.3-35.9; 9.0 per 10,000 births, Americas (3.3-27.9; 11.5 per 10,000 births, South-East Asian (1.9-66.2; 15.8 per 10,000 births, and Western Pacific (0.3-199.4; 6.9 per 10,000 births. The presence of a registry or surveillance system for NTDs increased with country income level: low income (0%, lower-middle income (25%, upper-middle income (70%, and high income (91%.Many WHO member states (120/194 did not have any data on NTD prevalence. Where data are collected, prevalence estimates vary widely. These findings highlight the need for greater NTD surveillance efforts, especially in lower-income countries. NTDs are an important public health problem that can be prevented with folic acid supplementation and fortification of staple foods.

  10. Neural neworks in a management information systems

    Directory of Open Access Journals (Sweden)

    Jana Weinlichová

    2009-01-01

    Full Text Available For having retrospection for all over the data which are used, analyzed, evaluated and for a future incident predictions are used Management Information Systems and Business Intelligence. In case of not to be able to apply standard methods of data processing there can be with benefit applied an Artificial Intelligence. In this article will be referred to proofed abilities of Neural Networks. The Neural Networks is supported by many software products related to provide effective solution of manager issues. Those products are given as primary support for manager issues solving. We were tried to find reciprocally between products using Neural Networks and between Management Information Systems for finding a real possibility of applying Neural Networks as a direct part of Management Information Systems (MIS. In the article are presented possibilities to apply Neural Networks on different types of tasks in MIS.

  11. HETEROGENEITY OF NEURAL-TUBE DEFECTS IN EUROPE - THE SIGNIFICANCE OF SITE OF DEFECT AND PRESENCE OF OTHER MAJOR ANOMALIES IN RELATION TO GEOGRAPHIC DIFFERENCES IN PREVALENCE

    NARCIS (Netherlands)

    DOLK, H; DEWALS, P; GILLEROT, Y; LECHAT, MF; AYME, S; CORNEL, M; CUSCHIERI, A; GARNE, E; GOUJARD, J; LAURENCE, KM; LILLIS, D; LYS, F; NEVIN, N; OWENS, J; RADIC, A; STOLL, C; STONE, D; TENKATE, L

    1991-01-01

    In the period 1980-1987, neural tube defects were two to three times more prevalent in populations covered by EUROCAT registries in the United Kingdom and Ireland (UKI) than in Continental Europe and Malta (CEM). 1864 NTD cases in a total population of 580,000 births in UKI and 455 cases in a

  12. Do neural tube defects lead to structural alterations in the human bladder?

    Science.gov (United States)

    Pazos, Helena M F; Lobo, Márcio Luiz de P; Costa, Waldemar S; Sampaio, Francisco J B; Cardoso, Luis Eduardo M; Favorito, Luciano Alves

    2011-05-01

    Anencephaly is the most severe neural tube defect in human fetuses. The objective of this paper is to analyze the structure of the bladder in anencephalic human fetuses. We studied 40 bladders of normal human fetuses (20 male and 20 female, aged 14 to 23 WPC) and 12 bladders of anencephalic fetuses (5 male and 7 female, aged 18 to 22 WPC). The bladders were removed and processed by routine histological techniques. Stereological analysis of collagen, elastic system fibers and smooth muscle was performed in sections. Data were expressed as volumetric density (Vv-%). The images were captured with Olympus BX51 microscopy and Olympus DP70 camera. The stereological analysis was done using the software Image Pro and Image J. For biochemical analysis, samples were fixed in acetone, and collagen concentrations were expressed as micrograms of hydroxyproline per mg of dry tissue. Means were statistically compared using the unpaired t-test (p<0.05). We observed a significant increase (p<0.0001) in the Vv of collagen in the bladders of anencephalic fetuses (69.71%) when compared to normal fetuses (52.74%), and a significant decrease (p<0.0001) in the Vv of smooth muscle cells in the bladders of anencephalic fetuses (23.96%) when compared to normal fetuses (38.35%). The biochemical analyses showed a higher concentration of total collagen in the bladders of anencephalic fetuses (37354 µg/mg) when compared to normal fetuses (48117 µg/mg, p<0.02). The structural alterations of the bladder found in this study may suggest the existence of functional alterations in the bladder of anencephalic human fetuses.

  13. Echoes in correlated neural systems

    International Nuclear Information System (INIS)

    Helias, M; Tetzlaff, T; Diesmann, M

    2013-01-01

    Correlations are employed in modern physics to explain microscopic and macroscopic phenomena, like the fractional quantum Hall effect and the Mott insulator state in high temperature superconductors and ultracold atoms. Simultaneously probed neurons in the intact brain reveal correlations between their activity, an important measure to study information processing in the brain that also influences the macroscopic signals of neural activity, like the electroencephalogram (EEG). Networks of spiking neurons differ from most physical systems: the interaction between elements is directed, time delayed, mediated by short pulses and each neuron receives events from thousands of neurons. Even the stationary state of the network cannot be described by equilibrium statistical mechanics. Here we develop a quantitative theory of pairwise correlations in finite-sized random networks of spiking neurons. We derive explicit analytic expressions for the population-averaged cross correlation functions. Our theory explains why the intuitive mean field description fails, how the echo of single action potentials causes an apparent lag of inhibition with respect to excitation and how the size of the network can be scaled while maintaining its dynamical state. Finally, we derive a new criterion for the emergence of collective oscillations from the spectrum of the time-evolution propagator. (paper)

  14. Neural systems for tactual memories.

    Science.gov (United States)

    Bonda, E; Petrides, M; Evans, A

    1996-04-01

    1. The aim of this study was to investigate the neural systems involved in the memory processing of experiences through touch. 2. Regional cerebral blood flow was measured with positron emission tomography by means of the water bolus H2(15)O methodology in human subjects as they performed tasks involving different levels of tactual memory. In one of the experimental tasks, the subjects had to palpate nonsense shapes to match each one to a previously learned set, thus requiring constant reference to long-term memory. The other experimental task involved judgements of the recent recurrence of shapes during the scanning period. A set of three control tasks was used to control for the type of exploratory movements and sensory processing inherent in the two experimental tasks. 3. Comparisons of the distribution of activity between the experimental and the control tasks were carried out by means of the subtraction method. In relation to the control conditions, the two experimental tasks requiring memory resulted in significant changes within the posteroventral insula and the central opercular region. In addition, the task requiring recall from long-term memory yielded changes in the perirhinal cortex. 4. The above findings demonstrated that a ventrally directed parietoinsular pathway, leading to the posteroventral insula and the perirhinal cortex, constitutes a system by which long-lasting representations of tactual experiences are formed. It is proposed that the posteroventral insula is involved in tactual feature analysis, by analogy with the similar role of the inferotemporal cortex in vision, whereas the perirhinal cortex is further involved in the integration of these features into long-lasting representations of somatosensory experiences.

  15. Melatonin prevents neural tube defects in the offspring of diabetic pregnancy.

    Science.gov (United States)

    Liu, Shangming; Guo, Yuji; Yuan, Qiuhuan; Pan, Yan; Wang, Liyan; Liu, Qian; Wang, Fuwu; Wang, Jingjing; Hao, Aijun

    2015-11-01

    Melatonin, an endogenous neurohormone secreted by the pineal gland, has a variety of physiological functions and neuroprotective effects. However, its protective role on the neural tube defects (NTDs) was not very clear. The aim of this study was to investigate the effects of melatonin on the incidence of NTDs (including anencephaly, encephalocele, and spina bifida) of offspring from diabetic pregnant mice as well as its underlying mechanisms. Pregnant mice were given 10 mg/kg melatonin by daily i.p. injection from embryonic day (E) 0.5 until being killed on E11.5. Here, we showed that melatonin decreased the NTDs (especially exencephaly) rate of embryos exposed to maternal diabetes. Melatonin stimulated proliferation of neural stem cells (NSCs) under hyperglycemic condition through the extracellular regulated protein kinases (ERK) pathway. Furthermore, as a direct free radical scavenger, melatonin decreased apoptosis of NSCs exposed to hyperglycemia. In the light of these findings, it suggests that melatonin supplementation may play an important role in the prevention of neural malformations in diabetic pregnancy. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  16. Mature teratoma in association with neural tube defect (occipital encephalocele): series of four cases and review of the literature.

    Science.gov (United States)

    Goyal, Nishant; Singh, Pankaj Kumar; Kakkar, Aanchal; Sharma, Meher Chand; Mahapatra, Ashok Kumar

    2012-01-01

    Both occipital encephalocele and teratomas are midline congenital malformations. Encephalocele is a form of neural tube defect in which there is a congenital defect of the cranium through which occurs a protrusion of brain matter or meninges, while teratoma is a tumor derived from all three germ layers. The association between occipital encephalocele and teratoma has not been reported to date. In the present study, the authors present a series of four such cases. Copyright © 2012 S. Karger AG, Basel.

  17. Management of Labor and Delivery After Fetoscopic Repair of an Open Neural Tube Defect.

    Science.gov (United States)

    Kohn, Jaden R; Rao, Vibha; Sellner, Allison A; Sharhan, Dina; Espinoza, Jimmy; Shamshirsaz, Alireza A; Whitehead, William E; Belfort, Michael A; Sanz Cortes, Magdalena

    2018-06-01

    To report labor, delivery, and neonatal outcomes in a cohort of women delivering neonates who had undergone fetoscopic neural tube defect repair. We conducted a retrospective cohort study from April 2014 to January 2018. All patients met Management of Myelomeningocele Study eligibility criteria. We included patients with completed second-trimester fetoscopic neural tube defect repair (laparotomy, uterine exteriorization, and minimally invasive access through two or three uterine ports) followed by standardized management of labor and delivery at our institution. Outcomes included rates of vaginal delivery, term delivery, and intrapartum cesarean delivery as well as obstetric and neonatal outcomes after oxytocin. Complications of interest included preterm prelabor rupture of membranes, chorioamnionitis, uterine dehiscence or rupture, 5-minute Apgar score less than 7, and neonatal acidosis (umbilical artery pH less than 7.15). Thirty-four patients had fetoscopic repair, followed by 17 vaginal deliveries (50%, 95% CI 32-68%). Median gestational age was 38 1/7 weeks at vaginal delivery (range 26 0/7-40 2/7 weeks of gestation) and 37 1/7 weeks of gestation at cesarean delivery (range 25 5/7-40 5/7 weeks of gestation); 62% of deliveries occurred at term. Eight patients had prelabor cesarean delivery: three nonurgent and five urgent (for nonreassuring fetal heart tracings). Twenty-six patients labored; six were induced and 20 labored spontaneously. Of the latter, five were augmented. Of 26 laboring patients, 17 delivered vaginally and nine underwent urgent cesarean delivery (35%, 95% CI 17-56%; seven nonreassuring fetal heart tracings and two breech). There were no cases of uterine rupture or dehiscence. Most (94%, 95% CI 80-99%) had normal 5-minute Apgar scores; one neonate (3%, 95% CI 0-15%) had acidosis but normal Apgar scores. Our data regarding trial of labor, use of low-dose oxytocin, and vaginal delivery after prenatal fetoscopic neural tube defect repair are

  18. Substitution and defect chemistry of La-Cu-O systems

    International Nuclear Information System (INIS)

    Gai, P.L.; McCarron, E.M.; Kunchur, M.

    1991-01-01

    In this paper substitutional effects of strontium in La-Cu-O system and defects accommodating stoichiometric deviations is investigated. The extended shear defects are analyzed using electron microscopy and the role in superconducting transport properties has been examined by magnetic measurements. The initial results suggest that the defects enhance flux pinning

  19. Neural neworks in a management information systems

    OpenAIRE

    Jana Weinlichová; Michael Štencl

    2009-01-01

    For having retrospection for all over the data which are used, analyzed, evaluated and for a future incident predictions are used Management Information Systems and Business Intelligence. In case of not to be able to apply standard methods of data processing there can be with benefit applied an Artificial Intelligence. In this article will be referred to proofed abilities of Neural Networks. The Neural Networks is supported by many software products related to provide effective solution of ma...

  20. Syndromes, disorders and maternal risk factors associated with neural tube defects (I).

    Science.gov (United States)

    Chen, Chih-Ping

    2008-03-01

    Fetuses with neural tube defects (NTDs) may be associated with syndromes, disorders, and maternal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal risk factors associated with NTDs, such as acrocallosal syndrome, autosomal dominant brachydactyly-clinodactyly syndrome, Manouvrier syndrome, short rib-polydactyly syndrome, Disorganization ( Ds )-like human malformations, isolated hemihyperplasia, X-linked NTDs, meroanencephaly, schisis association, diprosopus, fetal valproate syndrome, DiGeorge syndrome/velocardiofacial syndrome, Waardenburg syndrome, folic acid antagonists, diabetes mellitus, and obesity. NTDs associated with syndromes, disorders, and maternal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders, and maternal risk factors may be different from those of non-syndromic multifactorial NTDs. Perinatal identification of NTDs should alert one to the syndromes, disorders, and maternal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling.

  1. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (IV

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-06-01

    Full Text Available Fetuses with neural tube defects (NTDs may be associated with maternal and fetal risk factors. This article provides a comprehensive review of maternal and fetal risk factors associated with NTDs, such as infertility, periconceptional clomiphene use and assisted reproductive technology, periconceptional folic acid deficiency and effects offolic acid supplementation and fortification on NTD rates, periconceptional vitamin B1 2 deficiency, single nucleotide polymorphisms and polymorphisms in genes of folate metabolism, and maternal autoantibodies to folate receptors. NTDs associated with maternal and fetal risk factors are an important cause of NTDs. Perinatal identification of NTDs should alert the clinician to the maternal and fetal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling. [Taiwan J Obstet Cynecol 2008;47(2:141-1 50

  2. Syndromes, Disorders and Maternal Risk Factors Associated With Neural Tube Defects (VI

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-09-01

    Full Text Available Neural tube defects (NTDs may be associated with syndromes, disorders, and maternal and fetal risk factors. This article provides a comprehensive review of the syndromes, disorders, and maternal and fetal risk factors associated with NTDs, including maternal fumonisin consumption, periconceptional zinc deficiency, parental occupational exposure and residential proximity to pesticides, lower socioeconomic status, fetal alcohol syndrome, mutations in the VANGL1 gene, human athymic Nude/SCID fetus, and single nucleotide polymorphism in the NOS3 gene. NTDs associated with these syndromes, disorders, and maternal and fetal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders and maternal risk factors may be different from those of nonsyndromic multifactorial NTDs. Perinatal diagnosis of NTDs should alert doctors to the syndromes, disorders, and maternal and fetal risk factors associated with NTDs, and prompt thorough etiologic investigation and genetic counseling.

  3. Long term trends in prevalence of neural tube defects in Europe

    DEFF Research Database (Denmark)

    Khoshnood, Babak; Loane, Maria; Walle, Hermien de

    2015-01-01

    STUDY QUESTION: What are the long term trends in the total (live births, fetal deaths, and terminations of pregnancy for fetal anomaly) and live birth prevalence of neural tube defects (NTD) in Europe, where many countries have issued recommendations for folic acid supplementation but a policy...... for mandatory folic acid fortification of food does not exist? METHODS: This was a population based, observational study using data on 11 353 cases of NTD not associated with chromosomal anomalies, including 4162 cases of anencephaly and 5776 cases of spina bifida from 28 EUROCAT (European Surveillance......-conceptional folic acid supplementation and existence of voluntary folic acid fortification. FUNDING, COMPETING INTERESTS, DATA SHARING: The study was funded by the European Public Health Commission, EUROCAT Joint Action 2011-2013. HD and ML received support from the European Commission DG Sanco during the conduct...

  4. Neural control of magnetic suspension systems

    Science.gov (United States)

    Gray, W. Steven

    1993-01-01

    The purpose of this research program is to design, build and test (in cooperation with NASA personnel from the NASA Langley Research Center) neural controllers for two different small air-gap magnetic suspension systems. The general objective of the program is to study neural network architectures for the purpose of control in an experimental setting and to demonstrate the feasibility of the concept. The specific objectives of the research program are: (1) to demonstrate through simulation and experimentation the feasibility of using neural controllers to stabilize a nonlinear magnetic suspension system; (2) to investigate through simulation and experimentation the performance of neural controllers designs under various types of parametric and nonparametric uncertainty; (3) to investigate through simulation and experimentation various types of neural architectures for real-time control with respect to performance and complexity; and (4) to benchmark in an experimental setting the performance of neural controllers against other types of existing linear and nonlinear compensator designs. To date, the first one-dimensional, small air-gap magnetic suspension system has been built, tested and delivered to the NASA Langley Research Center. The device is currently being stabilized with a digital linear phase-lead controller. The neural controller hardware is under construction. Two different neural network paradigms are under consideration, one based on hidden layer feedforward networks trained via back propagation and one based on using Gaussian radial basis functions trained by analytical methods related to stability conditions. Some advanced nonlinear control algorithms using feedback linearization and sliding mode control are in simulation studies.

  5. Inositol for the prevention of neural tube defects: a pilot randomised controlled trial.

    Science.gov (United States)

    Greene, Nicholas D E; Leung, Kit-Yi; Gay, Victoria; Burren, Katie; Mills, Kevin; Chitty, Lyn S; Copp, Andrew J

    2016-03-28

    Although peri-conceptional folic acid (FA) supplementation can prevent a proportion of neural tube defects (NTD), there is increasing evidence that many NTD are FA non-responsive. The vitamin-like molecule inositol may offer a novel approach to preventing FA-non-responsive NTD. Inositol prevented NTD in a genetic mouse model, and was well tolerated by women in a small study of NTD recurrence. In the present study, we report the Prevention of Neural Tube Defects by Inositol (PONTI) pilot study designed to gain further experience of inositol usage in human pregnancy as a preliminary trial to a future large-scale controlled trial to evaluate efficacy of inositol in NTD prevention. Study subjects were UK women with a previous NTD pregnancy who planned to become pregnant again. Of 117 women who made contact, ninety-nine proved eligible and forty-seven agreed to be randomised (double-blind) to peri-conceptional supplementation with inositol plus FA or placebo plus FA. In total, thirty-three randomised pregnancies produced one NTD recurrence in the placebo plus FA group (n 19) and no recurrences in the inositol plus FA group (n 14). Of fifty-two women who declined randomisation, the peri-conceptional supplementation regimen and outcomes of twenty-two further pregnancies were documented. Two NTD recurred, both in women who took only FA in their next pregnancy. No adverse pregnancy events were associated with inositol supplementation. The findings of the PONTI pilot study encourage a large-scale controlled trial of inositol for NTD prevention, but indicate the need for a careful study design in view of the unwillingness of many high-risk women to be randomised.

  6. Prenatal screening, diagnosis, and pregnancy management of fetal neural tube defects.

    Science.gov (United States)

    Wilson, R Douglas

    2014-10-01

    To provide obstetrical and genetic health care practitioners with guidelines and recommendations for prenatal screening, diagnosis, and obstetrical management of fetal open and closed neural tube defects (OCNTD). This review includes prenatal screening and diagnostic techniques currently being used for the detection of OCNTD including maternal serum alpha fetoprotein screening, ultrasound, fetal magnetic resonance imaging, and amniocentesis. To improve prenatal screening, diagnosis, and obstetrical management of OCNTD while taking into consideration patient care, efficacy, cost, and care procedures. Published literature was retrieved through searches of PubMed or MEDLINE, CINAHL, and The Cochrane Library in November, 2013, using appropriate controlled vocabulary and key words (e.g., prenatal screening, congenital anomalies, neural tube defects, alpha fetoprotein, ultrasound scan, magnetic resonance imaging). Results were restricted to systematic reviews, randomized control trials/controlled clinical trials, and observational studies published in English from 1977 to 2012. Searches were updated on a regular basis and incorporated in the guideline to November 30, 2013. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology-related agencies, clinical practice guideline collections, clinical trial registries, and national and international medical specialty societies. An online survey of health care practitioners was also reviewed. The quality of evidence in this document was rated using the criteria described in the Report of the Canadian Task Force on Preventive Health Care (Table). This review will provide health care practitioners with a better understanding of the available prenatal screening methods for OCNTD and the benefits and risks associated with each technique to allow evidenced-based decisions on OCNTD screening, diagnosis, and obstetrical management.

  7. Defect and Innovation of Water Rights System

    Institute of Scientific and Technical Information of China (English)

    Zhou Bin

    2008-01-01

    The rare deposition of water resources conflicts with its limitless demand. This determined the existence of the water rights transaction system. The implementation of the water rights transaction system requires clarifying the definition of water re-source fight above all distinctly. At present, it is a kind of common right system arrangement which needs the Chinese government to dispose of water resources. Though a series of management sys-tems guaranteed the government's supply of water resource, it hindered the development of the water market seriously and caused the utilization of water resources to stay in the inefficient or low efficient state for a long time. Thus, we should change the government's leading role in the resource distribution and really rely on the market to carry on the water rights trade and transac-tion. In this way, the water rights could become a kind of private property right relatively, and circulate freely in the market. As a result of this, we should overcome the defects of common right, make its external performance internalized maximally and achieve the optimized water resource disposition and use it more effec-tively.

  8. Pullout Performances of Grouted Rockbolt Systems with Bond Defects

    Science.gov (United States)

    Xu, Chang; Li, Zihan; Wang, Shanyong; Wang, Shuren; Fu, Lei; Tang, Chunan

    2018-03-01

    This paper presents a numerical study on the pullout behaviour of fully grouted rockbolts with bond defects. The cohesive zone model (CZM) is adopted to model the bond-slip behaviour between the rockbolt and grout material. Tensile tests were also conducted to validate the numerical model. The results indicate that the defect length can obviously influence the load and stress distributions along the rockbolt as well as the load-displacement response of the grouted system. Moreover, a plateau in the stress distribution forms due to the bond defect. The linear limit and peak load of the load-displacement response decrease as the defect length increases. A bond defect located closer to the loaded end leads to a longer nonlinear stage in the load-displacement response. However, the peak loads measured from the specimens made with various defect locations are almost approximately the same. The peak load for a specimen with the defects equally spaced along the bolt is higher than that for a specimen with defects concentrated in a certain zone, even with the same total defect length. Therefore, the dispersed pattern of bond defects would be much safer than the concentrated pattern. For the specimen with dispersed defects, the peak load increases with an increase in the defect spacing, even if the total defect length is the same. The peak load for a grouted rockbolt system with defects increases with an increases in the bolt diameter. This work leads to a better understanding of the load transfer mechanism for grouted rockbolt systems with bond defects, and paves the way towards developing a general evaluation method for damaged rockbolt grouted systems.

  9. Application of neural networks in CRM systems

    Directory of Open Access Journals (Sweden)

    Bojanowska Agnieszka

    2017-01-01

    Full Text Available The central aim of this study is to investigate how to apply artificial neural networks in Customer Relationship Management (CRM. The paper presents several business applications of neural networks in software systems designed to aid CRM, e.g. in deciding on the profitability of building a relationship with a given customer. Furthermore, a framework for a neural-network based CRM software tool is developed. Building beneficial relationships with customers is generating considerable interest among various businesses, and is often mentioned as one of the crucial objectives of enterprises, next to their key aim: to bring satisfactory profit. There is a growing tendency among businesses to invest in CRM systems, which together with an organisational culture of a company aid managing customer relationships. It is the sheer amount of gathered data as well as the need for constant updating and analysis of this breadth of information that may imply the suitability of neural networks for the application in question. Neural networks exhibit considerably higher computational capabilities than sequential calculations because the solution to a problem is obtained without the need for developing a special algorithm. In the majority of presented CRM applications neural networks constitute and are presented as a managerial decision-taking optimisation tool.

  10. Maternal Antenatal Bereavement and Neural Tube Defect in Live-Born Offspring: A Cohort Study.

    Directory of Open Access Journals (Sweden)

    Katja Glejsted Ingstrup

    Full Text Available Maternal emotional stress during pregnancy has previously been associated with congenital neural malformations, but most studies are based on data collected retrospectively. The objective of our study was to investigate associations between antenatal maternal bereavement due to death of a close relative and neural tube defects (NTDs in the offspring.We performed a register-based cohort study including all live-born children (N = 1,734,190 from 1978-2008. Exposure was bereavement due to loss of a close relative from one year before conception to the end of the first trimester of pregnancy. The outcome was NTDs in the offspring according to the International Classification of Disease. We used multivariate logistic regression to estimate prevalence odds ratios (ORs.A total of 2% children were born to mothers who lost a close relative prenatally. During 30 years of follow-up, 1,115 children were diagnosed with any NTDs: spina bifida (n = 889, anencephaly (n = 85 and encephalocele (n = 164. And 23 children were diagnosed with two types of NTDs. Overall, when comparing bereaved mothers to non-bereaved mothers, no significant increased prevalence of NTDs in the offspring was seen (OR = 0.84; 95% confidence interval: 0.52-1.33.Overall maternal bereavement in the antenatal period was not related to NTDs in liveborn offspring.

  11. A regulating element essential for PDGFRA transcription is recognized by neural tube defect-associated PRX homeobox transcription factors

    NARCIS (Netherlands)

    Joosten, Paul H. L. J.; Toepoel, Mascha; van Oosterhout, Dirk; Afink, Gijs B.; van Zoelen, Everardus J. J.

    2002-01-01

    We have previously shown that deregulated expression of the platelet-derived growth factor alpha-receptor (PDGFRA) can be associated with neural tube defects (NTDs) in both men and mice. In the present study, we have investigated the transcription factors that control the up-regulation of PDGFRA

  12. Prevalentie, klinisch beeld en prognose van neuralebuisdefecten in Nederland [Prevalence, presentation and prognosis of neural tube defects in the Netherlands

    NARCIS (Netherlands)

    Ouden, A.L. den; Hirasing, R.A.; Buitendijk, S.E.; Jong-van de Berg, L.T.W. de; Walle, H.E.K. de; Cornel, M.C.

    1996-01-01

    Objective. To determine the live birth prevalence of neural tube defects (NTD) in the Netherlands and describe the clinical picture. Design. Descriptive. Setting. TNO Prevention and Health, Leiden, the Netherlands. Method. Data collected through active surveillance of NTD on a monthly basis by

  13. Epigenetic profiles in children with a neural tube defect; a case-control study in two populations

    NARCIS (Netherlands)

    L. Stolk (Lisette); M.I. Both (Marieke); N.H. van Mill (Nina); M.M.P.J. Verbiest (Michael); P.H.C. Eilers (Paul); H. Zhu (Huiping); L. Suarez (Lucina); A.G. Uitterlinden (André); R.P.M. Steegers-Theunissen (Régine)

    2013-01-01

    textabstractFolate deficiency is implicated in the causation of neural tube defects (NTDs). The preventive effect of periconceptional folic acid supplement use is partially explained by the treatment of a deranged folate-dependent one carbon metabolism, which provides methyl groups for

  14. Quantitative trait loci affecting phenotypic variation in the vacuolated lens mouse mutant, a multigenic mouse model of neural tube defects

    NARCIS (Netherlands)

    Korstanje, Ron; Desai, Jigar; Lazar, Gloria; King, Benjamin; Rollins, Jarod; Spurr, Melissa; Joseph, Jamie; Kadambi, Sindhuja; Li, Yang; Cherry, Allison; Matteson, Paul G.; Paigen, Beverly; Millonig, James H.

    Korstanje R, Desai J, Lazar G, King B, Rollins J, Spurr M, Joseph J, Kadambi S, Li Y, Cherry A, Matteson PG, Paigen B, Millonig JH. Quantitative trait loci affecting phenotypic variation in the vacuolated lens mouse mutant, a multigenic mouse model of neural tube defects. Physiol Genomics 35:

  15. Neural tube defects – disorders of neurulation and related embryonic processes

    Science.gov (United States)

    Copp, Andrew J.; Greene, Nicholas D. E.

    2014-01-01

    Neural tube defects (NTDs) are severe congenital malformations affecting 1 in every 1000 pregnancies. ‘Open’ NTDs result from failure of primary neurulation as seen in anencephaly, myelomeningocele (open spina bifida) and craniorachischisis. Degeneration of the persistently open neural tube in utero leads to loss of neurological function below the lesion level. ‘Closed’ NTDs are skin-covered disorders of spinal cord structure, ranging from asymptomatic spina bifida occulta to severe spinal cord tethering, and usually traceable to disruption of secondary neurulation. ‘Herniation’ NTDs are those in which meninges, with or without brain or spinal cord tissue, become exteriorised through a pathological opening in the skull or vertebral column (e.g. encephalocele and meningocele). NTDs have multifactorial etiology, with genes and environmental factors interacting to determine individual risk of malformation. While over 200 mutant genes cause open NTDs in mice, much less is known about the genetic causation of human NTDs. Recent evidence has implicated genes of the planar cell polarity signalling pathway in a proportion of cases. The embryonic development of NTDs is complex, with diverse cellular and molecular mechanisms operating at different levels of the body axis. Molecular regulatory events include the BMP and Sonic hedgehog pathways which have been implicated in control of neural plate bending. Primary prevention of NTDs has been implemented clinically following the demonstration that folic acid, when taken as a peri-conceptional supplement, can prevent many cases. Not all NTDs respond to folic acid, however, and adjunct therapies are required for prevention of this folic acid-resistant category. PMID:24009034

  16. Drinking water treatment is not associated with an observed increase in neural tube defects in mice

    Science.gov (United States)

    Melin, Vanessa E.; Johnstone, David W.; Etzkorn, Felicia A.

    2018-01-01

    Disinfection by-products (DBPs) arise when natural organic matter in source water reacts with disinfectants used in the water treatment process. Studies have suggested an association between DBPs and birth defects. Neural tube defects (NTDs) in embryos of untreated control mice were first observed in-house in May 2006 and have continued to date. The source of the NTD-inducing agent was previously determined to be a component of drinking water. Tap water samples from a variety of sources were analyzed for trihalomethanes (THMs) to determine if they were causing the malformations. NTDs were observed in CD-1 mice provided with treated and untreated surface water. Occurrence of NTDs varied by water source and treatment regimens. THMs were detected in tap water derived from surface water but not detected in tap water derived from a groundwater source. THMs were absent in untreated river water and laboratory purified waters, yet the percentage of NTDs in untreated river water were similar to the treated water counterpart. These findings indicate that THMs were not the primary cause of NTDs in the mice since the occurrence of NTDs was unrelated to drinking water disinfection. PMID:24497082

  17. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (III

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-06-01

    Full Text Available Fetuses with neural tube defects (NTDs may be associated with syndromes, disorders, and maternal and fetal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal and fetal risk factors associated with NTDs, such as omphalocele, OEIS (omphalocele-exstrophy-imperforate anus-spinal defects complex, pentalogy of Cantrell, amniotic band sequence, limb-body wall complex, Meckel syndrome, Joubert syndrome, skeletal dysplasia, diabetic embryopathy, and single nucleotide polymorphisms in genes of glucose metabolism. NTDs associated with syndromes, disorders, and maternal and fetal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders and maternal risk factors may be different from those of nonsyndromic multi facto rial NTDs. Perinatal identification of NTDs should alert the clinician to the syndromes, disorders, and maternal and fetal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling. [Taiwan J Obstet Cynecol 2008;47(2:131-140

  18. Risk factors of neural tube defects: A reality of Batna region in Algeria

    Directory of Open Access Journals (Sweden)

    Romyla Bourouba

    2018-07-01

    Full Text Available Background: Neural tube defects (NTDs are severe birth defects, with genetic and/or environmental risk factors. Aim: The objective of this study was to analyze data on NTDs cases at the Batna Maternity Hospital and to investigate some environmental and two genetic risk factors suspected in the etiology of NTDs. Subjects and methods: This study was conducted on 82 healthy participants and 48 mothers with an NTD child. Peripheral blood samples were collected, in EDTA tubes and frozen at −20 °C until DNA extraction by conventional method. Genetic analysis of methylene tetrahydrofolate reductase C677T polymorphism was determined by real time PCR, while cystathionine-beta-synthase 844 insertion was investigated by traditional PCR. Chi-square analyses were used to evaluate differences in the distribution of data. The odds-ratio was also calculated. A P-value less than 0.05 were significant. Results: The incidence of NTD in Batna region was 1.58 per 1000 births. The rate of NTD was significantly higher in females than males, highest affected NTD newborn’s was observed in mothers aged between 25 and 29 years and the consanguinity among all NTD cases was 30%. Data showed no significant association of NTDs with personal education, obesity, diabetes, but regarding folic acid consumption, about 86% of NTD’s mothers in our region didn’t take pre-conceptional supplementation with this vitamin .Genetic factors results didn't show a significant association of NTDs with specific mutations of the variant C677T MTHFR, and no gene-gene interaction of CBS insertion and C677T polymorphism was found, despite a significant difference in heterozygote frequency of CBS 844ins68 genotype between NTD’s mothers and controls, OR: 2.85(1.18–6.88. Conclusion: NTD represents a real public health problem in Batna, Algeria. Various genetic and/or nutritional factors are implicated, although the mechanism is not clear. We suggest that further research should continue

  19. Spiking neural P systems with multiple channels.

    Science.gov (United States)

    Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

    2017-11-01

    Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Evaluating neural networks and artificial intelligence systems

    Science.gov (United States)

    Alberts, David S.

    1994-02-01

    Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.

  1. Integrated Neural Flight and Propulsion Control System

    Science.gov (United States)

    Kaneshige, John; Gundy-Burlet, Karen; Norvig, Peter (Technical Monitor)

    2001-01-01

    This paper describes an integrated neural flight and propulsion control system. which uses a neural network based approach for applying alternate sources of control power in the presence of damage or failures. Under normal operating conditions, the system utilizes conventional flight control surfaces. Neural networks are used to provide consistent handling qualities across flight conditions and for different aircraft configurations. Under damage or failure conditions, the system may utilize unconventional flight control surface allocations, along with integrated propulsion control, when additional control power is necessary for achieving desired flight control performance. In this case, neural networks are used to adapt to changes in aircraft dynamics and control allocation schemes. Of significant importance here is the fact that this system can operate without emergency or backup flight control mode operations. An additional advantage is that this system can utilize, but does not require, fault detection and isolation information or explicit parameter identification. Piloted simulation studies were performed on a commercial transport aircraft simulator. Subjects included both NASA test pilots and commercial airline crews. Results demonstrate the potential for improving handing qualities and significantly increasing survivability rates under various simulated failure conditions.

  2. Are concentrations of alkaline earth elements in maternal hair associated with risk of neural tube defects?

    Science.gov (United States)

    Li, Zhenjiang; Wang, Bin; Huo, Wenhua; Liu, Yingying; Zhu, Yibing; Xie, Jing; Li, Zhiwen; Ren, Aiguo

    2017-12-31

    The relationship between maternal intake of alkaline earth elements (AEEs) during the period of neural tube closure and the risk of neural tube defects (NTDs) is still unclear. We propose that AEE deficiency during the early period of pregnancy is associated with an elevated risk of NTDs in the offspring. In this study, we recruited 191 women with NTD-affected pregnancies (cases) and 261 women who delivered healthy infants (controls). The concentrations of four AEEs (Ca, Mg, Sr, Ba) in maternal hair sections that grew during early pregnancy were analyzed. Information on the dietary habits of the mothers was also collected by questionnaire. Higher concentrations of the four AEEs in hair had protective effects against the risk of total NTDs, with odds ratios with 95% confidence interval (comparing groups separated by each median level) of 0.44 (0.28-0.68) for Mg, 0.56 (0.36-0.87) for Ca, 0.45 (0.28-0.70) for Sr, and 0.41 (0.26-0.65) for Ba. Significant negative dose-response trends were identified for the relationships between the four AEE concentrations in maternal hair and the risks of anencephaly and spina bifida, but not for encephalocele. The frequencies of maternal consumption of fresh green vegetables, fresh fruit, and meat or fish were positively correlated with the concentrations of AEEs in hair. We concluded that the maternal intake of AEEs may play an important role in preventing NTD formation in offspring, and that this intake is related to maternal dietary habits of consuming fresh green vegetables, fresh fruit, and fish or meat. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Spontaneous neural tube defects in splotch mice supplemented with selected micronutrients

    International Nuclear Information System (INIS)

    Wlodarczyk, Bogdan J.; Tang, Louisa S.; Triplett, Aleata; Aleman, Frank; Finnell, Richard H.

    2006-01-01

    Splotch (Sp/Sp) mice homozygous for a mutation in the Pax3 gene inevitably present with neural tube defects (NTDs), along with other associated congenital anomalies. The affected mutant embryos usually die by gestation days (E) 12-13. In the present study, the effect of modifier genes from a new genetic background (CXL-Sp) and periconceptional supplementation with selected micronutrients (folic acid, 5-formyltetrahydrofolate, 5-methyltetrahydrofolate, methionine, myoinositol, thiamine, thymidine, and α-tocopherol) was determined with respect to the incidence of NTDs. In order to explore how different exposure parameters (time, dose, and route of compound administration) modulate the beneficial effects of micronutrient supplementation, female mice received either short- or long-term nutrient supplements via enteral or parenteral routes. Embryos were collected on E12.5 and examined for the presence of anterior or posterior NTDs. Additionally, whole mount in situ hybridization studies were conducted in order to reveal/confirm normal expression patterns of the Pax3 gene during neurulation in the wild-type and Sp/Sp homozygous mutant mouse embryos utilized in this study. A strong Pax3 signal was demonstrated in CXL-Sp embryos during neural tube closure (E9.5 to E10.5). The intensity and spatial pattern of expression were similar to other Splotch mutant mice. Of all the micronutrients tested, only supplementation with folic acid or 5-methyltetrahydrofolate rescued the normal phenotype in Sp/Sp embryos. When the folate supplementation dose was increased to 200 mg/kg in the diet, the incidence of rescued splotch homozygotes reached 30%; however, this was accompanied by six-fold increased resorption rate

  4. Is 5-methyltetrahydrofolate an alternative to folic acid for the prevention of neural tube defects?

    Science.gov (United States)

    Obeid, Rima; Holzgreve, Wolfgang; Pietrzik, Klaus

    2013-09-01

    Women have higher requirements for folate during pregnancy. An optimal folate status must be achieved before conception and in the first trimester when the neural tube closes. Low maternal folate status is causally related to neural tube defects (NTDs). Many NTDs can be prevented by increasing maternal folate intake in the preconceptional period. Dietary folate is protective, but recommending increasing folate intake is ineffective on a population level particularly during periods of high demands. This is because the recommendations are often not followed or because the bioavailability of food folate is variable. Supplemental folate [folic acid (FA) or 5-methyltetrahydrofolate (5-methylTHF)] can effectively increase folate concentrations to the level that is considered to be protective. FA is a synthetic compound that has no biological functions unless it is reduced to dihydrofolate and tetrahydrofolate. Unmetabolized FA appears in the circulation at doses of >200 μg. Individuals show wide variations in their ability to reduce FA. Carriers of certain polymorphisms in genes related to folate metabolism or absorption can better benefit from 5-methylTHF instead of FA. 5-MethylTHF [also known as (6S)-5-methylTHF] is the predominant natural form that is readily available for transport and metabolism. In contrast to FA, 5-methylTHF has no tolerable upper intake level and does not mask vitamin B12 deficiency. Supplementation of the natural form, 5-methylTHF, is a better alternative to supplementation of FA, especially in countries not applying a fortification program. Supplemental 5-methylTHF can effectively improve folate biomarkers in young women in early pregnancy in order to prevent NTDs.

  5. Arsenate-induced maternal glucose intolerance and neural tube defects in a mouse model

    International Nuclear Information System (INIS)

    Hill, Denise S.; Wlodarczyk, Bogdan J.; Mitchell, Laura E.; Finnell, Richard H.

    2009-01-01

    Background: Epidemiological studies have linked environmental arsenic (As) exposure to increased type 2 diabetes risk. Periconceptional hyperglycemia is a significant risk factor for neural tube defects (NTDs), the second most common structural birth defect. A suspected teratogen, arsenic (As) induces NTDs in laboratory animals. Objectives: We investigated whether maternal glucose homeostasis disruption was responsible for arsenate-induced NTDs in a well-established dosing regimen used in studies of arsenic's teratogenicity in early neurodevelopment. Methods: We evaluated maternal intraperitoneal (IP) exposure to As 9.6 mg/kg (as sodium arsenate) in LM/Bc/Fnn mice for teratogenicity and disruption of maternal plasma glucose and insulin levels. Selected compounds (insulin pellet, sodium selenate (SS), N-acetyl cysteine (NAC), L-methionine (L-Met), N-tert-Butyl-α-phenylnitrone (PBN)) were investigated for their potential to mitigate arsenate's effects. Results: Arsenate caused significant glucose elevation during an IP glucose tolerance test (IPGTT). Insulin levels were not different between arsenate and control dams before (arsenate, 0.55 ng/dl; control, 0.48 ng/dl) or after glucose challenge (arsenate, 1.09 ng/dl; control, 0.81 ng/dl). HOMA-IR index was higher for arsenate (3.9) vs control (2.5) dams (p = 0.0260). Arsenate caused NTDs (100%, p < 0.0001). Insulin pellet and NAC were the most successful rescue agents, reducing NTD rates to 45% and 35%. Conclusions: IPGTT, insulin assay, and HOMA-IR results suggest a modest failure of glucose stimulated insulin secretion and insulin resistance characteristic of glucose intolerance. Insulin's success in preventing arsenate-induced NTDs provides evidence that these arsenate-induced NTDs are secondary to elevated maternal glucose. The NAC rescue, which did not restore maternal glucose or insulin levels, suggests oxidative disruption plays a role.

  6. Reduced folate carrier polymorphism (80A-->G) and neural tube defects.

    Science.gov (United States)

    De Marco, Patrizia; Calevo, Maria Grazia; Moroni, Anna; Merello, Elisa; Raso, Alessandro; Finnell, Richard H; Zhu, Huiping; Andreussi, Luciano; Cama, Armando; Capra, Valeria

    2003-03-01

    Transport of folates in mammalian cells occurs by a carrier-mediated mechanism. The human folate carrier (RFC-1) gene has been isolated and characterized. Within this gene, a common polymorphism, 80A-->G, changing a histidine to an arginine in exon 2 (H27R), was recently identified. Defects in folate metabolism, such as defective carrier molecules, could be implicated in the etiology of neural tube defects (NTDs). In the present case-control study, we recruited 174 Italian probands with nonsyndromic NTD, 43 mothers, 53 fathers and 156 control individuals and evaluated the impact of RFC-1 variant on NTD risk. A statistically significant risk was calculated for the 80GG genotype of the NTD cases (OR=2.35; 95% CI 1.21-4.58) and mothers (OR=2.74; 95% CI 0.92-8.38). On the contrary, the heterozygous genotype of the mothers and both heterozygous and homozygous genotypes of the fathers did not seem to be significant NTD risk factors. Furthemore, according to the multifactorial inheritance of NTDs, we demonstrated that the combined genotypes for MTHFR 1298A-->C and RFC-1 80A-->G polymorphisms of cases resulted in greater NTD risk than heterozygosity or homozygosity for RFC-1 80A-->G variant alone. Conversely, our data provide no evidence for an association between NTD phenotype and combined MTHFR C677T/RFC-1 A80G genotypes. Moreover, here we describe the combinations of the two MTHFR polymorphic sites (677CT and 1298AC) with RFC-1 genotypes. We found that both patients and controls could have at most quadruple-mutation combinations. Interestingly, 27% (7/26) of the mothers and 18.75% (30/160) of the cases genotyped presented four mutant alleles in comparison with 8.5% (11/129) of the controls. Finally, the frequency of NTD cases and mothers carrying combined heterozygosity for the two MTHFR polymorphisms and RFC-1 80GG homozygosity (677CT/1298AC/80GG) (cases=11.3%; mothers 11.5%) was increased compared with controls (1.6%). Altogether, our findings support the hypothesis

  7. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (I

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-03-01

    Full Text Available Fetuses with neural tube defects (NTDs maybe associated with syndromes, disorders, and maternal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal risk factors associated with NTDs, such as acrocallosal syndrome, autosomal dominant brachydactyly-clinodactyly syndrome, Manouvrier syndrome, short rib-polydactyly syndrome, Disorganization (Ds-like human malformations, isolated hemihyper-plasia, X-linked NTDs, meroanencephaly, schisis association, diprosopus, fetal valproate syndrome, DiGeorge syndrome/velocardiofacial syndrome, Waardenburg syndrome, folic acid antagonists, diabetes mellitus, and obesity. NTDs associated with syndromes, disorders, and maternal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders, and maternal risk factors may be different from those of non-syndromic multifactorial NTDs. Perinatal identification of NTDs should alert one to the syndromes, disorders, and maternal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling.

  8. Folate status in women of reproductive age as basis of neural tube defect risk assessment.

    Science.gov (United States)

    Bailey, Lynn B; Hausman, Dorothy B

    2018-02-01

    Reliable folate status data for women of reproductive age (WRA) to assess global risk for neural tube defects (NTDs) are needed. We focus on a recent recommendation by the World Health Organization that a specific "optimal" red blood cell (RBC) folate concentration be used as the sole indicator of NTD risk within a population and discuss how to best apply this guidance to reach the goal of assessing NTD risk globally. We also emphasize the importance of using the microbiologic assay (MBA) as the most reliable assay for obtaining comparable results for RBC folate concentration across time and countries, the need for harmonization of the MBA through use of consistent key reagents and procedures within laboratories, and the requirement to apply assay-matched cutoffs for folate deficiency and insufficiency. To estimate NTD risk globally, the ideal scenario would be to have country-specific population-based surveys of RBC folate in WRA determined utilizing a harmonized MBA, as was done in recent studies in Guatemala and Belize. We conclude with guidance on next steps to best navigate the road map toward the goal of generating reliable folate status data on which to assess NTD risk in WRA in low- and middle-income countries. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

  9. Folic acid supplement use in the prevention of neural tube defects.

    LENUS (Irish Health Repository)

    Delany, C

    2011-01-01

    In 2008, planned folic acid fortification for the prevention of Neural Tube Defects (NTD) was postponed. Concurrently, the economic recession may have affected dietary folic acid intake, placing increased emphasis on supplement use. This study examined folic acid supplement use in 2009. A cross-sectional survey of 300 ante-natal women was undertaken to assess folic acid knowledge and use. Associations between demographic, obstetric variables and folic acid knowledge and use were examined. A majority, 284\\/297 (96%), had heard of folic acid, and 178\\/297 (60%) knew that it could prevent NTD. Most, 270\\/297 (91%) had taken it during their pregnancy, but only 107\\/297 (36%) had used it periconceptionally. Being older, married, planned pregnancy and better socioeconomic status were associated with periconceptional use. Periconceptional folic acid use in 2009 was very low, little changed from economic status were associated with periconceptional use. Periconceptional folic acid use in 2009 was very low, little changed from earlier years. Continuous promotion efforts are necessary. Close monitoring of folic acid intake and NTD rates is essential, particularly in the absence of fortification.

  10. Risk factors for neural tube defects in Riyadh City, Saudi Arabia: Case-control study.

    Science.gov (United States)

    Salih, Mustafa A M; Murshid, Waleed R; Mohamed, Ashry Gad; Ignacio, Lena C; de Jesus, Julie E; Baabbad, Rubana; El Bushra, Hassan M

    2014-01-01

    Both genetic and non-genetic environmental factors are involved in the etiology of neural tube defects (NTD) which affect 0.5-2/1000 pregnancies worldwide. This study aimed to explore the risk factors for the development of NTD in Saudi population, and highlight identifiable and preventable causes. Similar studies are scarce in similar populations ofthe Arabian Peninsula and North Africa. This is an unmatched concurrent case-control study including NTD cases born at King Khalid University Hospital, Riyadh during a 4-year period (2002-2006). The case-control study included 25 cases and 125 controls (case: control ratio of 1:5). Years of formal education, employment, household environment (including availability of air conditioning) and rate of parental consanguinity did not differ between mothers of cases and controls. Significantly higher proportion of mothers of cases had history of stillbirth compared to control mothers (16% vs 4.1%, P=0.02). Also family history of hydrocephalus and congenital anomalies were more prevalent in cases than controls (P values=0.0000 and 0.003, respectively). There was significant protective effect of periconceptional folic acid consumption both prior to conception (OR 0.02, 95% CI 0.00-0.07) and during the first 6 weeks of conception (OR 0.13, 95% CI 0.04-0.39). Further research, including a larger cohort, is required to enable ascertainment of gene-nutrient and gene environment interactions associated with NTD in Saudi Arabia.

  11. Neural tube defects in the Republic of Ireland in 2009-11.

    LENUS (Irish Health Repository)

    McDonnell, R

    2014-03-18

    Neural tube defects (NTDs) are associated with deficient maternal folic acid peri-conceptionally. In Ireland, there is no mandatory folic acid food fortification, partly due to declining NTD rates in recent years. The aim of this study was to ascertain the incident rate of NTD during the period 2009-11 and describe epidemiologically NTD in Ireland.METHODSCases were ascertained through multiple sources, including three regional congenital anomaly registers, all maternity hospitals nationally and paediatric hospitals providing care for children with spina bifida in the Republic of Ireland during the period 2009-11.RESULTSFrom 225 998 total births, 236 NTDs were identified, giving an incidence of 1.04\\/1 000 births, increasing from 0.92\\/1 000 in 2009 to 1.17\\/1 000 in 2011. Of all cases, 45% (n = 106) had anencephaly, 49% (n = 115) had spina bifida and 6% (n = 15) had an encephalocoele; 78% (n = 184) were liveborn or stillborn and 22% (n = 52) were terminations abroad. Peri-conceptional folic acid supplement intake was 13.7% among the 52.5% (n = 124) of cases whose folic acid supplement intake was known.CONCLUSIONThe incidence of NTDs in the Republic of Ireland appears to be increasing. Renewed public health interventions, including mandatory folic acid food fortification, must be considered to reduce the incidence of NTD.

  12. Syndromes, Disorders and Maternal Risk Factors Associated With Neural Tube Defects (VII

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-09-01

    Full Text Available Neural tube defects (NTDs may be associated with syndromes, disorders and maternal risk factors. This article provides a comprehensive review of the syndromes, disorders and maternal risk factors associated with NTDs, including DK phocomelia syndrome (von Voss-Cherstvoy syndrome, Siegel-Bartlet syndrome, fetal warfarin syndrome, craniotelencephalic dysplasia, Czeizel-Losonci syndrome, maternal cocaine abuse, Weissenbacher-Zweymüller syndrome, parietal foramina (cranium bifidum, Apert syndrome, craniomicromelic syndrome, XX-agonadism with multiple dysraphic lesions including omphalocele and NTDs, Fryns microphthalmia syndrome, Gershoni-Baruch syndrome, PHAVER syndrome, periconceptional vitamin B6 deficiency, and autosomal dominant Dandy-Walker malformation with occipital cephalocele. NTDs associated with these syndromes, disorders and maternal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders and maternal risk factors may be different from those of nonsyndromic multifactorial NTDs. Perinatal diagnosis of NTDs should alert doctors to the syndromes, disorders and maternal risk factors associated with NTDs, and prompt thorough etiologic investigation and genetic counseling.

  13. MTHFD1 polymorphism as maternal risk for neural tube defects: a meta-analysis.

    Science.gov (United States)

    Zheng, Jinyu; Lu, Xiaocheng; Liu, Hao; Zhao, Penglai; Li, Kai; Li, Lixin

    2015-04-01

    Recently, the association between methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) G1958A polymorphism and neural tube defects (NTD) susceptibility has been widely investigated; however, the results remained inconclusive. Hence, we conducted a meta-analysis to evaluate the effect of MTHFD1 G1958A polymorphism on NTD. The relative literatures were identified by search of the electronic databases PubMed, MEDLINE, and EMBASE. The extracted data were statistically analyzed, and pooled odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated to estimate the association strength using Stata version 11.0 software. Finally, ten studies met our inclusion criteria, including 2,132/4,082 in NTD infants and controls; 1,402/3,136 in mothers with NTD offspring and controls; and 993/2,879 in fathers with NTD offspring and controls. This meta-analysis showed that, compared with the mothers with GG genotype, the women with AA genotype had an increased risk of NTD in their offspring, with OR values and 95 % CI at 1.39 (1.16-1.68), p < 0.001. Interestingly, fathers with AG genotype had a significant decreased risk of NTD offspring (OR = 0.79, 95 % CI = 0.66-0.94, p = 0.009). However, there was no significant association between the MTHFD1 G1958A polymorphism in NTD patients and the risk of NTD. In conclusion, the present meta-analysis provided evidence of the association between maternal MTHFD1 G1958A polymorphism and NTD susceptibility.

  14. Levels of Polycyclic Aromatic Hydrocarbons in Maternal Serum and Risk of Neural Tube Defects in Offspring

    Science.gov (United States)

    2015-01-01

    Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants, and have been reported to be a risk factor for human neural tube defects (NTDs). We investigated the relationship between PAH concentrations in maternal serum and NTD risk in offspring using a case-control study design, and explored the link between PAH concentrations to household energy usage characteristics and life styles. One hundred and seventeen women who had NTD-affected pregnancies (cases) and 121 women who delivered healthy infants (controls) were recruited in Northern China. Maternal blood samples were collected at pregnancy termination or at delivery. Twenty-seven PAHs were measured by gas chromatography–mass spectrometry. The concentrations of 13 individual PAHs detected were significantly higher in the cases than in the controls. Clear dose–response relationships between concentrations of most individual PAHs and the risk of total NTDs or subtypes were observed, even when potential covariates were adjusted for. High-molecular-weight PAHs (H-PAHs) showed higher risk than low-molecular-weight PAHs (L-PAHs). No associations between PAH concentrations and indoor life styles and energy usage characteristics were observed. It was concluded that maternal exposure to PAHs was associated with an increased risk of NTDs, and H-PAHs overall posed a higher risk for NTDs than L-PAHs. PMID:25488567

  15. Management of abnormal serum markers in the absence of aneuploidy or neural tube defects

    Science.gov (United States)

    Schnettler, William T.; Hacker, Michele R.; Barber, Rachel E.; Rana, Sarosh

    2013-01-01

    Objective Few guidelines address the management of pregnancies complicated by abnormal maternal serum analytes (MSAs) in the absence of aneuploidy or neural tube defects (NTDs). Our objective was to gather preliminary data regarding current opinions and management strategies among perinatologists in the US. Methods This survey of Maternal Fetal Medicine (MFM) physicians and fellows used a secure electronic web-based data capture tool. Results A total of 545 potential participants were contacted, and 136 (25%) responded. The majority were experienced academic physicians with robust practices. Nearly all (97.7%) respondents reported a belief in an association between abnormal MSAs and adverse pregnancy outcomes other than aneuploidy or NTDs. Plasma protein A (PAPP-A) and α-fetoprotein (AFP) were most often chosen as markers demonstrating a strong association with adverse outcomes. Most (86.9%) respondents acknowledged that abnormal MSAs influenced their counseling approach, and the majority (80.1%) offered additional ultrasound examinations. Nearly half started at 28 weeks and almost one-third at 32 weeks. Respondents acknowledging a relevant protocol in their hospital or practice were more likely to offer additional antenatal testing (p = 0.01). Conclusions Although most perinatologists were in agreement regarding the association of MSAs with adverse pregnancy outcomes, a lack of consensus exists regarding management strategies. PMID:22372385

  16. Incidence of neural tube defects in the natural radiation coastal areas of Kerala

    International Nuclear Information System (INIS)

    Jaikrishan, G.; Sudheer, K.R.; Andrews, V.J.; Koya, P.K.M.; Cheriyan, V.D.; Seshadri, M.

    2010-01-01

    All consecutive births in selected government hospitals in and around the high level natural background radiation areas (HLNRA) of Kerala were monitored for congenital malformations observable at birth since 1995. The HLNR area, a coastal strip of land about 55 km in length and 0.5 km in breadth from Purakkad in the north in Alleppey district to Sakthikulangara in the south of Quilon district, stands out among the most prominent background radiation areas of the world. Natural deposit of monazite sand, containing Thorium (8-10%), Uranium (0.3%) and corresponding decay products, is the source of elevated background radiation, ranging from < 1 to 45 mGy/year. Wide variation in dose, due to the patchy and non-uniform distribution of Monazite sand, enables in built controls. High population density, limited migration, ethnic diversity, good literacy, health awareness, institutionalized births and acceptance of small family norm are some of the key features of the population. Areas with a mean radiation dose of more than 1.5 mGy/year were treated as HLNR areas and areas with a dose level of 1.5 mGy/year or less were treated as normal level radiation (NLNR) areas. The study carried out since 1995 does not seem to implicate HLNR in the incidence of neural tube defects among newborns

  17. Nutrition, One-Carbon Metabolism and Neural Tube Defects: A Review

    Directory of Open Access Journals (Sweden)

    Kelei Li

    2016-11-01

    Full Text Available Neural tube defects (NTDs are a group of severe congenital malformations, induced by the combined effects of genes and the environment. The most valuable finding so far has been the protective effect of folic acid supplementation against NTDs. However, many women do not take folic acid supplements until they are pregnant, which is too late to prevent NTDs effectively. Long-term intake of folic acid–fortified food is a good choice to solve this problem, and mandatory folic acid fortification should be further promoted, especially in Europe, Asia and Africa. Vitamin B2, vitamin B-6, vitamin B-12, choline, betaine and n-3 polyunsaturated fatty acids (PUFAs can also reduce the NTD risk by interacting with the one-carbon metabolism pathway. This suggest that multivitamin B combined with choline, betaine and n-3 PUFAs supplementation may have a better protective effect against NTDs than folic acid alone. Genetic polymorphisms involved in one-carbon metabolism are associated with NTD risk, and gene screening for women of childbearing age prior to pregnancy may help prevent NTDs induced by the risk allele. In addition, the consumption of alcohol, tea and coffee, and low intakes of fruit and vegetable are also associated with the increased risk of NTDs, and should be avoided by women of childbearing age.

  18. Neural tube defects in Malaysia: data from the Malaysian National Neonatal Registry.

    Science.gov (United States)

    Boo, Nem-Yun; Cheah, Irene G S; Thong, Meow-Keong

    2013-10-01

    This study aimed to determine the prevalence and early outcome of neural tube defects (NTDs) in Malaysia. This prospective study included all neonates with NTDs (spina bifida, anencephaly, encephalocoele) born in 2009 in 32 Malaysian hospitals in the Malaysian National Neonatal Network. The prevalence of NTDs was 0.42 per 1000 live births, being highest among the indigenous people of Sarawak (1.09 per 1000 live births) and lowest among Malaysians of Chinese descent (0.09 per 1000 live births). The most common type of NTDs was anencephaly (0.19 per 1000 live births), followed by spina bifida (0.11 per 1000 live births) and encephalocoele (0.07 per 1000 live births). Majority of the infants with anencephaly (94.5%, n = 51), 45.8% (n = 11) with encephalocoele and 9.5% (n = 4) with spina bifida died. The median duration of hospital stay was 4 (range: 0-161) days. NTDs were common in Malaysia. Mortality was high. Long-term monitoring of NTD prevalence following folic fortification of food is recommended.

  19. System and method for determining stability of a neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2011-01-01

    Disclosed are methods, systems, and computer-readable media for determining stability of a neural system. The method includes tracking a function world line of an N element neural system within at least one behavioral space, determining whether the tracking function world line is approaching a psychological stability surface, and implementing a quantitative solution that corrects instability if the tracked function world line is approaching the psychological stability surface.

  20. Modulation of nuclear factor-κB signaling and reduction of neural tube defects by quercetin-3-glucoside in embryos of diabetic mice.

    Science.gov (United States)

    Tan, Chengyu; Meng, Fantong; Reece, E Albert; Zhao, Zhiyong

    2018-05-04

    Diabetes mellitus in early pregnancy increases the risk of birth defects in infants. Maternal hyperglycemia stimulates the expression of nitric oxide (NO) synthase 2 (NOS2), which can be regulated by transcription factors of the nuclear factor-κB (NF-κB) family. Increases in reactive nitrogen species (RNS) generate intracellular stress conditions, including nitrosative, oxidative, and endoplasmic reticulum (ER) stresses, and trigger programmed cell death (or apoptosis) in the neural folds, resulting in neural tube defects (NTDs) in the embryo. Inhibiting NOS2 can reduce NTDs; however, the underlying mechanisms require further delineation. Targeting NOS2 and associated nitrosative stress using naturally occurring phytochemicals is a potential approach to preventing birth defects in diabetic pregnancies. This study aims to investigate the effect of quercetin-3-glucoside (Q3G), a polyphenol flavonoid found in fruit, in reducing maternal diabetes-induced NTDs in an animal model, and to delineate the molecular mechanisms underlying Q3G action in regulating NOS2 expression. Female mice (C57BL/6) were induced to develop diabetes using streptozotocin before pregnancy. Diabetic pregnant mice were administered Q3G (100 mg/kg) daily via gavage feeding, introduction of drug to the stomach directly via a feeding needle, during neurulation from embryonic (E) day 6.5 to E9.5. After treatment, E10.5 embryos were collected and examined for the presence of NTDs and apoptosis in the neural tube. Expression of Nos2 and superoxide dismutase 1 (Sod1; an antioxidative enzyme) was quantified using Western blot assay. Nitrosative, oxidative, and endoplasmic reticulum (ER) stress conditions were assessed using specific biomarkers. Expression and posttranslational modification of factors in the NF-κB system were investigated. Treatment with Q3G (suspended in water) significantly decreased NTD rate (24.7%) and apoptosis in the embryos of diabetic mice, compared with those in the water

  1. Analysis of complex systems using neural networks

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

  2. Collaborative Recurrent Neural Networks forDynamic Recommender Systems

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:366–381, 2016 ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young...an unprece- dented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating...Recurrent Neural Network, Recommender System , Neural Language Model, Collaborative Filtering 1. Introduction As ever larger parts of the population

  3. Neural-specific deletion of Htra2 causes cerebellar neurodegeneration and defective processing of mitochondrial OPA1.

    Directory of Open Access Journals (Sweden)

    Victoria L Patterson

    Full Text Available HTRA2, a serine protease in the intermembrane space, has important functions in mitochondrial stress signaling while its abnormal activity may contribute to the development of Parkinson's disease. Mice with a missense or null mutation of Htra2 fail to thrive, suffer striatal neuronal loss, and a parkinsonian phenotype that leads to death at 30-40 days of age. While informative, these mouse models cannot separate neural contributions from systemic effects due to the complex phenotypes of HTRA2 deficiency. Hence, we developed mice carrying a Htra2-floxed allele to query the consequences of tissue-specific HTRA2 deficiency. We found that mice with neural-specific deletion of Htra2 exhibited atrophy of the thymus and spleen, cessation to gain weight past postnatal (P day 18, neurological symptoms including ataxia and complete penetrance of premature death by P40. Histologically, increased apoptosis was detected in the cerebellum, and to a lesser degree in the striatum and the entorhinal cortex, from P25. Even earlier at P20, mitochondria in the cerebella already exhibited abnormal morphology, including swelling, vesiculation, and fragmentation of the cristae. Furthermore, the onset of these structural anomalies was accompanied by defective processing of OPA1, a key molecule for mitochondrial fusion and cristae remodeling, leading to depletion of the L-isoform. Together, these findings suggest that HTRA2 is essential for maintenance of the mitochondrial integrity in neurons. Without functional HTRA2, a lifespan as short as 40 days accumulates a large quantity of dysfunctional mitochondria that contributes to the demise of mutant mice.

  4. IMPLEMENTATION OF NEURAL - CRYPTOGRAPHIC SYSTEM USING FPGA

    Directory of Open Access Journals (Sweden)

    KARAM M. Z. OTHMAN

    2011-08-01

    Full Text Available Modern cryptography techniques are virtually unbreakable. As the Internet and other forms of electronic communication become more prevalent, electronic security is becoming increasingly important. Cryptography is used to protect e-mail messages, credit card information, and corporate data. The design of the cryptography system is a conventional cryptography that uses one key for encryption and decryption process. The chosen cryptography algorithm is stream cipher algorithm that encrypt one bit at a time. The central problem in the stream-cipher cryptography is the difficulty of generating a long unpredictable sequence of binary signals from short and random key. Pseudo random number generators (PRNG have been widely used to construct this key sequence. The pseudo random number generator was designed using the Artificial Neural Networks (ANN. The Artificial Neural Networks (ANN providing the required nonlinearity properties that increases the randomness statistical properties of the pseudo random generator. The learning algorithm of this neural network is backpropagation learning algorithm. The learning process was done by software program in Matlab (software implementation to get the efficient weights. Then, the learned neural network was implemented using field programmable gate array (FPGA.

  5. Simulating neural systems with Xyce.

    Energy Technology Data Exchange (ETDEWEB)

    Schiek, Richard Louis; Thornquist, Heidi K.; Mei, Ting; Warrender, Christina E.; Aimone, James Bradley; Teeter, Corinne; Duda, Alex M.

    2012-12-01

    Sandias parallel circuit simulator, Xyce, can address large scale neuron simulations in a new way extending the range within which one can perform high-fidelity, multi-compartment neuron simulations. This report documents the implementation of neuron devices in Xyce, their use in simulation and analysis of neuron systems.

  6. Evaluation of common genetic variants in 82 candidate genes as risk factors for neural tube defects

    LENUS (Irish Health Repository)

    Pangilinan, Faith

    2012-08-02

    AbstractBackgroundNeural tube defects (NTDs) are common birth defects (~1 in 1000 pregnancies in the US and Europe) that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T) and MTHFD1 rs2236225 (R653Q)) have been found to increase NTD risk. We hypothesized that variants in additional folate\\/B12 pathway genes contribute to NTD risk.MethodsA tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate\\/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents), including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects.ResultsNearly 70 SNPs in 30 genes were found to be associated with NTDs at the p < 0.01 level. The ten strongest association signals (p-value range: 0.0003–0.0023) were found in nine genes (MFTC, CDKN2A, ADA, PEMT, CUBN, GART, DNMT3A, MTHFD1 and T (Brachyury)) and included the known NTD risk factor MTHFD1 R653Q (rs2236225). The single strongest signal was observed in a new candidate, MFTC rs17803441 (OR = 1.61 [1.23-2.08], p = 0.0003 for the minor allele). Though nominally significant, these associations did not remain significant after correction for multiple hypothesis testing.ConclusionsTo our knowledge, with respect to sample size and scope of evaluation of candidate polymorphisms, this is the largest NTD genetic association study reported to date. The scale of the study and the

  7. Detection of copy number variants reveals association of cilia genes with neural tube defects.

    Directory of Open Access Journals (Sweden)

    Xiaoli Chen

    Full Text Available BACKGROUND: Neural tube defects (NTDs are one of the most common birth defects caused by a combination of genetic and environmental factors. Currently, little is known about the genetic basis of NTDs although up to 70% of human NTDs were reported to be attributed to genetic factors. Here we performed genome-wide copy number variants (CNVs detection in a cohort of Chinese NTD patients in order to exam the potential role of CNVs in the pathogenesis of NTDs. METHODS: The genomic DNA from eighty-five NTD cases and seventy-five matched normal controls were subjected for whole genome CNVs analysis. Non-DGV (the Database of Genomic Variants CNVs from each group were further analyzed for their associations with NTDs. Gene content in non-DGV CNVs as well as participating pathways were examined. RESULTS: Fifty-five and twenty-six non-DGV CNVs were detected in cases and controls respectively. Among them, forty and nineteen CNVs involve genes (genic CNV. Significantly more non-DGV CNVs and non-DGV genic CNVs were detected in NTD patients than in control (41.2% vs. 25.3%, p<0.05 and 37.6% vs. 20%, p<0.05. Non-DGV genic CNVs are associated with a 2.65-fold increased risk for NTDs (95% CI: 1.24-5.87. Interestingly, there are 41 cilia genes involved in non-DGV CNVs from NTD patients which is significantly enriched in cases compared with that in controls (24.7% vs. 9.3%, p<0.05, corresponding with a 3.19-fold increased risk for NTDs (95% CI: 1.27-8.01. Pathway analyses further suggested that two ciliogenesis pathways, tight junction and protein kinase A signaling, are top canonical pathways implicated in NTD-specific CNVs, and these two novel pathways interact with known NTD pathways. CONCLUSIONS: Evidence from the genome-wide CNV study suggests that genic CNVs, particularly ciliogenic CNVs are associated with NTDs and two ciliogenesis pathways, tight junction and protein kinase A signaling, are potential pathways involved in NTD pathogenesis.

  8. Evaluation of common genetic variants in 82 candidate genes as risk factors for neural tube defects

    Directory of Open Access Journals (Sweden)

    Pangilinan Faith

    2012-08-01

    Full Text Available Abstract Background Neural tube defects (NTDs are common birth defects (~1 in 1000 pregnancies in the US and Europe that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T and MTHFD1 rs2236225 (R653Q have been found to increase NTD risk. We hypothesized that variants in additional folate/B12 pathway genes contribute to NTD risk. Methods A tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents, including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects. Results Nearly 70 SNPs in 30 genes were found to be associated with NTDs at the p MFTC, CDKN2A, ADA, PEMT, CUBN, GART, DNMT3A, MTHFD1 and T (Brachyury and included the known NTD risk factor MTHFD1 R653Q (rs2236225. The single strongest signal was observed in a new candidate, MFTC rs17803441 (OR = 1.61 [1.23-2.08], p = 0.0003 for the minor allele. Though nominally significant, these associations did not remain significant after correction for multiple hypothesis testing. Conclusions To our knowledge, with respect to sample size and scope of evaluation of candidate polymorphisms, this is the largest NTD genetic association study reported to date. The scale of the study and the stringency of correction are likely to have contributed to real associations failing to survive

  9. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    Science.gov (United States)

    1996-01-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

  10. Folic acid supplements to prevent neural tube defects: trends in East of Ireland 1996-2002.

    LENUS (Irish Health Repository)

    Ward, M

    2004-10-01

    Promotion of folic acid to prevent neural Tube Defects (NTD) has been ongoing for ten years in Ireland, without a concomitant reduction in the total birth prevalence of NTD. The effectiveness of folic acid promotion as the sole means of primary prevention of NTD is therefore questionable. We examined trends in folic acid knowledge and peri-conceptional use from 1996-2002 with the aim of assessing the value of this approach. From 1996-2002, 300 women attending ante-natal clinics in Dublin hospitals annually were surveyed regarding their knowledge and use of folic acid. During the period the proportion who had heard of folic acid rose from 54% to 94% between 1996 and 2002 (c2 test for trend: p<0.001). Knowledge that folic acid can prevent NTD also rose from 21% to 66% (c2 test for trend: p<0.001). Although the proportion who took folic acid during pregnancy increased from 14% to 83% from 1996 to 2002 (c2 test for trend: p<0.001), peri-conceptional intake did not rise above 24% in any year. There is a high awareness of folic acid and its relation to NTD, which is not matched by peri-conceptional uptake. The main barrier to peri-conceptional uptake is the lack of pregnancy planning. To date promotional campaigns appear to have been ineffective in reducing the prevalence of NTD in Ireland. Consequently, fortification of staple foodstuffs is the only practical and reliable means of primary prevention of NTD.

  11. Maternal exposure to arsenic, cadmium, lead, and mercury and neural tube defects in offspring

    International Nuclear Information System (INIS)

    Brender, Jean D.; Suarez, Lucina; Felkner, Marilyn; Gilani, Zunera; Stinchcomb, David; Moody, Karen; Henry, Judy; Hendricks, Katherine

    2006-01-01

    Arsenic, cadmium, lead, and mercury are neurotoxins, and some studies suggest that these elements might also be teratogens. Using a case-control study design, we investigated the relation between exposure to these heavy metals and neural tube defects (NTDs) in offspring of Mexican-American women living in 1 of the 14 Texas counties bordering Mexico. A total of 184 case-women with NTD-affected pregnancies and 225 control-women with normal live births were interviewed about their environmental and occupational exposures during the periconceptional period. Biologic samples for blood lead and urinary arsenic, cadmium, and mercury were also obtained for a subset of these women. Overall, the median levels of these biomarkers for heavy metal exposure did not differ significantly (P>0.05) between case- and control-women. However, among women in the highest income group, case-women were nine times more likely (95% confidence interval (CI) 1.4-57) than control-women to have a urinary mercury >=5.62μg/L. Case-women were 4.2 times more likely (95% CI 1.1-16) to report burning treated wood during the periconceptional period than control-women. Elevated odds ratios (ORs) were observed for maternal and paternal occupational exposures to arsenic and mercury, but the 95% CIs were consistent with unity. The 95% CIs of the ORs were also consistent with unity for higher levels of arsenic, cadmium, lead, and mercury in drinking water and among women who lived within 2 miles at the time of conception to industrial facilities with reported emissions of any of these heavy metals. Our findings suggest that maternal exposures to arsenic, cadmium, or lead are probably not significant risk factors for NTDs in offspring. However, the elevated urinary mercury levels found in this population and exposures to the combustion of treated wood may warrant further investigation

  12. Novel Mutation of LRP6 Identified in Chinese Han Population Links Canonical WNT Signaling to Neural Tube Defects.

    Science.gov (United States)

    Shi, Zhiwen; Yang, Xueyan; Li, Bin-Bin; Chen, Shuxia; Yang, Luming; Cheng, Liangping; Zhang, Ting; Wang, Hongyan; Zheng, Yufang

    2018-01-15

    Neural tube defects (NTDs), the second most frequent cause of human congenital abnormalities, are debilitating birth defects due to failure of neural tube closure. It has been shown that noncanonical WNT/planar cell polarity (PCP) signaling is required for convergent extension (CE), the initiation step of neural tube closure (NTC). But the effect of canonical WNT//β-catenin signaling during NTC is still elusive. LRP6 (low density lipoprotein receptor related proteins 6) was identified as a co-receptor for WNT/β-catenin signaling, but recent studies showed that it also can mediate WNT/PCP signaling. In this study, we screened mutations in the LRP6 gene in 343 NTDs and 215 ethnically matched normal controls of Chinese Han population. Three rare missense mutations (c.1514A>G, p.Y505C); c.2984A>G, p.D995G; and c.4280C>A, p.P1427Q) of the LRP6 gene were identified in Chinese NTD patients. The Y505C mutation is a loss-of-function mutation on both WNT/β-catenin and PCP signaling. The D995G mutation only partially lost inhibition on PCP signaling without affecting WNT/β-catenin signaling. The P1427Q mutation dramatically increased WNT/β-catenin signaling but only mildly loss of inhibition on PCP signaling. All three mutations failed to rescue CE defects caused by lrp6 morpholino oligos knockdown in zebrafish. Of interest, when overexpressed, D995G did not induce any defects, but Y505C and P1427Q caused more severe CE defects in zebrafish. Our results suggested that over-active canonical WNT signaling induced by gain-of-function mutation in LRP6 could also contribute to human NTDs, and a balanced WNT/β-catenin and PCP signaling is probably required for proper neural tube development. Birth Defects Research 110:63-71, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  13. Dynamic artificial neural networks with affective systems.

    Directory of Open Access Journals (Sweden)

    Catherine D Schuman

    Full Text Available Artificial neural networks (ANNs are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP and long term depression (LTD, and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance.

  14. Dynamical systems, attractors, and neural circuits.

    Science.gov (United States)

    Miller, Paul

    2016-01-01

    Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic-they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

  15. Neural System Prediction and Identification Challenge

    Directory of Open Access Journals (Sweden)

    Ioannis eVlachos

    2013-12-01

    Full Text Available Can we infer the function of a biological neural network (BNN if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC. We provide the connectivity and activity of all neurons and invite participants (i to infer the functions implemented (hard-wired in spiking neural networks (SNNs by stimulating and recording the activity of neurons and, (ii to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  16. Neural system prediction and identification challenge.

    Science.gov (United States)

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  17. Maternal Use of Weight Loss Products and the Risk of Neural Tube Defects in Offspring: A Systematic Literature Review.

    Science.gov (United States)

    Hoang, Thanh T; Agopian, A J; Mitchell, Laura E

    2018-01-15

    Several studies have assessed potential associations between use of weight loss products in the periconceptional period and neural tube defects (NTDs). However, the individual studies are inconclusive and there has not been a systematic review of this literature. We conducted a systematic search, using Ovid MEDLINE and PubMed, to identify studies that evaluated the association between products used for weight loss and the risk of NTDs. Because many studies of birth defects only evaluate a composite birth defect outcome, we evaluated studies that defined the outcome as "any major birth defect" or as NTDs. We abstracted data on study design, exposure definition, outcome definition, covariates and effect size estimates from each article that met our inclusion criteria. For studies that evaluated a composite birth defect outcome, we also abstracted the number of NTD cases included in the composite outcome. We used a modified version of the Newcastle-Ottawa Scale to assess the quality of each article. We screened 865 citations and identified nine articles that met our inclusion criteria. The majority of studies reported positive associations between maternal use of weight loss products and birth defects (overall and NTDs). However, there were few significant associations and there was considerable heterogeneity in the specific exposures assessed across the nine studies. Our systematic review of weight loss products and NTDs indicates that the literature on this topic is sparse. Because several studies reported modest, positive associations between risk and use of weight loss products, additional studies are warranted. Birth Defects Research 110:48-55, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  18. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network

    International Nuclear Information System (INIS)

    Garcia, Gabe V.

    2005-01-01

    A major cause of failure in nuclear steam generators is degradation of their tubes. Although seven primary defect categories exist, one of the principal causes of tube failure is intergranular attack/stress corrosion cracking (IGA/SCC). This type of defect usually begins on the secondary side surface of the tubes and propagates both inwards and laterally. In many cases this defect is found at or near the tube support plates

  19. Defect design of insulation systems for photovoltaic modules

    Science.gov (United States)

    Mon, G. R.

    1981-01-01

    A defect-design approach to sizing electrical insulation systems for terrestrial photovoltaic modules is presented. It consists of gathering voltage-breakdown statistics on various thicknesses of candidate insulation films where, for a designated voltage, module failure probabilities for enumerated thickness and number-of-layer film combinations are calculated. Cost analysis then selects the most economical insulation system. A manufacturing yield problem is solved to exemplify the technique. Results for unaged Mylar suggest using fewer layers of thicker films. Defect design incorporates effects of flaws in optimal insulation system selection, and obviates choosing a tolerable failure rate, since the optimization process accomplishes that. Exposure to weathering and voltage stress reduces the voltage-withstanding capability of module insulation films. Defect design, applied to aged polyester films, promises to yield reliable, cost-optimal insulation systems.

  20. Radioimmunoassay of alpha-foetoprotein in the eluate of dried blood. A method for antenatal screening of neural tube defects

    International Nuclear Information System (INIS)

    Travert, G.; Herlicoviez, M.; Laroche, D.

    1979-01-01

    A radioimmunoassay for alpha-foetoprotein (AFP) in dried blood spots is reported. The main technical characteristics (reproducibility, sensitivity, recovery of exogenous AFP added and AFP stability in dried blood) are evaluated. They indicate that this method is feasible and well adapted to AFP measurement during pregnancy. AFP determination in maternal serum allows early detection of at least 80% of neural tube defects. The use of dried blood spots as samples for AFP assay makes our method a possible mass screening test for these malformations, which occur with an incidence of 12 for 10,000 [fr

  1. Epigenetic profiles in children with a neural tube defect; a case-control study in two populations.

    Directory of Open Access Journals (Sweden)

    Lisette Stolk

    Full Text Available Folate deficiency is implicated in the causation of neural tube defects (NTDs. The preventive effect of periconceptional folic acid supplement use is partially explained by the treatment of a deranged folate-dependent one carbon metabolism, which provides methyl groups for DNA-methylation as an epigenetic mechanism. Here, we hypothesize that variations in DNA-methylation of genes implicated in the development of NTDs and embryonic growth are part of the underlying mechanism. In 48 children with a neural tube defect and 62 controls from a Dutch case-control study and 34 children with a neural tube defect and 78 controls from a Texan case-control study, we measured the DNA-methylation levels of imprinted candidate genes (IGF2-DMR, H19, KCNQ1OT1 and non-imprinted genes (the LEKR/CCNL gene region associated with birth weight, and MTHFR and VANGL1 associated with NTD. We used the MassARRAY EpiTYPER assay from Sequenom for the assessment of DNA-methylation. Linear mixed model analysis was used to estimate associations between DNA-methylation levels of the genes and a neural tube defect. In the Dutch study group, but not in the Texan study group we found a significant association between the risk of having an NTD and DNA methylation levels of MTHFR (absolute decrease in methylation of -0.33% in cases, P-value = 0.001, and LEKR/CCNL (absolute increase in methylation: 1.36% in cases, P-value = 0.048, and a borderline significant association for VANGL (absolute increase in methylation: 0.17% in cases, P-value = 0.063. Only the association between MTHFR and NTD-risk remained significant after multiple testing correction. The associations in the Dutch study were not replicated in the Texan study. We conclude that the associations between NTDs and the methylation of the MTHFR gene, and maybe VANGL and LEKKR/CNNL, are in line with previous studies showing polymorphisms in the same genes in association with NTDs and embryonic development

  2. E-cigarette aerosol exposure can cause craniofacial defects in Xenopus laevis embryos and mammalian neural crest cells.

    Directory of Open Access Journals (Sweden)

    Allyson E Kennedy

    Full Text Available Since electronic cigarette (ECIG introduction to American markets in 2007, vaping has surged in popularity. Many, including women of reproductive age, also believe that ECIG use is safer than traditional tobacco cigarettes and is not hazardous when pregnant. However, there are few studies investigating the effects of ECIG exposure on the developing embryo and nothing is known about potential effects on craniofacial development. Therefore, we have tested the effects of several aerosolized e-cigarette liquids (e-cigAM in an in vivo craniofacial model, Xenopus laevis, as well as a mammalian neural crest cell line. Results demonstrate that e-cigAM exposure during embryonic development induces a variety of defects, including median facial clefts and midface hypoplasia in two of e-cigAMs tested e-cigAMs. Detailed quantitative analyses of the facial morphology revealed that nicotine is not the main factor in inducing craniofacial defects, but can exacerbate the effects of the other e-liquid components. Additionally, while two different e-cigAMs can have very similar consequences on facial appearances, there are subtle differences that could be due to the differences in e-cigAM components. Further assessment of embryos exposed to these particular e-cigAMs revealed cranial cartilage and muscle defects and a reduction in the blood supply to the face. Finally, the expression of markers for vascular and cartilage differentiation was reduced in a mammalian neural crest cell line corroborating the in vivo effects. Our work is the first to show that ECIG use could pose a potential hazard to the developing embryo and cause craniofacial birth defects. This emphasizes the need for more testing and regulation of this new popular product.

  3. E-cigarette aerosol exposure can cause craniofacial defects in Xenopus laevis embryos and mammalian neural crest cells.

    Science.gov (United States)

    Kennedy, Allyson E; Kandalam, Suraj; Olivares-Navarrete, Rene; Dickinson, Amanda J G

    2017-01-01

    Since electronic cigarette (ECIG) introduction to American markets in 2007, vaping has surged in popularity. Many, including women of reproductive age, also believe that ECIG use is safer than traditional tobacco cigarettes and is not hazardous when pregnant. However, there are few studies investigating the effects of ECIG exposure on the developing embryo and nothing is known about potential effects on craniofacial development. Therefore, we have tested the effects of several aerosolized e-cigarette liquids (e-cigAM) in an in vivo craniofacial model, Xenopus laevis, as well as a mammalian neural crest cell line. Results demonstrate that e-cigAM exposure during embryonic development induces a variety of defects, including median facial clefts and midface hypoplasia in two of e-cigAMs tested e-cigAMs. Detailed quantitative analyses of the facial morphology revealed that nicotine is not the main factor in inducing craniofacial defects, but can exacerbate the effects of the other e-liquid components. Additionally, while two different e-cigAMs can have very similar consequences on facial appearances, there are subtle differences that could be due to the differences in e-cigAM components. Further assessment of embryos exposed to these particular e-cigAMs revealed cranial cartilage and muscle defects and a reduction in the blood supply to the face. Finally, the expression of markers for vascular and cartilage differentiation was reduced in a mammalian neural crest cell line corroborating the in vivo effects. Our work is the first to show that ECIG use could pose a potential hazard to the developing embryo and cause craniofacial birth defects. This emphasizes the need for more testing and regulation of this new popular product.

  4. 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.

  5. Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

    NARCIS (Netherlands)

    Chen, Junwen; Liu, Zhigang; Wang, H.; Nunez Vicencio, Alfredo; Han, Zhiwei

    2018-01-01

    The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary

  6. Neural systems for preparatory control of imitation.

    Science.gov (United States)

    Cross, Katy A; Iacoboni, Marco

    2014-01-01

    Humans have an automatic tendency to imitate others. Previous studies on how we control these tendencies have focused on reactive mechanisms, where inhibition of imitation is implemented after seeing an action. This work suggests that reactive control of imitation draws on at least partially specialized mechanisms. Here, we examine preparatory imitation control, where advance information allows control processes to be employed before an action is observed. Drawing on dual route models from the spatial compatibility literature, we compare control processes using biological and non-biological stimuli to determine whether preparatory imitation control recruits specialized neural systems that are similar to those observed in reactive imitation control. Results indicate that preparatory control involves anterior prefrontal, dorsolateral prefrontal, posterior parietal and early visual cortices regardless of whether automatic responses are evoked by biological (imitative) or non-biological stimuli. These results indicate both that preparatory control of imitation uses general mechanisms, and that preparatory control of imitation draws on different neural systems from reactive imitation control. Based on the regions involved, we hypothesize that preparatory control is implemented through top-down attentional biasing of visual processing.

  7. [C677T polymorphism of the methylentetrahydrofolate reductase gene in mothers of children affected with neural tube defects].

    Science.gov (United States)

    Morales de Machín, Alisandra; Méndez, Karile; Solís, Ernesto; Borjas de Borjas, Lisbeth; Bracho, Ana; Hernández, María Luisa; Negrón, Aimara; Delgado, Wilmer; Sánchez, Yanira

    2015-09-01

    Neural tube defects (NTD) are the most common congenital anomalies of the central nervous system, with a multifactorial pattern of inheritance, presumably involving the interaction of several genetic and environmental factors. The methylenetetrahydrofolate reductase (MTHFR) gene 677C>T polymorphism has been implicated as a risk factor for NTD. The main objective of this research was to investigate the association of the 677C>T polymorphism of the MTHFR gene as a genetic risk factor for NTD. Molecular analysis was performed in DNA samples from 52 mothers with antecedent of NTD offspring and from 119 healthy control mothers. Using the Polymerase Chain Reaction, a 198 bases pairs fragment was digested with the restriction enzyme Hinfi. 677T MTHFR allele frequencies for the problem and the control groups were 51.92% and 34.45%, respectively, and 677C MTHFR allele frequencies were 48.08% and 65.55%, respectively. There were significant differences in allele (p: 0.002) and genotype (p: 0.007) frequencies between these two groups. The odds ratio (OR) to the TT genotype vs. the CC genotype was estimated as OR: 4.9 [95% CI: 1,347-6.416] p: 0.002; CT+TT vs. CC: OR: 2.9 [95% CI: 1.347-6.416] p: 0.005; TT vs. CT+CC: OR: 2.675 [95% CI: 1,111-6.441] p: 0.024. The data presented in this study support the relationship between MTHFR 677C>T polymorphism and risk in mothers with antecedent of NTD offspring.

  8. Genome-wide association mapping in dogs enables identification of the homeobox gene, NKX2-8, as a genetic component of neural tube defects in humans.

    Directory of Open Access Journals (Sweden)

    Noa Safra

    Full Text Available Neural tube defects (NTDs is a general term for central nervous system malformations secondary to a failure of closure or development of the neural tube. The resulting pathologies may involve the brain, spinal cord and/or vertebral column, in addition to associated structures such as soft tissue or skin. The condition is reported among the more common birth defects in humans, leading to significant infant morbidity and mortality. The etiology remains poorly understood but genetic, nutritional, environmental factors, or a combination of these, are known to play a role in the development of NTDs. The variable conditions associated with NTDs occur naturally in dogs, and have been previously reported in the Weimaraner breed. Taking advantage of the strong linkage-disequilibrium within dog breeds we performed genome-wide association analysis and mapped a genomic region for spinal dysraphism, a presumed NTD, using 4 affected and 96 unaffected Weimaraners. The associated region on canine chromosome 8 (pgenome  =3.0 × 10(-5, after 100,000 permutations, encodes 18 genes, including NKX2-8, a homeobox gene which is expressed in the developing neural tube. Sequencing NKX2-8 in affected Weimaraners revealed a G to AA frameshift mutation within exon 2 of the gene, resulting in a premature stop codon that is predicted to produce a truncated protein. The exons of NKX2-8 were sequenced in human patients with spina bifida and rare variants (rs61755040 and rs10135525 were found to be significantly over-represented (p=0.036. This is the first documentation of a potential role for NKX2-8 in the etiology of NTDs, made possible by investigating the molecular basis of naturally occurring mutations in dogs.

  9. Mechanisms underlying metabolic and neural defects in zebrafish and human multiple acyl-CoA dehydrogenase deficiency (MADD.

    Directory of Open Access Journals (Sweden)

    Yuanquan Song

    2009-12-01

    Full Text Available In humans, mutations in electron transfer flavoprotein (ETF or electron transfer flavoprotein dehydrogenase (ETFDH lead to MADD/glutaric aciduria type II, an autosomal recessively inherited disorder characterized by a broad spectrum of devastating neurological, systemic and metabolic symptoms. We show that a zebrafish mutant in ETFDH, xavier, and fibroblast cells from MADD patients demonstrate similar mitochondrial and metabolic abnormalities, including reduced oxidative phosphorylation, increased aerobic glycolysis, and upregulation of the PPARG-ERK pathway. This metabolic dysfunction is associated with aberrant neural proliferation in xav, in addition to other neural phenotypes and paralysis. Strikingly, a PPARG antagonist attenuates aberrant neural proliferation and alleviates paralysis in xav, while PPARG agonists increase neural proliferation in wild type embryos. These results show that mitochondrial dysfunction, leading to an increase in aerobic glycolysis, affects neurogenesis through the PPARG-ERK pathway, a potential target for therapeutic intervention.

  10. Influence of defects on the vibrations of rotating systems

    International Nuclear Information System (INIS)

    Lazarus, A.

    2008-01-01

    For high rotation speeds, the imperfections (cracks, anisotropy...) of rotating machinery of the energy sector lead to a specific vibratory behavior which can damage the machine. The simulation of rotating machinery are usually realized for systems without defect. The aim of this thesis is to understand the influence of defects and to propose an algorithm to predict the dynamical behavior. In a first part the author studies the simplified rotating oscillators to propose a numerical method in order to taking into account the dynamic of these systems. This method is then applied to real rotating machinery with the Cast3m software. The numerical results are validated with experiments. (A.L.B.)

  11. Maternal Antenatal Bereavement and Neural Tube Defect in Live-Born Offspring

    DEFF Research Database (Denmark)

    Ingstrup, Katja Glejsted; Wu, Chun Sen; Olsen, Jørn

    2016-01-01

    BACKGROUND: Maternal emotional stress during pregnancy has previously been associated with congenital neural malformations, but most studies are based on data collected retrospectively. The objective of our study was to investigate associations between antenatal maternal bereavement due to death...

  12. Brain tissue aspiration neural tube defect Aspiração de tecido cerebral em casos de defeitos de fechamento do tubo neural

    Directory of Open Access Journals (Sweden)

    Luiz Cesar Peres

    2005-09-01

    Full Text Available The study aimed to find out how frequent is brain tissue aspiration and if brain tissue heterotopia could be found in the lung of human neural tube defect cases. Histological sections of each lobe of both lungs of 22 fetuses and newborn with neural tube defect were immunostained for glial fibrillary acidic protein (GFAP. There were 15 (68.2% females and 7 (31.8% males. Age ranged from 18 to 40 weeks of gestation (mean= 31.8. Ten (45.5% were stillborn, the same newborn, and 2 (9.1% were abortuses. Diagnosis were: craniorrhachischisis (9 cases, 40.9%, anencephaly (8 cases, 36,4%, ruptured occipital encephalocele and rachischisis (2 cases, 9.1% each, and early amniotic band disruption sequence (1 case, 4.5%. Only one case (4.5% exhibited GFAP positive cells inside bronchioles and alveoli admixed to epithelial amniotic squames. No heterotopic tissue was observed in the lung interstitium. We concluded that aspiration of brain tissue from the amniotic fluid in neural tube defect cases may happen but it is infrequent and heterotopia was not observed.O objetivo do estudo foi identificar qual a freqüência de aspiração de tecido cerebral e a existência de heterotopia nos pulmões de casos humanos de defeito de fechamento do tubo neural através da reação imuno-histoquímica para proteína fibrilar glial ácida (GFAP em cortes histológicos de todos os lobos de ambos os pulmões de 22 casos de fetos e neonatos com defeito de fechamento do tubo neural. Havia 15 casos femininos (68,2% e 7 masculinos (31,8%, com idade gestacional variando de 18 a 40 semanas (média= 31,8, sendo natimortos e neomortos 10 (45,5% cada e 2 (9,1% abortos. Os diagnósticos foram: Craniorraquisquise (9 casos, 40,9%, anencefalia (8 casos, 36,4%, encefalocele occipital rota e raquisquise (2 casos, 9,1% e 1 (4,5%caso de seqüência de disruptura amniótica precoce. Somente 1 caso (4,5% apresentou células positivas dentro de bronquíolos e alvéolos em meio a células epiteliais

  13. Evidence for increased SOX3 dosage as a risk factor for X-linked hypopituitarism and neural tube defects.

    Science.gov (United States)

    Bauters, Marijke; Frints, Suzanna G; Van Esch, Hilde; Spruijt, Liesbeth; Baldewijns, Marcella M; de Die-Smulders, Christine E M; Fryns, Jean-Pierre; Marynen, Peter; Froyen, Guy

    2014-08-01

    Genomic duplications of varying lengths at Xq26-q27 involving SOX3 have been described in families with X-linked hypopituitarism. Using array-CGH we detected a 1.1 Mb microduplication at Xq27 in a large family with three males suffering from X-linked hypopituitarism. The duplication was mapped from 138.7 to 139.8 Mb, harboring only two annotated genes, SOX3 and ATP11C, and was shown to be a direct tandem copy number gain. Unexpectedly, the microduplication did not fully segregate with the disease in this family suggesting that SOX3 duplications have variable penetrance for X-linked hypopituitarism. In the same family, a female fetus presenting with a neural tube defect was also shown to carry the SOX3 copy number gain. Since we also demonstrated increased SOX3 mRNA levels in amnion cells derived from an unrelated t(X;22)(q27;q11) female fetus with spina bifida, we propose that increased levels of SOX3 could be a risk factor for neural tube defects. © 2014 Wiley Periodicals, Inc.

  14. 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.

  15. Theory of Neural Information Processing Systems

    International Nuclear Information System (INIS)

    Galla, Tobias

    2006-01-01

    It is difficult not to be amazed by the ability of the human brain to process, to structure and to memorize information. Even by the toughest standards the behaviour of this network of about 10 11 neurons qualifies as complex, and both the scientific community and the public take great interest in the growing field of neuroscience. The scientific endeavour to learn more about the function of the brain as an information processing system is here a truly interdisciplinary one, with important contributions from biology, computer science, physics, engineering and mathematics as the authors quite rightly point out in the introduction of their book. The role of the theoretical disciplines here is to provide mathematical models of information processing systems and the tools to study them. These models and tools are at the centre of the material covered in the book by Coolen, Kuehn and Sollich. The book is divided into five parts, providing basic introductory material on neural network models as well as the details of advanced techniques to study them. A mathematical appendix complements the main text. The range of topics is extremely broad, still the presentation is concise and the book well arranged. To stress the breadth of the book let me just mention a few keywords here: the material ranges from the basics of perceptrons and recurrent network architectures to more advanced aspects such as Bayesian learning and support vector machines; Shannon's theory of information and the definition of entropy are discussed, and a chapter on Amari's information geometry is not missing either. Finally the statistical mechanics chapters cover Gardner theory and the replica analysis of the Hopfield model, not without being preceded by a brief introduction of the basic concepts of equilibrium statistical physics. The book also contains a part on effective theories of the macroscopic dynamics of neural networks. Many dynamical aspects of neural networks are usually hard to find in the

  16. Risk factors, organ weight deviation and associated anomalies in neural tube defects: A prospective fetal and perinatal autopsy series

    Directory of Open Access Journals (Sweden)

    Asaranti Kar

    2015-01-01

    Full Text Available Introduction: Neural tube defects (NTD are a group of serious birth defects occurring due to defective closure of neural tube during embryonic development. It comprises of anencephaly, encephalocele and spina bifida. We conducted this prospective fetal autopsy series to study the rate and distribution of NTD, analyze the reproductive factors and risk factors, note any associated anomalies and evaluate the organ weights and their deviation from normal. Materials and Methods: This was a prospective study done over a period of 6 years from August, 2007 to July, 2013. All cases of NTDs delivered as abortion, still born and live born were included. The reproductive and risk factors like age, parity, multiple births, previous miscarriage, obesity, diabetes mellitus, socioeconomic status and use of folic acid during pregnancy were collected.Autopsy was performed according to Virchow′s technique. Detail external and internal examination were carried out to detect any associated anomalies. Gross and microscopic examination of organs were done. Results: Out of 210 cases of fetal and perinatal autopsy done, 72 (34.28% had NTD constituting 49 cases of anencephaly, 16 spina bifida and 7 cases of encephalocele. The mothers in these cases predominantly were within 25-29 years (P = 0.02 and primy (P = 0.01. Female sex was more commonly affected than males (M:F = 25:47, P = 0.0005 There was no history of folate use in majority of cases. Organ weight deviations were >2 standard deviation low in most of the cases. Most common associated anomalies were adrenal hypoplasia and thymic hyperplasia. Conclusion: The authors have made an attempt to study NTD cases in respect to maternal reproductive and risk factors and their association with NTD along with the organ weight deviation and associated anomalies. This so far in our knowledge is an innovative study which was not found in literature even after extensive search.

  17. A targeted sequencing panel identifies rare damaging variants in multiple genes in the cranial neural tube defect, anencephaly.

    Science.gov (United States)

    Ishida, M; Cullup, T; Boustred, C; James, C; Docker, J; English, C; Lench, N; Copp, A J; Moore, G E; Greene, N D E; Stanier, P

    2018-04-01

    Neural tube defects (NTDs) affecting the brain (anencephaly) are lethal before or at birth, whereas lower spinal defects (spina bifida) may lead to lifelong neurological handicap. Collectively, NTDs rank among the most common birth defects worldwide. This study focuses on anencephaly, which despite having a similar frequency to spina bifida and being the most common type of NTD observed in mouse models, has had more limited inclusion in genetic studies. A genetic influence is strongly implicated in determining risk of NTDs and a molecular diagnosis is of fundamental importance to families both in terms of understanding the origin of the condition and for managing future pregnancies. Here we used a custom panel of 191 NTD candidate genes to screen 90 patients with cranial NTDs (n = 85 anencephaly and n = 5 craniorachischisis) with a targeted exome sequencing platform. After filtering and comparing to our in-house control exome database (N = 509), we identified 397 rare variants (minor allele frequency, MAF < 1%), 21 of which were previously unreported and predicted damaging. This included 1 frameshift (PDGFRA), 2 stop-gained (MAT1A; NOS2) and 18 missense variations. Together with evidence for oligogenic inheritance, this study provides new information on the possible genetic causation of anencephaly. © 2017 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Inositol- and folate-resistant neural tube defects in mice lacking the epithelial-specific factor Grhl-3.

    Science.gov (United States)

    Ting, Stephen B; Wilanowski, Tomasz; Auden, Alana; Hall, Mark; Voss, Anne K; Thomas, Tim; Parekh, Vishwas; Cunningham, John M; Jane, Stephen M

    2003-12-01

    The neural tube defects (NTDs) spina bifida and anencephaly are widely prevalent severe birth defects. The mouse mutant curly tail (ct/ct) has served as a model of NTDs for 50 years, even though the responsible genetic defect remained unrecognized. Here we show by gene targeting, mapping and genetic complementation studies that a mouse homolog of the Drosophila grainyhead (grh) gene, grainyhead-like-3 (Grhl3), is a compelling candidate for the gene underlying the curly tail phenotype. The NTDs in Grhl3-null mice are more severe than those in the curly tail strain, as the Grhl3 alleles in ct/ct mice are hypomorphic. Spina bifida in ct/ct mice is folate resistant, but its incidence can be markedly reduced by maternal inositol supplementation periconceptually. The NTDs in Grhl3-/- embryos are also folate resistant, but unlike those in ct/ct mice, they are resistant to inositol. These findings suggest that residual Grhl3 expression in ct/ct mice may be required for inositol rescue of folate-resistant NTDs.

  19. Neural Network for Optimization of Existing Control Systems

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1995-01-01

    The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....

  20. Folato, vitamina B12 e ferritina sérica e defeitos do tubo neural Folate, vitamin B12, serum ferritin and defects of the neural tube

    Directory of Open Access Journals (Sweden)

    Gizele Thame

    1998-09-01

    Full Text Available Objetivo: verificar os níveis de folatos, vitamina B12 e ferritina em pacientes cujos fetos apresentaram defeitos de tubo neural (DTN. O folato sangüíneo e a vitamina B12 atuam como cofatores para as enzimas envolvidas na biossíntese do DNA. A interrupção deste processo pode impedir o fechamento do tubo neural. A suplementação vitamínica contendo folato pode reduzir as taxas de ocorrência de defeitos de tubo neural, embora exista a preocupação de que esta prevenção possa mascarar a deficiência de vitamina B12. Métodos: dosagens de vitamina B12 e ferritina pelo método de enzimaimunoensaio com micropartículas e a dosagens de ácido fólico pelo método de captura iônica (IMx ABBOTT. Resultados: a porcentagem de gestantes com deficiência de vitamina B12 (níveis séricos Purpose: to determine folate, vitamin B12 and ferritin levels in patients whose fetuses presented neural-tube defects (NTD. Blood folate and vitamin B12 act as cofactors of enzymes involved in DNA biosynthesis. Interruption of this process may block neural-tube closing. Vitamin supplementation with folate may reduce occurrence rates and recurrence of NTD, although there is concern about the fact that this prevention may mask vitamin B12 deficiency. Methods: vitamin B12 and ferritin determinations by enzyme immunoassay with microparticles and folic acid determination using the ion capture method (IMx ABBOTT. Results: the percentage of pregnant women with vitamin B12 deficirncy (serum levels < 150 pg/ml was 11.8%. There was no case of folate deficiency (serum levels < 3.0 ng/ml and prevalence of pregnant women with iron store deficiency was 47.1% (serum levels < ng/mg. Conclusions: occording to the results obtained in this study (prevalence of 11.8% of vitamin B12 and 0% of folate deficient pregnant women we suggest that supplementation should be administered after serum vitamin B12 determination.

  1. The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

    Directory of Open Access Journals (Sweden)

    Wilfredo Blanco

    2017-09-01

    Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

  2. Imaging findings in patients with ventral dural defects and herniation of neural tissue

    International Nuclear Information System (INIS)

    Baur, A.; Staebler, A.; Reiser, M.; Psenner, K.; Hamburger, C.

    1997-01-01

    The aim of this paper is to describe clinical and imaging findings in three patients with ventral dural defects and herniation of the spinal cord or cauda equina. The literature is reviewed and the clinical, radiological and operative findings are compared. Three patients with ventral dural defects of different etiologies are presented. One patient gave a longstanding history of ankylosing spondylitis, the second patient presents 37 years after spinal trauma, and the third patient presents with spontaneous spinal cord herniation. All patients had typically slowly progressive neurological symptoms with multiple hospitalizations until diagnosis was made. Characteristic findings in postmyelographic CT included a ventral or ventrolateral displacement with deformation of the spinal cord or the cauda equina. Sagittal MRI showed this abrupt and localized anterior deviation of the spinal cord or the cauda equina to the posterior portions of a vertebral body with or without a bony vertebral defect optimally. Additionally, due to the ventral displacement of the spinal cord, the dorsal subarachnoid space was relatively enlarged without evidence of an arachnoid cyst, in all patients. Magnetic resonance imaging and postmyelographic CT can diagnose ventral dural defects with spinal cord herniation or nerve root entrapment. Dural defects must be considered in the presence of neurological symptoms in cases of longstanding ankylosing spondylitis, late sequelae of fractures of vertebral bodies, and without history of spinal trauma or surgery. (orig.). With 3 figs

  3. Detecting Topological Defect Dark Matter Using Coherent Laser Ranging System

    Science.gov (United States)

    Yang, Wanpeng; Leng, Jianxiao; Zhang, Shuangyou; Zhao, Jianye

    2016-01-01

    In the last few decades, optical frequency combs with high intensity, broad optical bandwidth, and directly traceable discrete wavelengths have triggered rapid developments in distance metrology. However, optical frequency combs to date have been limited to determine the absolute distance to an object (such as satellite missions). We propose a scheme for the detection of topological defect dark matter using a coherent laser ranging system composed of dual-combs and an optical clock via nongravitational signatures. The dark matter field, which comprises a defect, may interact with standard model particles, including quarks and photons, resulting in the alteration of their masses. Thus, a topological defect may function as a dielectric material with a distinctive frequency-depend index of refraction, which would cause the time delay of a periodic extraterrestrial or terrestrial light. When a topological defect passes through the Earth, the optical path of long-distance vacuum path is altered, this change in optical path can be detected through the coherent laser ranging system. Compared to continuous wavelength(cw) laser interferometry methods, dual-comb interferometry in our scheme excludes systematic misjudgement by measuring the absolute optical path length. PMID:27389642

  4. Dificultades en los métodos de estudio de exposiciones ambientales y defectos del tubo neural Methodological challenges to assess environmental exposures related to neural tube defects

    Directory of Open Access Journals (Sweden)

    Víctor Hugo Borja-Aburto

    1999-11-01

    susceptibilidad genética.Objective. To discuss the attitudes in the assessment of environmental exposures as risk factors associated with neural tube defects, and to present the main risk factors studied to date. Results. Environmental exposures have been suggested to have a roll in the genesis of birth defects. However, studies conducted in human populations have found difficulties in the design and conduction to show such an association for neural tube defects (anencephaly, espina bifida and encefalocele because of problems raised from: a the frequency measures used to compare time trends and communities, b the classification of heterogeneous malformations, c the inclusion of maternal, paternal and fetal factors as an integrated process and, d the assessment of environmental exposures. Conclusions. Hypothetically both maternal and paternal environmental exposures can produce damage before and after conception by direct action on the embryo and the fetus-placenta complex. Therefore, in the assessment of environmental exposures we need to take into account: a both paternal and maternal exposures; b the critical exposure period, three months before conception for paternal exposures and one month around the conceptional period for maternal exposures; c quantitatively evaluate environmental exposures when possible, avoiding a dichotomous classification; d the use of biological markers of exposure is highly recommended as well as markers of genetic susceptibility.

  5. Disostose espôndilo-costal associada a defeitos de fechamento do tubo neural Spondylocostal dysostosis associated with neural tube defects

    Directory of Open Access Journals (Sweden)

    Rafael Fabiano M. Rosa

    2009-09-01

    Full Text Available OBJETIVO: Salientar a relação dos defeitos de fechamento do tubo neural com a disostose espôndilo-costal (DEC por meio da descrição de três pacientes. DESCRIÇÃO DOS CASOS: Paciente 1: menina branca, 22 meses, nascida com mielomeningocele lombar. Na avaliação, apresentava hipotonia, baixa estatura, dolicocefalia, fendas palpebrais oblíquas para cima, pregas epicânticas e tronco curto com tórax assimétrico. A avaliação radiográfica revelou hemivértebras múltiplas, vértebras em borboleta e fusão e ausência de algumas costelas. Paciente 2: menina branca, 22 meses, com moderado atraso do desenvolvimento neuropsicomotor, baixa estatura, olhos profundos, pregas epicânticas, pescoço e tronco curtos com assimetria do tórax, abdome protruso, hemangioma plano na altura da transição lombossacra e fosseta sacral profunda no dorso. A avaliação radiográfica identificou hemivértebras, fusão incompleta de vértebras e vértebras em borboleta, malformações de costelas e espinha bífida oculta em L5/S1. Paciente 3: menina branca, 9 dias de vida, com fendas palpebrais oblíquas para cima, ponte nasal alargada, orelhas baixo implantadas e rotadas posteriormente, tronco curto, tórax assimétrico e meningocele tóraco-lombar. A avaliação radiográfica evidenciou hemivértebras, malformação e ausência de algumas costelas e agenesia diafragmática à esquerda. A tomografia computadorizada de encéfalo mostrou estenose de aqueduto. COMENTÁRIOS: Vários defeitos de fechamento do tubo neural, de espinha bífida oculta a grandes mielomeningoceles, são observados em pacientes com DEC, indicando que tais pacientes devem ser cuidadosamente avaliados quanto à possível presença desses defeitos.OBJECTIVE: To highlight the relationship between neural tube defects and spondylocostal dysostosis (SCD through the description of three patients. CASES DESCRIPTION: Patient 1: white girl, 22 months old, born with a lumbar meningomyelocele. At

  6. High glucose-induced oxidative stress represses sirtuin deacetylase expression and increases histone acetylation leading to neural tube defects.

    Science.gov (United States)

    Yu, Jingwen; Wu, Yanqing; Yang, Peixin

    2016-05-01

    Aberrant epigenetic modifications are implicated in maternal diabetes-induced neural tube defects (NTDs). Because cellular stress plays a causal role in diabetic embryopathy, we investigated the possible role of the stress-resistant sirtuin (SIRT) family histone deacetylases. Among the seven sirtuins (SIRT1-7), pre-gestational maternal diabetes in vivo or high glucose in vitro significantly reduced the expression of SIRT 2 and SIRT6 in the embryo or neural stem cells, respectively. The down-regulation of SIRT2 and SIRT6 was reversed by superoxide dismutase 1 (SOD1) over-expression in the in vivo mouse model of diabetic embryopathy and the SOD mimetic, tempol and cell permeable SOD, PEGSOD in neural stem cell cultures. 2,3-dimethoxy-1,4-naphthoquinone (DMNQ), a superoxide generating agent, mimicked high glucose-suppressed SIRT2 and SIRT6 expression. The acetylation of histone 3 at lysine residues 56 (H3K56), H3K14, H3K9, and H3K27, putative substrates of SIRT2 and SIRT6, was increased by maternal diabetes in vivo or high glucose in vitro, and these increases were blocked by SOD1 over-expression or tempol treatment. SIRT2 or SIRT6 over-expression abrogated high glucose-suppressed SIRT2 or SIRT6 expression, and prevented the increase in acetylation of their histone substrates. The potent sirtuin activator (SRT1720) blocked high glucose-increased histone acetylation and NTD formation, whereas the combination of a pharmacological SIRT2 inhibitor and a pan SIRT inhibitor mimicked the effect of high glucose on increased histone acetylation and NTD induction. Thus, diabetes in vivo or high glucose in vitro suppresses SIRT2 and SIRT6 expression through oxidative stress, and sirtuin down-regulation-induced histone acetylation may be involved in diabetes-induced NTDs. The mechanism underlying pre-gestational diabetes-induced neural tube defects (NTDs) is still elusive. Our study unravels a new epigenetic mechanism in which maternal diabetes-induced oxidative stress represses

  7. The ctenophore genome and the evolutionary origins of neural systems

    NARCIS (Netherlands)

    Moroz, Leonid L.; Kocot, Kevin M.; Citarella, Mathew R.; Dosung, Sohn; Norekian, Tigran P.; Povolotskaya, Inna S.; Grigorenko, Anastasia P.; Dailey, Christopher; Berezikov, Eugene; Buckley, Katherine M.; Ptitsyn, Andrey; Reshetov, Denis; Mukherjee, Krishanu; Moroz, Tatiana P.; Bobkova, Yelena; Yu, Fahong; Kapitonov, Vladimir V.; Jurka, Jerzy; Bobkov, Yuri V.; Swore, Joshua J.; Girardo, David O.; Fodor, Alexander; Gusev, Fedor; Sanford, Rachel; Bruders, Rebecca; Kittler, Ellen; Mills, Claudia E.; Rast, Jonathan P.; Derelle, Romain; Solovyev, Victor V.; Kondrashov, Fyodor A.; Swalla, Billie J.; Sweedler, Jonathan V.; Rogaev, Evgeny I.; Halanych, Kenneth M.; Kohn, Andrea B.

    2014-01-01

    The origins of neural systems remain unresolved. In contrast to other basal metazoans, ctenophores (comb jellies) have both complex nervous and mesoderm-derived muscular systems. These holoplanktonic predators also have sophisticated ciliated locomotion, behaviour and distinct development. Here we

  8. Spiking Neural P Systems with Communication on Request.

    Science.gov (United States)

    Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

    2017-12-01

    Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

  9. From disability to ability: comprehensive rehabilitation providing a holistic functional improvement in a child with neglected neural tube defect.

    Science.gov (United States)

    Mishra, Kriti; Siddharth, V

    2017-09-25

    Neural Tube defects are one of the most common congenital disorders, presenting in a paediatric rehabilitation set-up. With its wide spectrum of clinical presentation and possible complications, the condition can significantly impact an individual's functional capacity and quality of life. The condition also affects the family of the child leaving them with a lifelong impairment to cope up with. Through this 16-year-old child, we shed light on the effects of providing rehabilitation, even at a later stage and its benefits. We also get a glimpse of difficulties in availing rehabilitation services in developing countries and the need to reach out many more neglected children like him with good functional abilities. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  10. Application of neural networks to software quality modeling of a very large telecommunications system.

    Science.gov (United States)

    Khoshgoftaar, T M; Allen, E B; Hudepohl, J P; Aud, S J

    1997-01-01

    Society relies on telecommunications to such an extent that telecommunications software must have high reliability. Enhanced measurement for early risk assessment of latent defects (EMERALD) is a joint project of Nortel and Bell Canada for improving the reliability of telecommunications software products. This paper reports a case study of neural-network modeling techniques developed for the EMERALD system. The resulting neural network is currently in the prototype testing phase at Nortel. Neural-network models can be used to identify fault-prone modules for extra attention early in development, and thus reduce the risk of operational problems with those modules. We modeled a subset of modules representing over seven million lines of code from a very large telecommunications software system. The set consisted of those modules reused with changes from the previous release. The dependent variable was membership in the class of fault-prone modules. The independent variables were principal components of nine measures of software design attributes. We compared the neural-network model with a nonparametric discriminant model and found the neural-network model had better predictive accuracy.

  11. Bifurcation and chaos in neural excitable system

    International Nuclear Information System (INIS)

    Jing Zhujun; Yang Jianping; Feng Wei

    2006-01-01

    In this paper, we investigate the dynamical behaviors of neural excitable system without periodic external current (proposed by Chialvo [Generic excitable dynamics on a two-dimensional map. Chaos, Solitons and Fractals 1995;5(3-4):461-79] and with periodic external current as system's parameters vary. The existence and stability of three fixed points, bifurcation of fixed points, the conditions of existences of fold bifurcation, flip bifurcation and Hopf bifurcation are derived by using bifurcation theory and center manifold theorem. The chaotic existence in the sense of Marotto's definition of chaos is proved. We then give the numerical simulated results (using bifurcation diagrams, computations of Maximum Lyapunov exponent and phase portraits), which not only show the consistence with the analytic results but also display new and interesting dynamical behaviors, including the complete period-doubling and inverse period-doubling bifurcation, symmetry period-doubling bifurcations of period-3 orbit, simultaneous occurrence of two different routes (invariant cycle and period-doubling bifurcations) to chaos for a given bifurcation parameter, sudden disappearance of chaos at one critical point, a great abundance of period windows (period 2 to 10, 12, 19, 20 orbits, and so on) in transient chaotic regions with interior crises, strange chaotic attractors and strange non-chaotic attractor. In particular, the parameter k plays a important role in the system, which can leave the chaotic behavior or the quasi-periodic behavior to period-1 orbit as k varies, and it can be considered as an control strategy of chaos by adjusting the parameter k. Combining the existing results in [Generic excitable dynamics on a two-dimensional map. Chaos, Solitons and Fractals 1995;5(3-4):461-79] with the new results reported in this paper, a more complete description of the system is now obtained

  12. Differentiation defect in neural crest-derived smooth muscle cells in patients with aortopathy associated with bicuspid aortic valves

    Directory of Open Access Journals (Sweden)

    Jiao Jiao

    2016-08-01

    Full Text Available Individuals with bicuspid aortic valves (BAV are at a higher risk of developing thoracic aortic aneurysms (TAA than patients with trileaflet aortic valves (TAV. The aneurysms associated with BAV most commonly involve the ascending aorta and spare the descending aorta. Smooth muscle cells (SMCs in the ascending and descending aorta arise from neural crest (NC and paraxial mesoderm (PM, respectively. We hypothesized defective differentiation of the neural crest stem cells (NCSCs-derived SMCs but not paraxial mesoderm cells (PMCs-derived SMCs contributes to the aortopathy associated with BAV. When induced pluripotent stem cells (iPSCs from BAV/TAA patients were differentiated into NCSC-derived SMCs, these cells demonstrated significantly decreased expression of marker of SMC differentiation (MYH11 and impaired contraction compared to normal control. In contrast, the PMC-derived SMCs were similar to control cells in these aspects. The NCSC-SMCs from the BAV/TAA also showed decreased TGF-β signaling based on phosphorylation of SMAD2, and increased mTOR signaling. Inhibition of mTOR pathway using rapamycin rescued the aberrant differentiation. Our data demonstrates that decreased differentiation and contraction of patient's NCSC-derived SMCs may contribute to that aortopathy associated with BAV.

  13. INCREASED MATERNAL SERUM ALPHA-FETOPROTEIN AND HUMAN CHORIONIC-GONADOTROPIN IN COMPROMISED PREGNANCIES OTHER THAN FOR NEURAL-TUBE DEFECTS OR DOWN-SYNDROME

    NARCIS (Netherlands)

    BEEKHUIS, [No Value; VANLITH, JMM; DEWOLF, BTHM; MANTINGH, A

    Intrauterine fetal death occurred in four women who were 'screen-positive' in a screening programme for neural tube defects (NTDs) and Down syndrome (DS). These women had very high levels of maternal serum alpha-fetoprotein (MSAFP) and maternal serum human chorionic gonadotropin (MShCG). Therefore,

  14. Mortalidad por defectos del tubo neural en México, 1980-1997 Mortality due to neural tube defects in Mexico, 1980-1997

    Directory of Open Access Journals (Sweden)

    José A Ramírez-Espitia

    2003-10-01

    Full Text Available OBJETIVO: Describir la mortalidad en México por defectos del tubo neural, durante el periodo 1980-1997. MATERIAL Y MÉTODOS: Las tasas anuales de mortalidad estatales y nacionales, por defectos del tubo neural, se calcularon por 10 000 nacidos vivos. La tendencia temporal fue evaluada por el porcentaje de cambio anual obtenido mediante un modelo de regresión de Poisson. Se calculó la razón de mortalidad, tomando la media nacional como referencia. Las tasas y las razones se representaron gráficamente en mapas. RESULTADOS: Durante el periodo la tasa bruta de mortalidad por defectos del tubo neural fue de 5.8 por 10 000 nacidos vivos. La anencefalia fue el tipo de defecto más frecuente (37.7%, seguida de la espina bífida sin hidrocefalia (31.6%. La tendencia nacional de la mortalidad por defectos del tubo neural fue ascendente entre 1980 y 1990 (porcentaje de cambio anual 7.5 IC 95% 6.5, 8.6 y descendente entre 1990-1997 (porcentaje de cambio anual -2.3 IC 95% -3.6, -0.9. CONCLUSIONES: Las altas tasas de mortalidad por defectos del tubo neural fueron debidas principalmente a la elevada frecuencia de las anencefalias. El incremento observado parece no ser sólo atribuible a cuestiones puramente diagnósticas o de mejora en los registros. La influencia de factores asociados a estos defectos, como determinados polimorfismos genéticos, la deficiencia de ácido fólico, la obesidad materna, la exposición laboral a plaguicidas y la pobreza deberán evaluarse mediante estudios específicos.OBJECTIVE: To describe the mortality due to neural tube defects (NTD in Mexico for the 1980-1997 period. MATERIAL AND METHODS: The annual NTD mortality rates per 10000 liveborn infants were calculated by state and for the country. The time trend was evaluated with the annual percent change (APC obtained using a Poisson regression model. The NTD mortality ratio was calculated using the average national rate as reference. NTD mortality rates and ratios were

  15. Short-term synaptic plasticity and heterogeneity in neural systems

    Science.gov (United States)

    Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

    2013-01-01

    We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

  16. Running rescues defective adult neurogenesis by shortening the length of the cell cycle of neural stem and progenitor cells.

    Science.gov (United States)

    Farioli-Vecchioli, Stefano; Mattera, Andrea; Micheli, Laura; Ceccarelli, Manuela; Leonardi, Luca; Saraulli, Daniele; Costanzi, Marco; Cestari, Vincenzo; Rouault, Jean-Pierre; Tirone, Felice

    2014-07-01

    Physical exercise increases the generation of new neurons in adult neurogenesis. However, only few studies have investigated the beneficial effects of physical exercise in paradigms of impaired neurogenesis. Here, we demonstrate that running fully reverses the deficient adult neurogenesis within the hippocampus and subventricular zone of the lateral ventricle, observed in mice lacking the antiproliferative gene Btg1. We also evaluated for the first time how running influences the cell cycle kinetics of stem and precursor subpopulations of wild-type and Btg1-null mice, using a new method to determine the cell cycle length. Our data show that in wild-type mice running leads to a cell cycle shortening only of NeuroD1-positive progenitor cells. In contrast, in Btg1-null mice, physical exercise fully reactivates the defective hippocampal neurogenesis, by shortening the S-phase length and the overall cell cycle duration of both neural stem (glial fibrillary acidic protein(+) and Sox2(+)) and progenitor (NeuroD1(+)) cells. These events are sufficient and necessary to reactivate the hyperproliferation observed in Btg1-null early-postnatal mice and to expand the pool of adult neural stem and progenitor cells. Such a sustained increase of cell proliferation in Btg1-null mice after running provides a long-lasting increment of proliferation, differentiation, and production of newborn neurons, which rescues the impaired pattern separation previously identified in Btg1-null mice. This study shows that running positively affects the cell cycle kinetics of specific subpopulations of newly generated neurons and suggests that the plasticity of neural stem cells without cell cycle inhibitory control is reactivated by running, with implications for the long-term modulation of neurogenesis. © 2014 AlphaMed Press.

  17. Evolution of posterior fossa and brain morphology after in utero repair of open neural tube defects assessed by MRI

    Energy Technology Data Exchange (ETDEWEB)

    Rethmann, Christin; Scheer, Ianina; Kellenberger, Christian Johannes [University Children' s Hospital Zurich, Department of Diagnostic Imaging, Zurich (Switzerland); University of Zurich, The Zurich Center for Fetal Diagnosis and Therapy, Zurich (Switzerland); Children' s Research Center (CRC), Zurich (Switzerland); Meuli, Martin; Mazzone, Luca; Moehrlen, Ueli [University of Zurich, The Zurich Center for Fetal Diagnosis and Therapy, Zurich (Switzerland); Children' s Research Center (CRC), Zurich (Switzerland); University Children' s Hospital Zurich, Department of Pediatric Surgery, Zurich (Switzerland)

    2017-11-15

    To describe characteristics of foetuses undergoing in utero repair of open neural tube defects (ONTD) and assess postoperative evolution of posterior fossa and brain morphology. Analysis of pre- and postoperative foetal as well as neonatal MRI of 27 foetuses who underwent in utero repair of ONTD. Type and level of ONTD, hindbrain configuration, posterior fossa and liquor space dimensions, and detection of associated findings were compared between MRI studies and to age-matched controls. Level of bony spinal defect was defined with exactness of ± one vertebral body. Of surgically confirmed 18 myelomeningoceles (MMC) and 9 myeloschisis (MS), 3 MMC were misdiagnosed as MS due to non-visualisation of a flat membrane on MRI. Hindbrain herniation was more severe in MS than MMC (p < 0.001). After repair, hindbrain herniation resolved in 25/27 cases at 4 weeks and liquor spaces increased. While posterior fossa remained small (p < 0.001), its configuration normalised. Lateral ventricle diameter indexed to cerebral width decreased in 48% and increased in 12% of cases, implying a low rate of progressive obstructive hydrocephalus. Neonatally evident subependymal heterotopias were detected in 33% at preoperative and 50% at postoperative foetal MRI. MRI demonstrates change of Chiari malformation type II (CM-II) features. (orig.)

  18. Evolution of posterior fossa and brain morphology after in utero repair of open neural tube defects assessed by MRI

    International Nuclear Information System (INIS)

    Rethmann, Christin; Scheer, Ianina; Kellenberger, Christian Johannes; Meuli, Martin; Mazzone, Luca; Moehrlen, Ueli

    2017-01-01

    To describe characteristics of foetuses undergoing in utero repair of open neural tube defects (ONTD) and assess postoperative evolution of posterior fossa and brain morphology. Analysis of pre- and postoperative foetal as well as neonatal MRI of 27 foetuses who underwent in utero repair of ONTD. Type and level of ONTD, hindbrain configuration, posterior fossa and liquor space dimensions, and detection of associated findings were compared between MRI studies and to age-matched controls. Level of bony spinal defect was defined with exactness of ± one vertebral body. Of surgically confirmed 18 myelomeningoceles (MMC) and 9 myeloschisis (MS), 3 MMC were misdiagnosed as MS due to non-visualisation of a flat membrane on MRI. Hindbrain herniation was more severe in MS than MMC (p < 0.001). After repair, hindbrain herniation resolved in 25/27 cases at 4 weeks and liquor spaces increased. While posterior fossa remained small (p < 0.001), its configuration normalised. Lateral ventricle diameter indexed to cerebral width decreased in 48% and increased in 12% of cases, implying a low rate of progressive obstructive hydrocephalus. Neonatally evident subependymal heterotopias were detected in 33% at preoperative and 50% at postoperative foetal MRI. MRI demonstrates change of Chiari malformation type II (CM-II) features. (orig.)

  19. Developing effective campaign messages to prevent neural tube defects: a qualitative assessment of women's reactions to advertising concepts.

    Science.gov (United States)

    Massi Lindsey, Lisa L; Silk, Kami J; Von Friederichs-Fitzwater, Marlene M; Hamner, Heather C; Prue, Christine E; Boster, Franklin J

    2009-03-01

    The incidence of neural tube defects (NTDs), serious birth defects of the brain and spine that affect approximately 3,000 pregnancies in the United States each year, can be reduced by 50-70% with daily periconceptional consumption of the B vitamin folic acid. Two studies were designed to assess college women's reactions to and perceptions of potential campaign advertising concepts derived from preproduction formative research to increase folic acid consumption through the use of a daily multivitamin. Study one assessed draft advertising concepts in eight focus groups (N = 71) composed of college-enrolled women in four cities geographically dispersed across the United States. Based on study one results, the concepts were revised and reassessed in study two with a different sample (eight focus groups; N = 73) of college women in the same four cities. Results indicated that participants generally responded favorably to concepts in each of the two studies, and provided insight into individual concepts to increase their overall appeal and effectiveness. The specific findings and implications of these results are discussed.

  20. Disruption of Smad4 in neural crest cells leads to mid-gestation death with pharyngeal arch, craniofacial and cardiac defects

    Science.gov (United States)

    Nie, Xuguang; Deng, Chu-xia; Wang, Qin; Jiao, Kai

    2008-01-01

    TGFβ/BMP signaling pathways are essential for normal development of neural crest cells (NCCs). Smad4 encodes the only common Smad protein in mammals, which is a critical nuclear mediator of TGFβ/BMP signaling. In this work, we sought to investigate the roles of Smad4 for development of NCCs. To overcome the early embryonic lethality of Smad4 null mice, we specifically disrupted Smad4 in NCCs using a Cre/loxP system. The mutant mice died at mid-gestation with defects in facial primordia, pharyngeal arches, outflow tract and cardiac ventricles. Further examination revealed that mutant embryos displayed severe molecular defects starting from E9.5. Expression of multiple genes, including Msx1, 2, Ap-2α, Pax3, and Sox9, which play critical roles for NCC development, was downregulated by NCC disruption of Smad4. Moreover, increased cell death was observed in pharyngeal arches from E10.5. However, the cell proliferation rate in these areas was not substantially altered. Taken together, these findings provide compelling genetic evidence that Smad4-mediated activities of TGFβ/BMP signals are essential for appropriate NCC development. PMID:18334251

  1. Mortality due to neural tube defects and risk factors in Hidalgo, Mexico

    OpenAIRE

    Muñoz-Juárez, Sergio; Vargas-Flores, Humberto; Hernández-Prado, Bernardo; López-Ríos, Olga; Ortiz-Espinosa, Rosa María

    2002-01-01

    Objetivo. Calcular el riesgo de muerte fetal secundaria a defectos del cierre del tubo neural y estimar factores asociados con este tipo de muertes en el estado de Hidalgo. Material y métodos. La información analizada en el año 2000 fue obtenida de los certificados de muerte fetal del periodo 1990-1995 en el estado de Hidalgo. Se utilizó un diseño de mortalidad proporcional, considerado como una variante del diseño de casos y controles. Los casos fueron aquellas muertes fetales secundarias a ...

  2. PWR system simulation and parameter estimation with neural networks

    International Nuclear Information System (INIS)

    Akkurt, Hatice; Colak, Uener

    2002-01-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within ±0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected

  3. PWR system simulation and parameter estimation with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Akkurt, Hatice; Colak, Uener E-mail: uc@nuke.hacettepe.edu.tr

    2002-11-01

    A detailed nonlinear model for a typical PWR system has been considered for the development of simulation software. Each component in the system has been represented by appropriate differential equations. The SCILAB software was used for solving nonlinear equations to simulate steady-state and transient operational conditions. Overall system has been constructed by connecting individual components to each other. The validity of models for individual components and overall system has been verified. The system response against given transients have been analyzed. A neural network has been utilized to estimate system parameters during transients. Different transients have been imposed in training and prediction stages with neural networks. Reactor power and system reactivity during the transient event have been predicted by the neural network. Results show that neural networks estimations are in good agreement with the calculated response of the reactor system. The maximum errors are within {+-}0.254% for power and between -0.146 and 0.353% for reactivity prediction cases. Steam generator parameters, pressure and water level, are also successfully predicted by the neural network employed in this study. The noise imposed on the input parameters of the neural network deteriorates the power estimation capability whereas the reactivity estimation capability is not significantly affected.

  4. Dopamine system: Manager of neural pathways

    Directory of Open Access Journals (Sweden)

    Simon eHong

    2013-12-01

    Full Text Available There are a growing number of roles that midbrain dopamine (DA neurons assume, such as, reward, aversion, alerting and vigor. Here I propose a theory that may be able to explain why the suggested functions of DA came about. It has been suggested that largely parallel cortico-basal ganglia-thalamo-cortico loops exist to control different aspects of behavior. I propose that (1 the midbrain DA system is organized in a similar manner, with different groups of DA neurons corresponding to these parallel neural pathways (NPs. The DA system can be viewed as the manager of these parallel NPs in that it recruits and activates only the task-relevant NPs when they are needed. It is likely that the functions of those NPs that have been consistently activated by the corresponding DA groups are facilitated. I also propose that (2 there are two levels of DA roles: the How and What roles. The How role is encoded in tonic and phasic DA neuron firing patterns and gives a directive to its target NP: how vigorously its function needs to be carried out. The tonic DA firing is to maintain a certain level of DA in the target NPs to support their expected behavioral and mental functions; it is only when a sudden unexpected boost or suppression of activity is required by the relevant target NP that DA neurons in the corresponding NP act in a phasic manner. The What role is the implementational aspect of the role of DA in the target NP, such as binding to D1 receptors to boost working memory. This What aspect of DA explains why DA seems to assume different functions depending on the region of the brain in which it is involved. In terms of the role of the lateral habenula (LHb, the LHb is expected to suppress maladaptive behaviors and mental processes by controlling the DA system. The demand-based smart management by the DA system may have given animals an edge in evolution with adaptive behaviors and a better survival rate in resource-scarce situations.

  5. Study on on-machine defects measuring system on high power laser optical elements

    Science.gov (United States)

    Luo, Chi; Shi, Feng; Lin, Zhifan; Zhang, Tong; Wang, Guilin

    2017-10-01

    The influence of surface defects on high power laser optical elements will cause some harm to the performances of imaging system, including the energy consumption and the damage of film layer. To further increase surface defects on high power laser optical element, on-machine defects measuring system was investigated. Firstly, the selection and design are completed by the working condition analysis of the on-machine defects detection system. By designing on processing algorithms to realize the classification recognition and evaluation of surface defects. The calibration experiment of the scratch was done by using the self-made standard alignment plate. Finally, the detection and evaluation of surface defects of large diameter semi-cylindrical silicon mirror are realized. The calibration results show that the size deviation is less than 4% that meet the precision requirement of the detection of the defects. Through the detection of images the on-machine defects detection system can realize the accurate identification of surface defects.

  6. Diagnostic Neural Network Systems for the Electronic Circuits

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2014-01-01

    Neural Networks is one of the most important artificial intelligent approaches for solving the diagnostic processes. This research concerns with uses the neural networks for diagnosis of the electronic circuits. Modern electronic systems contain both the analog and digital circuits. But, diagnosis of the analog circuits suffers from great complexity due to their nonlinearity. To overcome this problem, the proposed system introduces a diagnostic system that uses the neural network to diagnose both the digital and analog circuits. So, it can face the new requirements for the modern electronic systems. A fault dictionary method was implemented in the system. Experimental results are presented on three electronic systems. They are: artificial kidney, wireless network and personal computer systems. The proposed system has improved the performance of the diagnostic systems when applied for these practical cases

  7. Vein matching using artificial neural network in vein authentication systems

    Science.gov (United States)

    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.

  8. Efeito da fortificação alimentar com ácido fólico na prevalência de defeitos do tubo neural Efecto de la fortificación alimentaria con ácido fólico en la prevalencia de defectos del tubo neural Effects of folic acid fortification on the prevalence of neural tube defects

    Directory of Open Access Journals (Sweden)

    Sâmya Silva Pacheco

    2009-08-01

    defectos del cierre del tubo neural fueron definidos de acuerdo con el Códigos Internacional de Enfermedades- 10ª Revisión: anencefalia, encefalocele y espina bífida. Se compararon las prevalencias en los períodos anterior (2000 - 2004 y posterior (2005-2006 al período obligatorio de fortificación. Se analizó la tendencia temporal de las prevalencias trimestrales de defectos del cierre del tubo neural por las pruebas de Mann-Kendall y Sen's Slope. RESULTADOS: No se identificó tendencia de reducción en la ocurrencia del hecho (Teste de Mann-Kendall; p= 0,270; Sen's Slope = - 0,008 en el período estudiado. No hubo diferencia estadísticamente significativa entre las prevalencias de defectos de cierre del tubo neural en los períodos anterior y posterior a la fortificación de los alimentos con ácido fólico de acuerdo con las características maternas. CONCLUSIONES: A pesar de que no haya sido observada reducción de los defectos de cierre del tubo neural posterior al período obligatorio de fortificación de alimentos con ácido fólico, los resultados encontrados no permiten descartar el beneficio del mismo en la prevención de esta malformación. Son necesarios estudios evaluando mayor período y considerando el nivel de consumo de los productos fortificados por las mujeres en edad fértil.OBJECTIVE:To analyze the effect of folic acid-fortified foods on the prevalence of neural tube defects in live newborns. METHODS: Longitudinal study with newborns from the city of Recife, Northeastern Brazil, between 2000 and 2006. Data analyzed were obtained from the Sistema Nacional de Informações de Nascidos Vivos (National Information System on Live Births. Neural tube defects were defined in accordance with the International Classification of Diseases, 10th revision (ICD-10: anencephaly, encephalocele, and spina bifida. Prevalences from the periods before (2000-2004 and after (2005-2006 the mandatory fortification period were compared. Time trend of three

  9. Use of neural networks in the analysis of complex systems

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms) to some of the problems of complex engineering systems has the potential to enhance the safety reliability and operability of these systems. The work described here deals with complex systems or parts of such systems that can be isolated from the total system. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network. The neural networks are usually simulated on modern high-speed computers that carry out the calculations serially. However, it is possible to implement neural networks using specially designed microchips where the network calculations are truly carried out in parallel, thereby providing virtually instantaneous outputs for each set of inputs. Specific applications described include: Diagnostics: State of the Plant; Hybrid System for Transient Identification; Detection of Change of Mode in Complex Systems; Sensor Validation; Plant-Wide Monitoring; Monitoring of Performance and Efficiency; and Analysis of Vibrations. Although the specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

  10. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  11. Bio-inspired spiking neural network for nonlinear systems control.

    Science.gov (United States)

    Pérez, Javier; Cabrera, Juan A; Castillo, Juan J; Velasco, Juan M

    2018-08-01

    Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more complex computation. As demonstrated by biological organisms, they are a potentially good approach to designing controllers for highly nonlinear dynamic systems in which the performance of controllers developed by conventional techniques is not satisfactory or difficult to implement. SNN-based controllers exploit their ability for online learning and self-adaptation to evolve when transferred from simulations to the real world. SNN's inherent binary and temporary way of information codification facilitates their hardware implementation compared to analog neurons. Biological neural networks often require a lower number of neurons compared to other controllers based on artificial neural networks. In this work, these neuronal systems are imitated to perform the control of non-linear dynamic systems. For this purpose, a control structure based on spiking neural networks has been designed. Particular attention has been paid to optimizing the structure and size of the neural network. The proposed structure is able to control dynamic systems with a reduced number of neurons and connections. A supervised learning process using evolutionary algorithms has been carried out to perform controller training. The efficiency of the proposed network has been verified in two examples of dynamic systems control. Simulations show that the proposed control based on SNN exhibits superior performance compared to other approaches based on Neural Networks and SNNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Folic acid and pantothenic acid protection against valproic acid-induced neural tube defects in CD-1 mice

    Energy Technology Data Exchange (ETDEWEB)

    Dawson, Jennifer E [Department of Pharmacology and Toxicology and School of Environmental Studies, Queen' s University, Kingston, Ontario, K7L 3N6 (Canada); Raymond, Angela M [Department of Pharmacology and Toxicology and School of Environmental Studies, Queen' s University, Kingston, Ontario, K7L 3N6 (Canada); Winn, Louise M [Department of Pharmacology and Toxicology and School of Environmental Studies, Queen' s University, Kingston, Ontario, K7L 3N6 (Canada)

    2006-03-01

    In utero exposure to valproic acid (VPA) during pregnancy is associated with an increased risk of neural tube defects (NTDs). Although the mechanism by which VPA mediates these effects is unknown, VPA-initiated changes in embryonic protein levels have been implicated. The objectives of this study were to investigate the effect of in utero VPA exposure on embryonic protein levels of p53, NF-{kappa}B, Pim-1, c-Myb, Bax, and Bcl-2 in the CD-1 mouse. We also evaluated the protective effects of folic acid and pantothenic acid on VPA-induced NTDs and VPA-induced embryonic protein changes in this model. Pregnant CD-1 mice were administered a teratogenic dose of VPA prior to neural tube closure and embryonic protein levels were analyzed. In our study, VPA (400 mg/kg)-induced NTDs (24%) and VPA-exposed embryos with an NTD showed a 2-fold increase in p53, and 4-fold decreases in NF-{kappa}B, Pim-1, and c-Myb protein levels compared to their phenotypically normal littermates (P < 0.05). Additionally, VPA increased the ratio of embryonic Bax/Bcl-2 protein levels (P < 0.05). Pretreatment of pregnant dams with either folic acid or pantothenic acid prior to VPA significantly protected against VPA-induced NTDs (P < 0.05). Folic acid also reduced VPA-induced alterations in p53, NF-{kappa}B, Pim-1, c-Myb, and Bax/Bcl-2 protein levels, while pantothenic acid prevented VPA-induced alterations in NF-{kappa}B, Pim-1, and c-Myb. We hypothesize that folic acid and pantothenic acid protect CD-1 embryos from VPA-induced NTDs by independent, but not mutually exclusive mechanisms, both of which may be mediated by the prevention of VPA-induced alterations in proteins involved in neurulation.

  13. The Effects of Epidermal Neural Crest Stem Cells on Local Inflammation Microenvironment in the Defected Sciatic Nerve of Rats

    Directory of Open Access Journals (Sweden)

    Yue Li

    2017-05-01

    Full Text Available Cell-based therapy is a promising strategy for the repair of peripheral nerve injuries (PNIs. epidermal neural crest stems cells (EPI-NCSCs are thought to be important donor cells for repairing PNI in different animal models. Following PNI, inflammatory response is important to regulate the repair process. However, the effects of EPI-NCSCs on regulation of local inflammation microenviroment have not been investigated extensively. In the present study, these effects were studied by using 10 mm defected sciatic nerve, which was bridged with 15 mm artificial nerve composed of EPI-NCSCs, extracellular matrix (ECM and poly (lactide-co-glycolide (PLGA. Then the expression of pro- and anti-inflammatory cytokines, polarization of macrophages, regulation of fibroblasts and shwann cells (SCs were assessed by western blot, immunohistochemistry, immunofluorescence staining at 1, 3, 7 and 21 days after bridging. The structure and the function of the bridged nerve were determined by observation under light microscope and by examination of right lateral foot retraction time (LFRT, sciatic function index (SFI, gastrocnemius wet weight and electrophysiology at 9 weeks. After bridging with EPI-NCSCs, the expression of anti-inflammatory cytokines (IL-4 and IL-13 was increased, but decreased for pro-inflammatory cytokines (IL-6 and TNF-α compared to the control bridging, which was consistent with increase of M2 macrophages and decrease of M1 macrophages at 7 days after transplantation. Likewise, myelin-formed SCs were significantly increased, but decreased for the activated fibroblasts in their number at 21 days. The recovery of structure and function of nerve bridged with EPI-NCSCs was significantly superior to that of DMEM. These results indicated that EPI-NCSCs could be able to regulate and provide more suitable inflammation microenvironment for the repair of defected sciatic nerve.

  14. Automatic cross-sectioning and monitoring system locates defects in electronic devices

    Science.gov (United States)

    Jacobs, G.; Slaughter, B.

    1971-01-01

    System consists of motorized grinding and lapping apparatus, sample holder, and electronic control circuit. Low power microscope examines device to pinpoint location of circuit defect, and monitor displays output signal when defect is located exactly.

  15. Anomaly detection in an automated safeguards system using neural networks

    International Nuclear Information System (INIS)

    Whiteson, R.; Howell, J.A.

    1992-01-01

    An automated safeguards system must be able to detect an anomalous event, identify the nature of the event, and recommend a corrective action. Neural networks represent a new way of thinking about basic computational mechanisms for intelligent information processing. In this paper, we discuss the issues involved in applying a neural network model to the first step of this process: anomaly detection in materials accounting systems. We extend our previous model to a 3-tank problem and compare different neural network architectures and algorithms. We evaluate the computational difficulties in training neural networks and explore how certain design principles affect the problems. The issues involved in building a neural network architecture include how the information flows, how the network is trained, how the neurons in a network are connected, how the neurons process information, and how the connections between neurons are modified. Our approach is based on the demonstrated ability of neural networks to model complex, nonlinear, real-time processes. By modeling the normal behavior of the processes, we can predict how a system should be behaving and, therefore, detect when an abnormality occurs

  16. Development of an ultrasonic weld inspection system based on image processing and neural networks

    Science.gov (United States)

    Roca Barceló, Fernando; Jaén del Hierro, Pedro; Ribes Llario, Fran; Real Herráiz, Julia

    2018-04-01

    Several types of discontinuities and defects may be present on a weld, thus leading to a considerable reduction of its resistance. Therefore, ensuring a high welding quality and reliability has become a matter of key importance for many construction and industrial activities. Among the non-destructive weld testing and inspection techniques, the time-of-flight diffraction (TOFD) arises as a very safe (no ionising radiation), precise, reliable and versatile practice. However, this technique presents a relevant drawback, associated to the appearance of speckle noise that should be addressed. In this regard, this paper presents a new, intelligent and automatic method for weld inspection and analysis, based on TOFD, image processing and neural networks. The developed system is capable of detecting weld defects and imperfections with accuracy, and classify them into different categories.

  17. New design environment for defect detection in web inspection systems

    Science.gov (United States)

    Hajimowlana, S. Hossain; Muscedere, Roberto; Jullien, Graham A.; Roberts, James W.

    1997-09-01

    One of the aims of industrial machine vision is to develop computer and electronic systems destined to replace human vision in the process of quality control of industrial production. In this paper we discuss the development of a new design environment developed for real-time defect detection using reconfigurable FPGA and DSP processor mounted inside a DALSA programmable CCD camera. The FPGA is directly connected to the video data-stream and outputs data to a low bandwidth output bus. The system is targeted for web inspection but has the potential for broader application areas. We describe and show test results of the prototype system board, mounted inside a DALSA camera and discuss some of the algorithms currently simulated and implemented for web inspection applications.

  18. Representation of neural networks as Lotka-Volterra systems

    International Nuclear Information System (INIS)

    Moreau, Yves; Vandewalle, Joos; Louies, Stephane; Brenig, Leon

    1999-01-01

    We study changes of coordinates that allow the representation of the ordinary differential equations describing continuous-time recurrent neural networks into differential equations describing predator-prey models--also called Lotka-Volterra systems. We transform the equations for the neural network first into quasi-monomial form, where we express the vector field of the dynamical system as a linear combination of products of powers of the variables. In practice, this transformation is possible only if the activation function is the hyperbolic tangent or the logistic sigmoied. From this quasi-monomial form, we can directly transform the system further into Lotka-Volterra equations. The resulting Lotka-Volterra system is of higher dimension than the original system, but the behavior of its first variables is equivalent to the behavior of the original neural network

  19. Frecuencia de los defectos del tubo neural en Asturias: impacto del diagnóstico prenatal Prevalence of neural tube defects in Asturias (Spain: impact of prenatal diagnosis

    Directory of Open Access Journals (Sweden)

    Enrique García López

    2009-12-01

    Full Text Available Objetivo Describir la frecuencia de defectos del tubo neural (DTN -anencefalia, espina bífida y encefalocele-en Asturias, su evolución temporal y el impacto del diagnóstico prenatal. Métodos: Se estudiaron los casos de DTN en nacidos y abortos inducidos durante el período 1990-2004, utilizando la base de datos del Registro de Defectos Congénitos de Asturias, de base poblacional. Se calcularon las tasas de prevalencia total y al nacimiento. Resultados: La prevalencia total de DTN fue de 12,2 casos por 10.000 nacidos (5,9 anencefalias, 5,0 espinas bífidas y 1,3 encefaloceles y mostró una tendencia ligeramente descendente, con un descenso significativo de la espina bífida, mientras que las cifras de anencefalia y encefalocele se mantuvieron estables. Finalizaron en aborto inducido tras el diagnóstico prenatal el 88% de los casos (anencefalia 96,7%; espina bífida 80%; encefalocele 84,6%, lo que determinó una prevalencia al nacimiento muy baja (1,4 DTN por 10.000 nacidos. Conclusiones: En Asturias, en los últimos 15 años se ha producido un descenso selectivo en la prevalencia total de espina bífida de causa no aclarada. La prevención secundaria, mediante los programas de diagnóstico prenatal y la consiguiente interrupción del embarazo, fue el motivo del marcado descenso de la frecuencia en los nacidos; la simple recomendación de suplementación periconcepcional con ácido fólico no parece haber logrado el efecto buscado.Objective: To describe the frequency and prevalence trend for neural tube defects (NTD (anencephaly, spina bifida and encephalocele in Asturias (Spain, as well as the impact of prenatal diagnosis programs. Methods: All cases of NTD in births and induced abortions were studied, using data from the Registry of Congenital Defects of Asturias for 1990-2004. Total and birth prevalence rates were calculated. Results: The prevalence of NTD for 1990-2004 was 12.2 per 10,000 births (5.9 anencephaly, 5.0 spina bifida and 1

  20. Myo-inositol soft gel capsules may prevent the risk of coffee-induced neural tube defects.

    Science.gov (United States)

    De Grazia, Sara; Carlomagno, Gianfranco; Unfer, Vittorio; Cavalli, Pietro

    2012-09-01

    Neural tube defects (NTDs) are classified as folate sensitive (about 70%) and folate resistant (about 30%); although folic acid is able to prevent the former, several data have shown that inositol may prevent the latter. It has recently been proposed that coffee intake might represent a risk factor for NTD, likely by interfering with the inositol signaling. In the present study, we tested the hypothesis that, beside affecting the inositol signaling pathway, coffee also interferes with inositol absorption. In order to evaluate coffee possible negative effects on inositol gastrointestinal absorption, a single-dose bioavailability trial was conducted. Pharmacokinetics (PK) parameters of myo-inositol (MI) powder and MI soft gelatin capsules swallowed with water and with a single 'espresso' were compared. PK profiles were obtained by analysis of MI plasma concentration, and the respective MI bioavailability was compared. Myo-inositol powder administration was negatively affected by coffee intake, thus suggesting an additional explanation to the interference between inositol deficiency and coffee consumption. On the contrary, the concomitant single 'espresso' consumption did not affect MI absorption following MI soft gelatin capsules administration. Furthermore, it was observed that MI soft gelatin capsule administration resulted in improved bioavailability compared to the MI powder form. Myo-inositol soft gelatin capsules should be considered for the preventive treatment of NTDs in folate-resistant subjects due to their higher bioavailability and to the capability to reduce espresso interference.

  1. Ectopic cross-talk between thyroid and retinoic acid signaling: A possible etiology for spinal neural tube defects.

    Science.gov (United States)

    Li, Huili; Bai, Baoling; Zhang, Qin; Bao, Yihua; Guo, Jin; Chen, Shuyuan; Miao, Chunyue; Liu, Xiaozhen; Zhang, Ting

    2015-12-01

    Previous studies have highlighted the connections between neural tube defects (NTDs) and both thyroid hormones (TH) and vitamin A. However, whether the two hormonal signaling pathways interact in NTDs has remained unclear. We measured the expression levels of TH signaling genes in human fetuses with spinal NTDs associated with maternal hyperthyroidism as well as levels of retinoic acid (RA) signaling genes in mouse fetuses exposed to an overdose of RA using NanoString or real-time PCR on spinal cord tissues. Interactions between the two signaling pathways were detected by ChIP assays. The data revealed attenuated DIO2/DIO3 switching in fetuses with NTDs born to hyperthyroid mothers. The promoters of the RA signaling genes CRABP1 and RARB were ectopically occupied by increased RXRG and RXRB but displayed decreased levels of inhibitory histone modifications, suggesting that elevated TH signaling abnormally stimulates RA signaling genes. Conversely, in the mouse model, the observed decrease in Dio3 expression could be explained by increased levels of inhibitory histone modifications in the Dio3 promoter region, suggesting that overactive RA signaling may ectopically derepress TH signaling. This study thus raises in vivo a possible abnormal cross-promotion between two different hormonal signals through their common RXRs and the subsequent recruitment of histone modifications, prompting further investigation into their involvement in the etiology of spinal NTDs. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. System Identification, Prediction, Simulation and Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    a Gauss-Newton search direction is applied. 3) Amongst numerous model types, often met in control applications, only the Non-linear ARMAX (NARMAX) model, representing input/output description, is examined. A simulated example confirms that a neural network has the potential to perform excellent System......The intention of this paper is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: 1) Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. 2) Amongst numerous training algorithms, only the Recursive Prediction Error Method using...

  3. Neural network training by Kalman filtering in process system monitoring

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-03-01

    Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

  4. Thermal photovoltaic solar integrated system analysis using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

    2007-07-01

    The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.

  5. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

    In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

  6. High speed digital interfacing for a neural data acquisition system

    Directory of Open Access Journals (Sweden)

    Bahr Andreas

    2016-09-01

    Full Text Available Diseases like schizophrenia and genetic epilepsy are supposed to be caused by disorders in the early development of the brain. For the further investigation of these relationships a custom designed application specific integrated circuit (ASIC was developed that is optimized for the recording from neonatal mice [Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. 16 Channel Neural Recording Integrated Circuit with SPI Interface and Error Correction Coding. Proc. 9th BIOSTEC 2016. Biodevices: Rome, Italy, 2016; 1: 263; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. Development of a neural recording mixed signal integrated circuit for biomedical signal acquisition. Biomed Eng Biomed Tech Abstracts 2015; 60(S1: 298–299; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider WH. 16 Channel Neural Recording Mixed Signal ASIC. CDNLive EMEA 2015 Conference Proceedings, 2015.]. To enable the live display of the neural signals a multichannel neural data acquisition system with live display functionality is presented. It implements a high speed data transmission from the ASIC to a computer with a live display functionality. The system has been successfully implemented and was used in a neural recording of a head-fixed mouse.

  7. Nonlinear signal processing using neural networks: Prediction and system modelling

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  8. Microfluidic systems for stem cell-based neural tissue engineering.

    Science.gov (United States)

    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.

  9. Optimal serum and red blood cell folate concentrations in women of reproductive age for prevention of neural tube defects: World Health Organization guidelines.

    Science.gov (United States)

    Cordero, Amy M; Crider, Krista S; Rogers, Lisa M; Cannon, Michael J; Berry, R J

    2015-04-24

    Neural tube defects (NTDs) such as spina bifida, anencephaly, and encephalocele are serious birth defects of the brain and spine that occur during the first month of pregnancy when the neural tube fails to close completely. Randomized controlled trials and observational studies have shown that adequate daily consumption of folic acid before and during early pregnancy considerably reduces the risk for NTDs. The U.S. Public Health Service recommends that women capable of becoming pregnant consume 400 µg of folic acid daily for NTD prevention. Furthermore, fortification of staple foods (e.g., wheat flour) with folic acid has decreased folate-sensitive NTD prevalence in multiple settings and is a highly cost-effective intervention.

  10. Epidemiologic study of neural tube defects in Los Angeles County. I. Prevalence at birth based on multiple sources of case ascertainment

    Energy Technology Data Exchange (ETDEWEB)

    Sever, L.E. (Pacific Northwest Lab., Richland, WA); Sanders, M.; Monsen, R.

    1982-01-01

    Epidemiologic studies of the neural tube defects (NTDs), anencephalus and spina bifida, have for the most part been based on single sources of case ascertainment in past studies. The present investigation attempts total ascertainment of NTD cases in the newborn population of Los Angeles County residents for the period 1966 to 1972. Design of the study, sources of data, and estimates of prevalence rates based on single and multiple sources of case ascertainment are here discussed. Anencephalus cases totaled 448, spina bifida 442, and encephalocele 72, giving prevalence rates of 0.52, 0.51, and 0.08 per 1000 total births, respectively, for these neural tube defects - rates considered to be low. The Los Angeles County prevalence rates are compared with those of other recent North American studies and support is provided for earlier suggestions of low rates on the West Coast.

  11. Quantum control of topological defects in magnetic systems

    Science.gov (United States)

    Takei, So; Mohseni, Masoud

    2018-02-01

    Energy-efficient classical information processing and storage based on topological defects in magnetic systems have been studied over the past decade. In this work, we introduce a class of macroscopic quantum devices in which a quantum state is stored in a topological defect of a magnetic insulator. We propose noninvasive methods to coherently control and read out the quantum state using ac magnetic fields and magnetic force microscopy, respectively. This macroscopic quantum spintronic device realizes the magnetic analog of the three-level rf-SQUID qubit and is built fully out of electrical insulators with no mobile electrons, thus eliminating decoherence due to the coupling of the quantum variable to an electronic continuum and energy dissipation due to Joule heating. For a domain wall size of 10-100 nm and reasonable material parameters, we estimate qubit operating temperatures in the range of 0.1-1 K, a decoherence time of about 0.01-1 μ s , and the number of Rabi flops within the coherence time scale in the range of 102-104 .

  12. Feasibility of Genetic Algorithm for Textile Defect Classification Using Neural Network

    OpenAIRE

    Habib, Md. Tarek; Faisal, Rahat Hossain; Rokonuzzaman, M.

    2012-01-01

    The global market for textile industry is highly competitive nowadays. Quality control in production process in textile industry has been a key factor for retaining existence in such competitive market. Automated textile inspection systems are very useful in this respect, because manual inspection is time consuming and not accurate enough. Hence, automated textile inspection systems have been drawing plenty of attention of the researchers of different countries in order to replace...

  13. Neural tube defects and associated anomalies in a fetal and perinatal autopsy series

    DEFF Research Database (Denmark)

    Nielsen, Ljudmilla A G; Maroun, Lisa Leth; Broholm, Helle

    2006-01-01

    anomalies. Among the most common were hydrocephalus, NTD in another region, and anomalies in the urogenital system. 58% of the NTD cases had abnormal weight of one or more organs. Most notable was low adrenal weight not only in anencephalic fetuses but also in cases with cephalocele, suggesting a possible...

  14. Defeitos de fechamento do tubo neural e fatores associados em recém-nascidos vivos e natimortos Neural tube defects and associated factors among liveborn and stillborn infants

    Directory of Open Access Journals (Sweden)

    Marcos J.B. Aguiar

    2003-04-01

    evaluate the prevalence and factors associated to neural tube defects in liveborn and stillborn infants delivered at the Hospital das Clínicas, UFMG, from January 8, 1999 to July 31, 2000. METHODS: this is a descriptive study, based on a database, according to the Latin-American Collaborative Study of Congenital Malformation (ECLAMC rules. Reports on liveborn and stillborn infants with congenital anomalies were prepared including information about morphological description, necropsy results, complementary exams, family, social and pregnancy histories and other clinical data. Each malformed liveborn infant originated a control of the same sex, without malformations. The liveborn and stillborn infants with neural tube defects delivered during that period were classified according to their defect and the presence or absence of associated defects. The liveborn and stillborn infants with neural tube defects were compared to newborns without neural tube defects according to their weight and sex and their mother's age and parity. Epi-Info 6.0 Program was used for the statistical analysis of the results. RESULTS: the prevalence of neural tube defects was 4.73 to 1,000 deliveries (89:18,807; it was significantly higher among stillborn infants (23.7:1,000 than among liveborn infants (4.16:1,000, p < 0.001. Neural tube defects were more often found among low weight liveborn infants (< 2,500 g, p < 0.001 and less frequently among women who had had more than three gestations, p = 0.007. No association was found regarding newborn's sex or maternal age. There was no association with newborn's sex and weight, maternal parity or age among stillborn infants. The most common neural tube defects were myelomeningocele (47.2%, anencephaly (26.9% and encephalocele (16.9%. The defects were found as isolated anomalies in 71.1% of the liveborn and 38.5% of the stillborn infants; they were part of a syndrome in 9.2% (liveborn and 7.7% (stillborn. CONCLUSIONS: the neural tube defect prevalence found

  15. Adaptive Synchronization of Memristor-based Chaotic Neural Systems

    Directory of Open Access Journals (Sweden)

    Xiaofang Hu

    2014-11-01

    Full Text Available Chaotic neural networks consisting of a great number of chaotic neurons are able to reproduce the rich dynamics observed in biological nervous systems. In recent years, the memristor has attracted much interest in the efficient implementation of artificial synapses and neurons. This work addresses adaptive synchronization of a class of memristor-based neural chaotic systems using a novel adaptive backstepping approach. A systematic design procedure is presented. Simulation results have demonstrated the effectiveness of the proposed adaptive synchronization method and its potential in practical application of memristive chaotic oscillators in secure communication.

  16. Self-focusing and defect characterization with the FAUST system

    International Nuclear Information System (INIS)

    Mahaut, S.; Cattiaux, G.; Roy, O.; Benoist, PH.

    1996-01-01

    The FAUST (Focusing Adaptative UltraSonic Tomography) system was developed at the French Atomic Energy Commission (CEA) to improve performances of ultrasonic non destructive testing in terms of adaptability to various control configurations and defect characterization. Unlike conventional techniques only allowing fixed focusing, this system can dynamically modify the characteristics of the ultrasonic beam. This system relies on optimized phased array transducers connected to a multi-channel acquisition system supplying amplitude and delay laws allowing to drive the ultrasonic beam. Previous works have demonstrated the skills of this system for ultrasonic beam forming. The reliability of the procedure was proved by comparison with theoretical results, while comparisons with experimental results provided by conventional transducer pointed out the improved capacities of the system. In the first part of paper, we briefly present the model used for the system validation. This field computational model developed at the CEA is used to design optimized phased array transducers dedicated to NDE configurations (immersed transducers used to focus through Fluid/Solid interfaces). Theoretical delay laws and related ultrasonic fields are also calculated from this model. In addition to its ability to dynamically form the ultrasonic beam by taking account of the control configuration, we investigate in the second part of the paper the capabilities of the system to extract informations from he received signals. The ability of the system to store the signals received by all the elements of the array allows one to perform different reconstruction procedures. Useful informations can be extracted from the received signals: experimentally measured delay laws can be determined from reflected signals to obtain an optimal imaging, while the related amplitude distribution over the array points out geometrical characteristics of the reflector. (authors)

  17. Integrated evolutionary computation neural network quality controller for automated systems

    Energy Technology Data Exchange (ETDEWEB)

    Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

    1999-06-01

    With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

  18. Temporal neural networks and transient analysis of complex engineering systems

    Science.gov (United States)

    Uluyol, Onder

    A theory is introduced for a multi-layered Local Output Gamma Feedback (LOGF) neural network within the paradigm of Locally-Recurrent Globally-Feedforward neural networks. It is developed for the identification, prediction, and control tasks of spatio-temporal systems and allows for the presentation of different time scales through incorporation of a gamma memory. It is initially applied to the tasks of sunspot and Mackey-Glass series prediction as benchmarks, then it is extended to the task of power level control of a nuclear reactor at different fuel cycle conditions. The developed LOGF neuron model can also be viewed as a Transformed Input and State (TIS) Gamma memory for neural network architectures for temporal processing. The novel LOGF neuron model extends the static neuron model by incorporating into it a short-term memory structure in the form of a digital gamma filter. A feedforward neural network made up of LOGF neurons can thus be used to model dynamic systems. A learning algorithm based upon the Backpropagation-Through-Time (BTT) approach is derived. It is applicable for training a general L-layer LOGF neural network. The spatial and temporal weights and parameters of the network are iteratively optimized for a given problem using the derived learning algorithm.

  19. Optical neural network system for pose determination of spinning satellites

    Science.gov (United States)

    Lee, Andrew; Casasent, David

    1990-01-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

  20. 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.

  1. Association of main folate metabolic pathway gene polymorphisms with neural tube defects in Han population of Northern China.

    Science.gov (United States)

    Fang, Yulian; Zhang, Ruiping; Zhi, Xiufang; Zhao, Linsheng; Cao, Lirong; Wang, Yizheng; Cai, Chunquan

    2018-04-01

    Neural tube defects (NTDs) are one of the most prevalent and the most severe congenital malformations worldwide. Studies have confirmed that folic acid supplementation could effectively reduce NTDs risk, but the genetic mechanism remains unclear. In this study, we explored association of single nucleotide polymorphisms (SNP) within folate metabolic pathway genes with NTDs in Han population of Northern China. We performed a case-control study to compare genotype and allele distributions of SNPs in 152 patients with NTDs and 169 controls. A total of 16 SNPs within five genes were genotyped by the Sequenom MassARRAY assay. Our results indicated that three SNPs associated significantly with NTDs (P<0.05). For rs2236225 within MTHFD1, children with allele A or genotype AA had a high NTDs risk (OR=1.500, 95%CI=1.061~2.120; OR=2.862, 95%CI=1.022~8.015, respectively). For rs1801133 within MTHFR, NTDs risk markedly increased in patients with allele T or genotype TT (OR=1.552, 95%CI=1.130~2.131; OR=2.344, 95%CI=1.233~4.457, respectively). For rs1801394 within MTRR, children carrying allele G and genotype GG had a higher NTDs risk (OR=1.533, 95%CI=1.102~2.188; OR=2.355, 95%CI=1.044~5.312, respectively). Our results suggest that rs2236225 of MTHFD1 gene, rs1801133 of MTHFR gene and rs1801394 of MTRR gene were associated with NTDs in Han population of Northern China.

  2. Fetoscopic Open Neural Tube Defect Repair: Development and Refinement of a Two-Port, Carbon Dioxide Insufflation Technique.

    Science.gov (United States)

    Belfort, Michael A; Whitehead, William E; Shamshirsaz, Alireza A; Bateni, Zhoobin H; Olutoye, Oluyinka O; Olutoye, Olutoyin A; Mann, David G; Espinoza, Jimmy; Williams, Erin; Lee, Timothy C; Keswani, Sundeep G; Ayres, Nancy; Cassady, Christopher I; Mehollin-Ray, Amy R; Sanz Cortes, Magdalena; Carreras, Elena; Peiro, Jose L; Ruano, Rodrigo; Cass, Darrell L

    2017-04-01

    To describe development of a two-port fetoscopic technique for spina bifida repair in the exteriorized, carbon dioxide-filled uterus and report early results of two cohorts of patients: the first 15 treated with an iterative technique and the latter 13 with a standardized technique. This was a retrospective cohort study (2014-2016). All patients met Management of Myelomeningocele Study selection criteria. The intraoperative approach was iterative in the first 15 patients and was then standardized. Obstetric, maternal, fetal, and early neonatal outcomes were compared. Standard parametric and nonparametric tests were used as appropriate. Data for 28 patients (22 endoscopic only, four hybrid, two abandoned) are reported, but only those with a complete fetoscopic repair were analyzed (iterative technique [n=10] compared with standardized technique [n=12]). Maternal demographics and gestational age (median [range]) at fetal surgery (25.4 [22.9-25.9] compared with 24.8 [24-25.6] weeks) were similar, but delivery occurred at 35.9 (26-39) weeks of gestation with the iterative technique compared with 39 (35.9-40) weeks of gestation with the standardized technique (Pmet in 9 of 12 (75%) and 3 of 10 (30%), respectively, and 7 of 12 (58%) compared with 2 of 10 (20%) have been treated for hydrocephalus to date. These latter differences were not statistically significant. Fetoscopic open neural tube defect repair does not appear to increase maternal-fetal complications as compared with repair by hysterotomy, allows for vaginal delivery, and may reduce long-term maternal risks. ClinicalTrials.gov, https://clinicaltrials.gov, NCT02230072.

  3. 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.

  4. Interaction between the SLC19A1 gene and maternal first trimester fever on offspring neural tube defects.

    Science.gov (United States)

    Pei, Lijun; Zhu, Huiping; Ye, Rongwei; Wu, Jilei; Liu, Jianmeng; Ren, Aiguo; Li, Zhiwen; Zheng, Xiaoying

    2015-01-01

    Many studies have indicated that the reduced folate carrier gene (SLC19A1) is associated with an increased risk of neural tube defects (NTDs). However, the interaction between the SLC19A1 gene variant and maternal fever exposure and NTD risk remains unknown. The aim of this study was to investigate whether the risk for NTDs was influenced by the interactions between the SLC19A1 (rs1051266) variant and maternal first trimester fever. We investigated the potential interaction between maternal first trimester fever and maternal or offspring SLC19A1 polymorphism through a population-based case-control study. One hundred and four nuclear families with NTDs and 100 control families with nonmal newborns were included in the study. SLC19A1 polymorphism was determined using polymerase chain reaction-restricted fragment length polymorphism. Mothers who had the GG/GA genotype and first trimester fever had an elevated risk of NTDs (adjusted odds ratio, 11.73; 95% confidence interval, 3.02-45.58) as compared to absence of maternal first trimester fever and AA genotype after adjusting for maternal education, paternal education, and age, and had a significant interactive coefficient (γ = 3.17) between maternal GG/GA genotype and first trimester fever. However, there was no interaction between offspring's GG/GA genotype and maternal first trimester fever (the interactive coefficient γ = 0.97) after adjusting for confounding factors. Our findings suggested that the risk of NTDs was potentially influenced by a gene-environment interaction between maternal SLC19A1 rs1051266 GG/GA genotype and first trimester fever. Maternal GG/GA genotype may strengthen the effect of maternal fever exposure on NTD risk in this Chinese population. © 2014 Wiley Periodicals, Inc.

  5. Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

    DEFF Research Database (Denmark)

    Lehmann, Torsten

    1998-01-01

    In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  6. Neural network based system for script identification in Indian ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... The paper describes a neural network-based script identification system which can be used in the machine reading of documents written in English, Hindi and Kannada language scripts. Script identification is a basic requirement in automation of document processing, in multi-script, multi-lingual ...

  7. Development of a hybrid system of artificial neural networks and ...

    African Journals Online (AJOL)

    Development of a hybrid system of artificial neural networks and artificial bee colony algorithm for prediction and modeling of customer choice in the market. ... attempted to present a new method for the modeling and prediction of customer choice in the market using the combination of artificial intelligence and data mining.

  8. Deciphering defective amelogenesis using in vitro culture systems.

    Science.gov (United States)

    Arinawati, Dian Yosi; Miyoshi, Keiko; Tanimura, Ayako; Horiguchi, Taigo; Hagita, Hiroko; Noma, Takafumi

    2018-04-01

    The conventional two-dimensional (2D) in vitro culture system is frequently used to analyze the gene expression with or without extracellular signals. However, the cells derived from primary culture and cell lines frequently deviate the gene expression profile compared to the corresponding in vivo samples, which sometimes misleads the actual gene regulation in vivo. To overcome this gap, we developed the comparative 2D and 3D in vitro culture systems and applied them to the genetic study of amelogenesis imperfecta (AI) as a model. Recently, we found specificity protein 6 (Sp6) mutation in an autosomal-recessive AI rat that was previously named AMI. We constructed 3D structure of ARE-B30 cells (AMI-derived rat dental epithelial cells) or G5 (control wild type cells) combined with RPC-C2A cells (rat pulp cell line) separated by the collagen membrane, while in 2D structure, ARE-B30 or G5 was cultured with or without the collagen membrane. Comparative analysis of amelogenesis-related gene expression in ARE-B30 and G5 using our 2D and 3D in vitro systems revealed distinct expression profiles, showing the causative outcomes. Bone morphogenetic protein 2 and follistatin were reciprocally expressed in G5, but not in ARE-B30 cells. All-or-none expression of amelotin, kallikrein-related peptidase 4, and nerve growth factor receptor was observed in both cell types. In conclusion, our in vitro culture systems detected the phenotypical differences in the expression of the stage-specific amelogenesis-related genes. Parallel analysis with 2D and 3D culture systems may provide a platform to understand the molecular basis for defective amelogenesis caused by Sp6 mutation. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  9. A Robust Single Primate Neuroepithelial Cell Clonal Expansion System for Neural Tube Development and Disease Studies

    Directory of Open Access Journals (Sweden)

    Xiaoqing Zhu

    2016-02-01

    Full Text Available Developing a model of primate neural tube (NT development is important to promote many NT disorder studies in model organisms. Here, we report a robust and stable system to allow for clonal expansion of single monkey neuroepithelial stem cells (NESCs to develop into miniature NT-like structures. Single NESCs can produce functional neurons in vitro, survive, and extensively regenerate neuron axons in monkey brain. NT formation and NESC maintenance depend on high metabolism activity and Wnt signaling. NESCs are regionally restricted to a telencephalic fate. Moreover, single NESCs can turn into radial glial progenitors (RGPCs. The transition is accurately regulated by Wnt signaling through regulation of Notch signaling and adhesion molecules. Finally, using the “NESC-TO-NTs” system, we model the functions of folic acid (FA on NT closure and demonstrate that FA can regulate multiple mechanisms to prevent NT defects. Our system is ideal for studying NT development and diseases.

  10. Frecuencia y algunos factores de riesgo de mortalidad en el estado de Hidalgo, México, por defectos de cierre del tubo neural Mortality due to neural tube defects and risk factors in Hidalgo, Mexico

    Directory of Open Access Journals (Sweden)

    Sergio Muñoz-Juárez

    2002-09-01

    Full Text Available Objetivo. Calcular el riesgo de muerte fetal secundaria a defectos del cierre del tubo neural y estimar factores asociados con este tipo de muertes en el estado de Hidalgo. Material y métodos. La información analizada en el año 2000 fue obtenida de los certificados de muerte fetal del periodo 1990-1995 en el estado de Hidalgo. Se utilizó un diseño de mortalidad proporcional, considerado como una variante del diseño de casos y controles. Los casos fueron aquellas muertes fetales secundarias a defectos del tubo neural y los controles las muertes fetales por otros motivos. Se utilizó ji cuadrada de Pearson para estimar las diferencias entre los casos y controles. Para el riesgo crudo de morir por defectos de cierre del tubo neural se empleó la razón de momios, y para el riesgo ajustado se usó la regresión logística no condicional. Resultados. Se analizaron 3 673 certificados de muerte fetal, identificándose 8.06% de muertes por defectos del tubo neural; el resto lo constituyeron muertes por otras causas. Se encontró como variables asociadas con la muerte fetal por defectos del tubo neural a los fetos que pesaron menos de 2 500 gramos (RM 5.0, IC 95% 3.6, 6.7, a los productos del sexo femenino (RM 1.7, IC 95% 1.3, 2.3 y a las muertes ocurridas en el periodo fetal tardío (RM 5.5 IC 95% 3.8, 8.1. Conclusiones. Los resultados indican que el riesgo de muerte fetal debida a defectos del tubo neural es mayor en productos de bajo peso, en los del sexo femenino y los que ocurren en el periodo fetal tardío.Objective. To calculate the risk of fetal death due to neural tube defects and estimate associated factors in the state of Hidalgo, Mexico. Material and Methods. Data were abstracted from death certificates registered during 1990-1995 in the state of Hidalgo, Mexico. The design was a proportional mortality study, which is considered as a variant of the case control design. Cases were deaths with any type of neural tube defect, and controls

  11. Neural mechanisms of selective attention in the somatosensory system.

    Science.gov (United States)

    Gomez-Ramirez, Manuel; Hysaj, Kristjana; Niebur, Ernst

    2016-09-01

    Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates. Copyright © 2016 the American Physiological Society.

  12. Frequency-difference-dependent stochastic resonance in neural systems

    Science.gov (United States)

    Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

    2017-08-01

    Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

  13. Fault diagnosis system of electromagnetic valve using neural network filter

    International Nuclear Information System (INIS)

    Hayashi, Shoji; Odaka, Tomohiro; Kuroiwa, Jousuke; Ogura, Hisakazu

    2008-01-01

    This paper is concerned with the gas leakage fault detection of electromagnetic valve using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty in detecting gas leakage faults by sound signals lies in the fact that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system, and an accurate mathematical model of the dynamic system can be established using a neural network filter. The predicted error between predicted values and practical ones constitutes the output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that the neural network filter was effective in gas leakage detection. (author)

  14. Neural Tube Defects

    Science.gov (United States)

    ... March of Dimes Premature Birth Report Card Grades Cities, Counties; Focuses on Racial and Ethnic Disparities March ... folate. Good sources of folate are: Beans Leafy green vegetables Orange juice You have to eat a ...

  15. Synthesis of recurrent neural networks for dynamical system simulation.

    Science.gov (United States)

    Trischler, Adam P; D'Eleuterio, Gabriele M T

    2016-08-01

    We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

    Science.gov (United States)

    Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

    2016-11-14

    In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

  17. 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

  18. Neural multigrid for gauge theories and other disordered systems

    International Nuclear Information System (INIS)

    Baeker, M.; Kalkreuter, T.; Mack, G.; Speh, M.

    1992-09-01

    We present evidence that multigrid works for wave equations in disordered systems, e.g. in the presence of gauge fields, no matter how strong the disorder, but one needs to introduce a 'neural computations' point of view into large scale simulations: First, the system must learn how to do the simulations efficiently, then do the simulation (fast). The method can also be used to provide smooth interpolation kernels which are needed in multigrid Monte Carlo updates. (orig.)

  19. Neural computing thermal comfort index for HVAC systems

    International Nuclear Information System (INIS)

    Atthajariyakul, S.; Leephakpreeda, T.

    2005-01-01

    The primary purpose of a heating, ventilating and air conditioning (HVAC) system within a building is to make occupants comfortable. Without real time determination of human thermal comfort, it is not feasible for the HVAC system to yield controlled conditions of the air for human comfort all the time. This paper presents a practical approach to determine human thermal comfort quantitatively via neural computing. The neural network model allows real time determination of the thermal comfort index, where it is not practical to compute the conventional predicted mean vote (PMV) index itself in real time. The feed forward neural network model is proposed as an explicit function of the relation of the PMV index to accessible variables, i.e. the air temperature, wet bulb temperature, globe temperature, air velocity, clothing insulation and human activity. An experiment in an air conditioned office room was done to demonstrate the effectiveness of the proposed methodology. The results show good agreement between the thermal comfort index calculated from the neural network model in real time and those calculated from the conventional PMV model

  20. Magnitude of Neural Tube Defects and Associated Risk Factors at Three Teaching Hospitals in Addis Ababa, Ethiopia

    Directory of Open Access Journals (Sweden)

    Abel Gedefaw

    2018-01-01

    Full Text Available There is scarcity of data on prevalence of neural tube defects (NTDs in lower-income countries. Local data are important to understand the real burden of the problem and explore risk factors to design and implement preventive approaches. This study aimed to determine prevalence and risk factors of NTDs. A hospital-based cross-sectional and unmatched case-control study was conducted at three teaching hospitals of Addis Ababa University. NTDs were defined as cases of anencephaly, spina bifida, and encephalocele based on ICD-10 criteria. The prevalence of NTDs was calculated per 10,000 births for both birth and total prevalence. During seven months, we observed 55 cases of NTDs out of 8677 births after 28 weeks of gestation—birth prevalence of 63.4 per 10,000 births (95% confidence interval (CI, 51–77. A total of 115 cases were medically terminated after 12 weeks of gestation. Fifty-six of these terminations (48.7% were due to NTDs. Thus, total prevalence of NTDs after 12 weeks’ gestation is 126 per 10,000 births (95% CI, 100–150. Planned pregnancy (adjusted odds ratio (aOR, 0.47; 95% CI, 0.24–0.92, male sex (aOR, 0.56; 95% CI, 0.33–0.94, normal or underweight body mass index (aOR, 0.49; 95%, 0.29–0.95, and taking folic acid or multivitamins during first trimester (aOR, 0.47; 95%, 0.23–0.95 were protective of NTDs. However, annual cash family income less than $1,300 USD (aOR, 2.5; 95%, 1.2–5.5, $1,300–1,800 USD (aOR, 2.8; 95%, 1.3–5.8, and $1,801–2,700 USD (aOR, 2.6; 95%, 1.2–5.8 was found to be risk factors compared to income greater than $2,700 USD. The prevalence of NTDs was found to be high in this setting. Comprehensive preventive strategies focused on identified risk factors should be urgently established. More studies on prevention strategies, including folic acid supplementations, should be conducted in the setting.

  1. Magnitude of Neural Tube Defects and Associated Risk Factors at Three Teaching Hospitals in Addis Ababa, Ethiopia.

    Science.gov (United States)

    Gedefaw, Abel; Teklu, Sisay; Tadesse, Birkneh Tilahun

    2018-01-01

    There is scarcity of data on prevalence of neural tube defects (NTDs) in lower-income countries. Local data are important to understand the real burden of the problem and explore risk factors to design and implement preventive approaches. This study aimed to determine prevalence and risk factors of NTDs. A hospital-based cross-sectional and unmatched case-control study was conducted at three teaching hospitals of Addis Ababa University. NTDs were defined as cases of anencephaly, spina bifida, and encephalocele based on ICD-10 criteria. The prevalence of NTDs was calculated per 10,000 births for both birth and total prevalence. During seven months, we observed 55 cases of NTDs out of 8677 births after 28 weeks of gestation-birth prevalence of 63.4 per 10,000 births (95% confidence interval (CI), 51-77). A total of 115 cases were medically terminated after 12 weeks of gestation. Fifty-six of these terminations (48.7%) were due to NTDs. Thus, total prevalence of NTDs after 12 weeks' gestation is 126 per 10,000 births (95% CI, 100-150). Planned pregnancy (adjusted odds ratio (aOR), 0.47; 95% CI, 0.24-0.92), male sex (aOR, 0.56; 95% CI, 0.33-0.94), normal or underweight body mass index (aOR, 0.49; 95%, 0.29-0.95), and taking folic acid or multivitamins during first trimester (aOR, 0.47; 95%, 0.23-0.95) were protective of NTDs. However, annual cash family income less than $1,300 USD (aOR, 2.5; 95%, 1.2-5.5), $1,300-1,800 USD (aOR, 2.8; 95%, 1.3-5.8), and $1,801-2,700 USD (aOR, 2.6; 95%, 1.2-5.8) was found to be risk factors compared to income greater than $2,700 USD. The prevalence of NTDs was found to be high in this setting. Comprehensive preventive strategies focused on identified risk factors should be urgently established. More studies on prevention strategies, including folic acid supplementations, should be conducted in the setting.

  2. Maternal Consumption of Non-Staple Food in the First Trimester and Risk of Neural Tube Defects in Offspring

    Directory of Open Access Journals (Sweden)

    Meng Wang

    2015-04-01

    Full Text Available To study the associations between maternal consumption of non-staple food in the first trimester and risk of neural tube defects (NTDs in offspring. Data collected from a hospital-based case-control study conducted between 2006 and 2008 in Shandong/Shanxi provinces including 459 mothers with NTDs-affected births and 459 mothers without NTDs-affected births. Logistic regression models were used to examine the associations between maternal consumption of non-staple food in the first trimester and risk of NTDs in offspring. The effects were evaluated by odds ratio (OR and 95% confidence intervals (95% CIs with SAS9.1.3.software. Maternal consumption of milk, fresh fruits and nuts in the first trimester were protective factors for total NTDs. Compared with consumption frequency of ˂1 meal/week, the ORs for milk consumption frequency of 1–2, 3–6, ≥7 meals/week were 0.50 (95% CI: 0.28–0.88, 0.56 (0.32–0.99, and 0.59 (0.38–0.90, respectively; the ORs for fresh fruits consumption frequency of 1–2, 3–6, ≥7 meals/week were 0.29 (95% CI: 0.12–0.72, 0.22 (0.09–0.53, and 0.32 (0.14–0.71, respectively; the ORs for nuts consumption frequency of 1–2, 3–6, ≥7 meals/week were 0.60 (95% CI: 0.38–0.94, 0.49 (0.31–0.79, and 0.63 (0.36–1.08, respectively. Different effects of above factors on NTDs were found for subtypes of anencephaly and spina bifida. Maternal non-staple food consumption of milk, fresh fruits and nuts in the first trimester was associated with reducing NTDs risk in offspring.

  3. A comprehensive evaluation of food fortification with folic acid for the primary prevention of neural tube defects

    Directory of Open Access Journals (Sweden)

    Lam Angeline

    2004-09-01

    Full Text Available Abstract Background Periconceptional use of vitamin supplements containing folic acid reduces the risk of a neural tube defect (NTD. In November 1998, food fortification with folic acid was mandated in Canada, as a public health strategy to increase the folic acid intake of all women of childbearing age. We undertook a comprehensive population based study in Newfoundland to assess the benefits and possible adverse effects of this intervention. Methods This study was carried out in women aged 19–44 years and in seniors from November 1997 to March 1998, and from November 2000 to March 2001. The evaluation was comprised of four components: I Determination of rates of NTDs; II Dietary assessment; III Blood analysis; IV Assessment of knowledge and use of folic acid supplements. Results The annual rates of NTDs in Newfoundland varied greatly between 1976 and 1997, with a mean rate of 3.40 per 1,000 births. There was no significant change in the average rates between 1991–93 and 1994–97 (relative risk [RR] 1.01, 95% confidence interval [CI] 0.76–1.34. The rates of NTDs fell by 78% (95% CI 65%–86% after the implementation of folic acid fortification, from an average of 4.36 per 1,000 births during 1991–1997 to 0.96 per 1,000 births during 1998–2001 (RR 0.22, 95% CI 0.14–0.35. The average dietary intake of folic acid due to fortification was 70 μg/day in women aged 19–44 years and 74 μg/day in seniors. There were significant increases in serum and RBC folate levels for women and seniors after mandatory fortification. Among seniors, there were no significant changes in indices typical of vitamin B12 deficiencies, and no evidence of improved folate status masking haematological manifestations of vitamin B12 deficiency. The proportion of women aged 19–44 years taking a vitamin supplement containing folic acid increased from 17% to 28%. Conclusions Based on these findings, mandatory food fortification in Canada should continue at the

  4. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  5. Lot-sizing for a single-stage single-product production system with rework of perishable production defectives

    NARCIS (Netherlands)

    Teunter, R.; Flapper, S.D.P.

    2003-01-01

    We consider a single-stage single-product production system. Produced units may be non-defective, reworkable defective, or non-reworkable defective. The system switches between production and rework. After producing a fixed number (N) of units, all reworkable defective units are reworked. Reworkable

  6. 49 CFR 215.109 - Defective plain bearing box: Journal lubrication system.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Defective plain bearing box: Journal lubrication... Freight Car Components Suspension System § 215.109 Defective plain bearing box: Journal lubrication system...) Metal parts contacting the journal; or (e) Is— (1) Missing; or (2) Not in contact with the journal. ...

  7. Parameter estimation in space systems using recurrent neural networks

    Science.gov (United States)

    Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.

    1991-01-01

    The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

  8. Analysis of the DWPF glass pouring system using neural networks

    International Nuclear Information System (INIS)

    Calloway, T.B. Jr.; Jantzen, C.M.

    1997-01-01

    Neural networks were used to determine the sensitivity of 39 selected Melter/Melter Off Gas and Melter Feed System process parameters as related to the Defense Waste Processing Facility (DWPF) Melter Pour Spout Pressure during the overall analysis and resolution of the DWPF glass production and pouring issues. Two different commercial neural network software packages were used for this analysis. Models were developed and used to determine the critical parameters which accurately describe the DWPF Pour Spout Pressure. The model created using a low-end software package has a root mean square error of ± 0.35 inwc ( 2 = 0.77) with respect to the plant data used to validate and test the model. The model created using a high-end software package has a R 2 = 0.97 with respect to the plant data used to validate and test the model. The models developed for this application identified the key process parameters which contribute to the control of the DWPF Melter Pour Spout pressure during glass pouring operations. The relative contribution and ranking of the selected parameters was determined using the modeling software. Neural network computing software was determined to be a cost-effective software tool for process engineers performing troubleshooting and system performance monitoring activities. In remote high-level waste processing environments, neural network software is especially useful as a replacement for sensors which have failed and are costly to replace. The software can be used to accurately model critical remotely installed plant instrumentation. When the instrumentation fails, the software can be used to provide a soft sensor to replace the actual sensor, thereby decreasing the overall operating cost. Additionally, neural network software tools require very little training and are especially useful in mining or selecting critical variables from the vast amounts of data collected from process computers

  9. Primary prevention of neural-tube defects and some other congenital abnormalities by folic acid and multivitamins: history, missed opportunity and tasks

    Science.gov (United States)

    Bártfai, Zoltán; Bánhidy, Ferenc

    2011-01-01

    The history of intervention trials of periconception folic acid with multivitamin and folic acid supplementation in women has shown a recent breakthrough in the primary prevention of structural birth defects, namely neural-tube defects and some other congenital abnormalities. Recently, some studies have demonstrated the efficacy of this new method in reducing congenital abnormalities with specific origin; for example, in the offspring of diabetic and epileptic mothers, and in pregnancy with high fever. The benefits and drawbacks of four possible uses of periconception folate/folic acid and multivitamin supplementation are discussed: we believe there has been a missed opportunity to implement this preventive approach in medical practice. The four methods are as follows: (i) dietary intake of folate and other vitamins, (ii) periconception folic acid/multivitamin supplementation, (iii) food fortification with folic acid, and (iv) the combination of oral contraceptives with 6S-5-methytetrahydrofolate (‘folate’). PMID:25083211

  10. Prevalência de defeitos de fechamento de tubo neural no Vale do Paraíba, São Paulo Prevalence of neural tube defects in Vale do Paraíba, São Paulo, Brazil

    Directory of Open Access Journals (Sweden)

    Luiz Fernando C. Nascimento

    2008-12-01

    Full Text Available OBJETIVO: Estimar a prevalência de defeitos de fechamento do tubo neural no Vale do Paraíba paulista e identificar possíveis fatores maternos e neonatais associados a tais defeitos. MÉTODOS: Realizou-se um estudo transversal com dados secundários obtidos na Secretaria Estadual da Saúde referentes aos nascimentos ocorridos em 2004 no Vale do Paraíba paulista, que compreende 35 municípios e conta com população de 2 milhões de habitantes. Anencefalia, encefalocele e espina bífida (mielocele e mielomeningocele foram considerados defeitos de fechamento do tubo neural. As variáveis maternas foram: idade, escolaridade, cor da pele, número de consultas no pré-natal, número de filhos vivos e relato de óbito fetal prévio. As variáveis relativas ao recém-nascido foram: peso, idade gestacional e escore de Apgar. Realizou-se comparação das médias por meio do teste t de Student e obtiveram-se os valores das razões de chance com intervalos de confiança de 95%. RESULTADOS: Foram analisados 33.653 nascidos vivos. Trinta e oito recém-nascidos com o defeito foram encontrados (1,13/1.000 nascidos vivos, sendo 23 casos de espina bífida. Houve associação com baixo peso ao nascimento, prematuridade e menores escores de Apgar de cinco minutos. CONCLUSÕES: A prevalência desta anomalia foi inferior à de outros estudos nacionais e sua presença esteve associada ao baixo peso, à prematuridade e à baixa vitalidade ao nascer.OBJECTIVE: To estimate the prevalence of neural tube defects in Vale do Paraíba, São Paulo, Brazil, and to identify possible maternal and neonatal variables associated with these defects. METHODS: This cross-sectional study used secondary records of the Health Department of São Paulo State related live births during 2004 in Vale do Paraíba, São Paulo, Brazil. This region has 35 cities and 2 million inhabitants. Anencephaly, encephalocele and spina bifida (myelocele and myelomeningocele were considered as neural tube

  11. Neural Computations in a Dynamical System with Multiple Time Scales.

    Science.gov (United States)

    Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

    2016-01-01

    Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

  12. Statistical Physics of Neural Systems with Nonadditive Dendritic Coupling

    Directory of Open Access Journals (Sweden)

    David Breuer

    2014-03-01

    Full Text Available How neurons process their inputs crucially determines the dynamics of biological and artificial neural networks. In such neural and neural-like systems, synaptic input is typically considered to be merely transmitted linearly or sublinearly by the dendritic compartments. Yet, single-neuron experiments report pronounced supralinear dendritic summation of sufficiently synchronous and spatially close-by inputs. Here, we provide a statistical physics approach to study the impact of such nonadditive dendritic processing on single-neuron responses and the performance of associative-memory tasks in artificial neural networks. First, we compute the effect of random input to a neuron incorporating nonlinear dendrites. This approach is independent of the details of the neuronal dynamics. Second, we use those results to study the impact of dendritic nonlinearities on the network dynamics in a paradigmatic model for associative memory, both numerically and analytically. We find that dendritic nonlinearities maintain network convergence and increase the robustness of memory performance against noise. Interestingly, an intermediate number of dendritic branches is optimal for memory functionality.

  13. Levels of PAH-DNA adducts in cord blood and cord tissue and the risk of fetal neural tube defects in a Chinese population.

    Science.gov (United States)

    Yi, Deqing; Yuan, Yue; Jin, Lei; Zhou, Guodong; Zhu, Huiping; Finnell, Richard H; Ren, Aiguo

    2015-01-01

    Maternal exposure to polycyclic aromatic hydrocarbons (PAHs) has been shown to be associated with an elevated risk for neural tube defects (NTDs). In the human body, PAHs are bioactivated and the resultant reactive epoxides can covalently bind to DNA to form PAH-DNA adducts, which may, in turn, cause transcription errors, changes in gene expression or altered patterns of apoptosis. During critical developmental phases, these changes can result in abnormal morphogenesis. We aimed to examine the relationship between the levels of PAH-DNA adducts in cord blood and cord tissue and the risk of NTDs. From 2010 to 2012, 60 NTD cases and 60 healthy controls were recruited from a population-based birth defects surveillance system in five counties of Shanxi Province in Northern China, where the emission of PAHs remains one of the highest in the country and PAHs exposure is highly prevalent. PAH-DNA adducts in cord blood of 15 NTD cases and 15 control infants, and in cord tissue of 60 NTD cases and 60 control infants were measured using the (32)P-postlabeling method. PAH-DNA adduct levels in cord blood tend to be higher in the NTD group (28.5 per 10(8) nucleotides) compared with controls (19.7 per 10(8) nucleotides), although the difference was not statistically significant (P=0.377). PAH-DNA adducts in cord tissue were significantly higher in the NTD group (24.6 per 10(6) nucleotides) than in the control group (15.3 per 10(6) nucleotides), P=0.010. A positive dose-response relationship was found between levels of PAH-DNA adducts in cord tissue and the risk of NTDs (P=0.009). When the lowest tertile was used as the referent and potential confounding factors were adjusted for, a 1.03-fold (95% CI, 0.37-2.89) and 2.96-fold (95% CI, 1.16-7.58) increase in the risk of NTDs was observed for fetuses whose cord tissue PAH-DNA adduct levels were in the second and highest tertile, respectively. High levels of PAH-DNA adducts in fetal tissues were associated with increased risks of

  14. Oxygen defects in Fe-substituted Tl-system superconductors

    Institute of Scientific and Technical Information of China (English)

    李阳; 曹国辉; 王耘波; 马庆珠; 熊小涛; 陈宁; 马如璋; 郭应焕; 许祝安; 王劲松; 张小俊; 焦正宽; 彭获田; 周思海

    1996-01-01

    For Fe-doped T1-1223 phase,the excess oxygen defects induced by Fe dopants are studied by means of Hall coefficient,thermogravimetric measurements,Mossbauer spectroscopy,and the model calculation of the effective bond valence.The extra oxygen defects have effects on carrier density and microstructure of the superconductors.In the light doping level of Fe (x=0-0.05),the superconducting transition and carrier density have significant corresponding relation--the zero resistance temperature Tco and carrier densities decrease linearly with Fe dopants increasing.The thermogravimetric measurements show that the Fe3+ ions’ substituting for Cu2+ ions can bring the extra oxygen into the lattice to form extra oxygen defects.The calculation of the effective bond valence shows that the decrease of carrier density originates the strongly localized binding of the extra oxygen defects.The distortion of Cu-O layer induced by the extra oxygen defects decreases the superconductive transition temperature.The microstructure

  15. Neural network-based expert system for severe accident management

    International Nuclear Information System (INIS)

    Klopp, G.T.; Silverman, E.B.

    1992-01-01

    This paper presents the results of the second phase of a three-phase Severe Accident Management expert system program underway at Commonwealth Edison Company (CECo). Phase I successfully demonstrated the feasibility of Artificial Neural Networks to support several of the objectives of severe accident management. Simulated accident scenarios were generated by the Modular Accident Analysis Program (MAAP) code currently in use by CECo as part of their Individual Plant Evaluations (IPE)/Accident Management Program. The primary objectives of the second phase were to develop and demonstrate four capabilities of neural networks with respect to nuclear power plant severe accident monitoring and prediction. The results of this work would form the foundation of a demonstration system which included expert system performance features. These capabilities included the ability to: (1) Predict the time available prior to support plate (and reactor vessel) failure; (2) Calculate the time remaining until recovery actions were too late to prevent core damage; (3) Predict future parameter values of each of the MAAP parameter variables; and (4) Detect simulated sensor failure and provide best-value estimates for further processing in the presence of a sensor failure. A variety of accident scenarios for the Zion and Dresden plants were used to train and test the neural network expert system. These included large and small break LOCAs as well as a range of transient events. 3 refs., 1 fig., 1 tab

  16. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Biaobiao Zhang

    2011-01-01

    Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

  17. Neural Mechanisms and Information Processing in Recognition Systems

    Directory of Open Access Journals (Sweden)

    Mamiko Ozaki

    2014-10-01

    Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

  18. Microstructural defects modeling in the Al-Mo system

    International Nuclear Information System (INIS)

    Pascuet, Maria I.; Fernandez, Julian R.; Monti, Ana M.

    2006-01-01

    In this work we have utilized computer simulation techniques to study microstructural defects, such as point defects and interfaces, in the Al-Mo alloy. Such alloy is taken as a model to study the Al(fcc)/U-Mo(bcc) interface. The EAM interatomic potential used has been fitted to the formation energy and lattice constant of the AlMo 3 intermetallic. Formation of vacancies for both components Al and Mo and anti-sites, Al Mo and Mo Al , as well as vacancy migration was studied in this structure. We found that the lowest energy defect complex that preserves stoichiometry is the antisite pair Al Mo +Mo Al , in correspondence with other intermetallics of the same structure. Our results also suggest that the structure of the Al(fcc)/Mo(bcc) interface is unstable, while that of the Al(fcc)/Al 5 Mo interface is stable, as observed experimentally. (author) [es

  19. Ion beam deposition system for depositing low defect density extreme ultraviolet mask blanks

    Science.gov (United States)

    Jindal, V.; Kearney, P.; Sohn, J.; Harris-Jones, J.; John, A.; Godwin, M.; Antohe, A.; Teki, R.; Ma, A.; Goodwin, F.; Weaver, A.; Teora, P.

    2012-03-01

    Extreme ultraviolet lithography (EUVL) is the leading next-generation lithography (NGL) technology to succeed optical lithography at the 22 nm node and beyond. EUVL requires a low defect density reflective mask blank, which is considered to be one of the top two critical technology gaps for commercialization of the technology. At the SEMATECH Mask Blank Development Center (MBDC), research on defect reduction in EUV mask blanks is being pursued using the Veeco Nexus deposition tool. The defect performance of this tool is one of the factors limiting the availability of defect-free EUVL mask blanks. SEMATECH identified the key components in the ion beam deposition system that is currently impeding the reduction of defect density and the yield of EUV mask blanks. SEMATECH's current research is focused on in-house tool components to reduce their contributions to mask blank defects. SEMATECH is also working closely with the supplier to incorporate this learning into a next-generation deposition tool. This paper will describe requirements for the next-generation tool that are essential to realize low defect density EUV mask blanks. The goal of our work is to enable model-based predictions of defect performance and defect improvement for targeted process improvement and component learning to feed into the new deposition tool design. This paper will also highlight the defect reduction resulting from process improvements and the restrictions inherent in the current tool geometry and components that are an impediment to meeting HVM quality EUV mask blanks will be outlined.

  20. Nonlinear dynamical system approaches towards neural prosthesis

    International Nuclear Information System (INIS)

    Torikai, Hiroyuki; Hashimoto, Sho

    2011-01-01

    An asynchronous discrete-state spiking neurons is a wired system of shift registers that can mimic nonlinear dynamics of an ODE-based neuron model. The control parameter of the neuron is the wiring pattern among the registers and thus they are suitable for on-chip learning. In this paper an asynchronous discrete-state spiking neuron is introduced and its typical nonlinear phenomena are demonstrated. Also, a learning algorithm for a set of neurons is presented and it is demonstrated that the algorithm enables the set of neurons to reconstruct nonlinear dynamics of another set of neurons with unknown parameter values. The learning function is validated by FPGA experiments.

  1. Integrating Artificial Immune, Neural and Endrocine Systems in Autonomous Sailing Robots

    Science.gov (United States)

    2010-09-24

    system - Development of an adaptive hormone system capable of changing operation and control of the neural network depending on changing enviromental ...and control of the neural network depending on changing enviromental conditions • First basic design of the MOOP and a simple neural-endocrine based

  2. Sympathetic neural modulation of the immune system

    International Nuclear Information System (INIS)

    Madden, K.S.

    1989-01-01

    One route by which the central nervous system communicates with lymphoid organs in the periphery is through the sympathetic nervous system (SNS). To study SNS regulation of immune activity in vivo, selective removal of peripheral noradrenergic nerve fibers was achieved by administration of the neurotoxic drug, 6-hydroxydopamine (6-OHDA), to adult mice. To assess SNS influence on lymphocyte proliferation in vitro, uptake of 125 iododeoxyuridine ( 125 IUdR), a DNA precursor, was measured following 6-OHDA treatment. Sympathectomy prior to epicutaneous immunization with TNCB did not alter draining lymph nodes (LN) cell proliferation, whereas 6-OHDA treatment before footpad immunization with KLH reduced DNA synthesis in popliteal LN by 50%. In mice which were not deliberately immunized, sympathectomy stimulated 125 IUdR uptake inguinal and axillary LN, spleen, and bone marrow. In vitro, these LN and spleen cells exhibited decreased proliferation responses to the T cell mitogen, concanavalin A (Con A), whereas lipopolysaccharide (LPS)-stimulated IgG secretion was enhanced. Studies examining 51 Cr-labeled lymphocyte trafficking to LN suggested that altered cell migration may play a part in sympathectomy-induced changes in LN cell function

  3. Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

    Directory of Open Access Journals (Sweden)

    Bahita Mohamed

    2011-01-01

    Full Text Available In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.

  4. Fuzzy-Neural Automatic Daylight Control System

    Directory of Open Access Journals (Sweden)

    Grif H. Şt.

    2011-12-01

    Full Text Available The paper presents the design and the tuning of a CMAC controller (Cerebellar Model Articulation Controller implemented in an automatic daylight control application. After the tuning process of the controller, the authors studied the behavior of the automatic lighting control system (ALCS in the presence of luminance disturbances. The luminance disturbances were produced by the authors in night conditions and day conditions as well. During the night conditions, the luminance disturbances were produced by turning on and off a halogen desk lamp. During the day conditions the luminance disturbances were produced in two ways: by daylight contributions changes achieved by covering and uncovering a part of the office window and by turning on and off a halogen desk lamp. During the day conditions the luminance disturbances, produced by turning on and off the halogen lamp, have a smaller amplitude than those produced during the night conditions. The luminance disturbance during the night conditions was a helpful tool to select the proper values of the learning rate for CMAC controller. The luminance disturbances during the day conditions were a helpful tool to demonstrate the right setting of the CMAC controller.

  5. Reliability analysis of a consecutive r-out-of-n: F system based on neural networks

    International Nuclear Information System (INIS)

    Habib, Aziz; Alsieidi, Ragab; Youssef, Ghada

    2009-01-01

    In this paper, we present a generalized Markov reliability and fault-tolerant model, which includes the effects of permanent fault and intermittent fault for reliability evaluations based on neural network techniques. The reliability of a consecutive r-out-of-n: F system was obtained with a three-layer connected neural network represents a discrete time state reliability Markov model of the system. Such that we fed the neural network with the desired reliability of the system under design. Then we extracted the parameters of the system from the neural weights at the convergence of the neural network to the desired reliability. Finally, we obtain simulation results.

  6. Systems biological approach to investigate the lack of familial link between Down's Syndrome & Neural Tube Disorders.

    Science.gov (United States)

    Ragunath, Pk; Abhinand, Pa

    2013-01-01

    Systems Biology involves the study of the interactions of biological systems and ultimately their functions. Down's syndrome (DS) is one of the most common genetic disorders which are caused by complete, or occasionally partial, triplication of chromosome 21, characterized by cognitive and language dysfunction coupled with sensory and neuromotor deficits. Neural Tube Disorders (NTDs) are a group of congenital malformations of the central nervous system and neighboring structures related to defective neural tube closure during the first trimester of pregnancy usually occurring between days 18-29 of gestation. Several studies in the past have provided considerable evidence that abnormal folate and methyl metabolism are associated with onset of DS & NTDs. There is a possible common etiological pathway for both NTDs and Down's syndrome. But, various research studies over the years have indicated very little evidence for familial link between the two disorders. Our research aimed at the gene expression profiling of microarray datasets pertaining to the two disorders to identify genes whose expression levels are significantly altered in these conditions. The genes which were 1.5 fold unregulated and having a p-value disorders were recognized and over representation analysis was carried out for each of the constituent genes. The comprehensive manual analysis of these genes yields a hypothetical understanding of the lack of familial link between DS and NTDs. There were no genes involved with folic acid present in the dense cliques. Only - CBL, EGFR genes were commonly present, which makes the allelic variants of these genes - good candidates for future studies regarding the familial link between DS and NTDs. NTD - Neural Tube Disorders, DS - Down's Syndrome, MTHFR - Methylenetetrahydrofolate reductase, MTRR- 5 - methyltetrahydrofolate-homocysteine methyltransferase reductase.

  7. Neural networks for feedback feedforward nonlinear control systems.

    Science.gov (United States)

    Parisini, T; Zoppoli, R

    1994-01-01

    This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

  8. Dynamics of a neural system with a multiscale architecture

    Science.gov (United States)

    Breakspear, Michael; Stam, Cornelis J

    2005-01-01

    The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

  9. Artificial Neural Network for Location Estimation in Wireless Communication Systems

    Directory of Open Access Journals (Sweden)

    Chien-Sheng Chen

    2012-03-01

    Full Text Available In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS. To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA measurements and the angle of arrival (AOA information to locate MS when three base stations (BSs are available. Artificial neural networks (ANN are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line, based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  10. Artificial neural network for location estimation in wireless communication systems.

    Science.gov (United States)

    Chen, Chien-Sheng

    2012-01-01

    In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  11. Semi-empirical neural network models of controlled dynamical systems

    Directory of Open Access Journals (Sweden)

    Mihail V. Egorchev

    2017-12-01

    Full Text Available A simulation approach is discussed for maneuverable aircraft motion as nonlinear controlled dynamical system under multiple and diverse uncertainties including knowledge imperfection concerning simulated plant and its environment exposure. The suggested approach is based on a merging of theoretical knowledge for the plant with training tools of artificial neural network field. The efficiency of this approach is demonstrated using the example of motion modeling and the identification of the aerodynamic characteristics of a maneuverable aircraft. A semi-empirical recurrent neural network based model learning algorithm is proposed for multi-step ahead prediction problem. This algorithm sequentially states and solves numerical optimization subproblems of increasing complexity, using each solution as initial guess for subsequent subproblem. We also consider a procedure for representative training set acquisition that utilizes multisine control signals.

  12. 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

  13. 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

  14. Development of an accident diagnosis system using a dynamic neural network for nuclear power plants

    International Nuclear Information System (INIS)

    Lee, Seung Jun; Kim, Jong Hyun; Seong, Poong Hyun

    2004-01-01

    In this work, an accident diagnosis system using the dynamic neural network is developed. In order to help the plant operators to quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support system and accident diagnosis systems have been developed. Neural networks have been recognized as a good method to implement an accident diagnosis system. However, conventional accident diagnosis systems that used neural networks did not consider a time factor sufficiently. If the neural network could be trained according to time, it is possible to perform more efficient and detailed accidents analysis. Therefore, this work suggests a dynamic neural network which has different features from existing dynamic neural networks. And a simple accident diagnosis system is implemented in order to validate the dynamic neural network. After training of the prototype, several accident diagnoses were performed. The results show that the prototype can detect the accidents correctly with good performances

  15. Radial basis function (RBF) neural network control for mechanical systems design, analysis and Matlab simulation

    CERN Document Server

    Liu, Jinkun

    2013-01-01

    Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.   This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...

  16. Neural Computations in a Dynamical System with Multiple Time Scales

    Directory of Open Access Journals (Sweden)

    Yuanyuan Mi

    2016-09-01

    Full Text Available Neural systems display rich short-term dynamics at various levels, e.g., spike-frequencyadaptation (SFA at single neurons, and short-term facilitation (STF and depression (STDat neuronal synapses. These dynamical features typically covers a broad range of time scalesand exhibit large diversity in different brain regions. It remains unclear what the computationalbenefit for the brain to have such variability in short-term dynamics is. In this study, we proposethat the brain can exploit such dynamical features to implement multiple seemingly contradictorycomputations in a single neural circuit. To demonstrate this idea, we use continuous attractorneural network (CANN as a working model and include STF, SFA and STD with increasing timeconstants in their dynamics. Three computational tasks are considered, which are persistent activity,adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, andhence cannot be implemented by a single dynamical feature or any combination with similar timeconstants. However, with properly coordinated STF, SFA and STD, we show that the network isable to implement the three computational tasks concurrently. We hope this study will shed lighton the understanding of how the brain orchestrates its rich dynamics at various levels to realizediverse cognitive functions.

  17. Neural network application to aircraft control system design

    Science.gov (United States)

    Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

    1991-01-01

    The feasibility of using artificial neural network as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research identified to enhance the practical applicability of neural networks to flight control design.

  18. Neural network application to aircraft control system design

    Science.gov (United States)

    Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

    1991-01-01

    The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design.

  19. Neural Network Based Intrusion Detection System for Critical Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Ondrej Linda; Milos Manic

    2009-07-01

    Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

  20. Neural Network Target Identification System for False Alarm Reduction

    Science.gov (United States)

    Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

    2009-01-01

    A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

  1. Olfactory systems and neural circuits that modulate predator odor fear

    Directory of Open Access Journals (Sweden)

    Lorey K. Takahashi

    2014-03-01

    Full Text Available When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS and accessory olfactory systems (AOS detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray, paraventricular nucleus of the hypothalamus, and the medial amygdala appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal stress hormone secretion. The medial amygdala also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus appear prominently involve in predator odor fear behavior. The basolateral amygdala, medial hypothalamic nuclei, and medial prefrontal cortex are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator odors activate

  2. Olfactory systems and neural circuits that modulate predator odor fear

    Science.gov (United States)

    Takahashi, Lorey K.

    2014-01-01

    When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS) and accessory olfactory systems (AOS) detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray (DPAG), paraventricular nucleus (PVN) of the hypothalamus, and the medial amygdala (MeA) appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal (HPA) stress hormone secretion. The MeA also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus (VHC) appear prominently involved in predator odor fear behavior. The basolateral amygdala (BLA), medial hypothalamic nuclei, and medial prefrontal cortex (mPFC) are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator

  3. System identification of an unmanned quadcopter system using MRAN neural

    Science.gov (United States)

    Pairan, M. F.; Shamsudin, S. S.

    2017-12-01

    This project presents the performance analysis of the radial basis function neural network (RBF) trained with Minimal Resource Allocating Network (MRAN) algorithm for real-time identification of quadcopter. MRAN’s performance is compared with the RBF with Constant Trace algorithm for 2500 input-output pair data sampling. MRAN utilizes adding and pruning hidden neuron strategy to obtain optimum RBF structure, increase prediction accuracy and reduce training time. The results indicate that MRAN algorithm produces fast training time and more accurate prediction compared with standard RBF. The model proposed in this paper is capable of identifying and modelling a nonlinear representation of the quadcopter flight dynamics.

  4. Monitoring nuclear reactor systems using neural networks and fuzzy logic

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.; Uhrig, R.E.; Mullens, J.A.

    1991-01-01

    A new approach is presented that demonstrates the potential of trained artificial neural networks (ANNs) as generators of membership functions for the purpose of monitoring nuclear reactor systems. ANN's provide a complex-to-simple mapping of reactor parameters in a process analogous to that of measurement. Through such ''virtual measurements'' the value of parameters with operational significance, e.g., control-valve-disk-position, valve-line-up or performance can be determined. In the methodology presented the output of a virtual measuring device is a set of membership functions which independently represent different states of the system. Utilizing a fuzzy logic representation offers the advantage of describing the state of the system in a condensed form, developed through linguistic descriptions and convenient for application in monitoring, diagnostics and generally control algorithms. The developed methodology is applied to the problem of measuring the disk position of the secondary flow control valve of an experimental reactor using data obtained during a start-up. The enhanced noise tolerance of the methodology is clearly demonstrated as well as a method for selecting the actual output. The results suggest that it is possible to construct virtual measuring devices through artificial neural networks mapping dynamic time series to a set of membership functions and thus enhance the capability of monitoring systems. 8 refs., 11 figs., 1 tab

  5. Monitoring nuclear reactor systems using neural networks and fuzzy logic

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.; Uhrig, R.E.; Mullens, J.A.

    1992-01-01

    A new approach is presented that demonstrates the potential of trained artificial neural networks (ANNs) as generators of membership functions for the purpose of monitoring nuclear reactor systems. ANN's provide a complex-to-simple mapping of reactor parameters in a process analogous to that of measurement. Through such virtual measurements the value of parameters with operational significance, e.g., control-valve-disk-position, valve-line-up-or performance can be determined. In the methodology presented the output of virtual measuring device is a set of membership functions which independently represent different states of the system. Utilizing a fuzzy logic representation offers the advantage of describing the state of the system in a condensed form, developed through linguistic descriptions and convenient for application in monitoring, diagnostics and generally control algorithms. The developed methodology is applied to the problem of measuring the disk position of the secondary flow control is clearly demonstrated as well as a method for selecting the actual output. The results suggest that it is possible to construct virtual measuring devices through artificial neural networks mapping dynamic time series to a set of membership functions and thus enhance the capability of monitoring systems

  6. Infrared Radiometric Scanning System for Flexible Package Seal Defects

    Science.gov (United States)

    1973-12-01

    spotted. Pccfcarres tasted Two types of packages currently used for therm- ally processed foods were tested. Both had an outer layer of 0.5-mil...polyester and a middle layer of 0.35- mil aluminum foil. The inner, heat-seal layer was either 3-mil high-dtnsity polyethylene or 3-mil mod- ified...a variety ol causes—including urease . moisture, occluded food fibres or particles, threads, voids and wrinkles. Defects as small as 0.5 mg. of free

  7. Phase transitions in glassy systems via convolutional neural networks

    Science.gov (United States)

    Fang, Chao

    Machine learning is a powerful approach commonplace in industry to tackle large data sets. Most recently, it has found its way into condensed matter physics, allowing for the first time the study of, e.g., topological phase transitions and strongly-correlated electron systems. The study of spin glasses is plagued by finite-size effects due to the long thermalization times needed. Here we use convolutional neural networks in an attempt to detect a phase transition in three-dimensional Ising spin glasses. Our results are compared to traditional approaches.

  8. NEURAL NETWORK SYSTEM FOR DIAGNOSTICS OF AVIATION DESIGNATION PRODUCTS

    Directory of Open Access Journals (Sweden)

    В. Єременко

    2011-02-01

    Full Text Available In the article for solving the classification problem of the technical state of the  object, proposed to use a hybrid neural network with a Kohonen layer and multilayer perceptron. The information-measuring system can be used for standardless diagnostics, cluster analysis and to classify the products which made from composite materials. The advantage of this architecture is flexibility, high performance, ability to use different methods for collecting diagnostic information about unit under test, high reliability of information processing

  9. Fault Tolerant Neural Network for ECG Signal Classification Systems

    Directory of Open Access Journals (Sweden)

    MERAH, M.

    2011-08-01

    Full Text Available The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

  10. Optimizing Markovian modeling of chaotic systems with recurrent neural networks

    International Nuclear Information System (INIS)

    Cechin, Adelmo L.; Pechmann, Denise R.; Oliveira, Luiz P.L. de

    2008-01-01

    In this paper, we propose a methodology for optimizing the modeling of an one-dimensional chaotic time series with a Markov Chain. The model is extracted from a recurrent neural network trained for the attractor reconstructed from the data set. Each state of the obtained Markov Chain is a region of the reconstructed state space where the dynamics is approximated by a specific piecewise linear map, obtained from the network. The Markov Chain represents the dynamics of the time series in its statistical essence. An application to a time series resulted from Lorenz system is included

  11. Examination of neural systems sub-serving facebook "addiction".

    Science.gov (United States)

    Turel, Ofir; He, Qinghua; Xue, Gui; Xiao, Lin; Bechara, Antoine

    2014-12-01

    Because addictive behaviors typically result from violated homeostasis of the impulsive (amygdala-striatal) and inhibitory (prefrontal cortex) brain systems, this study examined whether these systems sub-serve a specific case of technology-related addiction, namely Facebook "addiction." Using a go/no-go paradigm in functional MRI settings, the study examined how these brain systems in 20 Facebook users (M age = 20.3 yr., SD = 1.3, range = 18-23) who completed a Facebook addiction questionnaire, responded to Facebook and less potent (traffic sign) stimuli. The findings indicated that at least at the examined levels of addiction-like symptoms, technology-related "addictions" share some neural features with substance and gambling addictions, but more importantly they also differ from such addictions in their brain etiology and possibly pathogenesis, as related to abnormal functioning of the inhibitory-control brain system.

  12. Is MSAFP still a useful test for detecting open neural tube defects and ventral wall defects in the era of first-trimester and early second-trimester fetal anatomical ultrasounds?

    Science.gov (United States)

    Roman, Ashley S; Gupta, Simi; Fox, Nathan S; Saltzman, Daniel; Klauser, Chad K; Rebarber, Andrei

    2015-01-01

    To evaluate whether maternal serum α-fetoprotein (MSAFP) improves the detection rate for open neural tube defects (ONTDs) and ventral wall defects (VWD) in patients undergoing first-trimester and early second-trimester fetal anatomical survey. A cohort of women undergoing screening between 2005 and 2012 was identified. All patients were offered an ultrasound at between 11 weeks and 13 weeks and 6 days of gestational age for nuchal translucency/fetal anatomy followed by an early second-trimester ultrasound at between 15 weeks and 17 weeks and 6 days of gestational age for fetal anatomy and MSAFP screening. All cases of ONTD and VWD were identified via query of billing and reporting software. Sensitivity and specificity for detection of ONTD/VWD were calculated, and groups were compared using the Fisher exact test, with p met the criteria for inclusion. Overall, 15 cases of ONTD and 17 cases of VWD were identified; 100% of cases were diagnosed by ultrasound prior to 18 weeks' gestation; none were diagnosed via MSAFP screening (p < 0.001). First-trimester and early second-trimester ultrasound had 100% sensitivity and 100% specificity for diagnosing ONTD/VWD. Ultrasound for fetal anatomy during the first and early second trimester detected 100% of ONTD/VWD in our population. MSAFP is not useful as a screening tool for ONTD and VWD in the setting of this ultrasound screening protocol. © 2014 S. Karger AG, Basel.

  13. Neural systems supporting and affecting economically relevant behavior

    Directory of Open Access Journals (Sweden)

    Braeutigam S

    2012-05-01

    Full Text Available Sven BraeutigamOxford Centre for Human Brain Activity, University of Oxford, Oxford, United KingdomAbstract: For about a hundred years, theorists and traders alike have tried to unravel and understand the mechanisms and hidden rules underlying and perhaps determining economically relevant behavior. This review focuses on recent developments in neuroeconomics, where the emphasis is placed on two directions of research: first, research exploiting common experiences of urban inhabitants in industrialized societies to provide experimental paradigms with a broader real-life content; second, research based on behavioral genetics, which provides an additional dimension for experimental control and manipulation. In addition, possible limitations of state-of-the-art neuroeconomics research are addressed. It is argued that observations of neuronal systems involved in economic behavior converge to some extent across the technologies and paradigms used. Conceptually, the data available as of today raise the possibility that neuroeconomic research might provide evidence at the neuronal level for the existence of multiple systems of thought and for the importance of conflict. Methodologically, Bayesian approaches in particular may play an important role in identifying mechanisms and establishing causality between patterns of neural activity and economic behavior.Keywords: neuroeconomics, behavioral genetics, decision-making, consumer behavior, neural system

  14. Neural circuit architecture defects in a Drosophila model of Fragile X syndrome are alleviated by minocycline treatment and genetic removal of matrix metalloproteinase

    Directory of Open Access Journals (Sweden)

    Saul S. Siller

    2011-09-01

    Fragile X syndrome (FXS, caused by loss of the fragile X mental retardation 1 (FMR1 product (FMRP, is the most common cause of inherited intellectual disability and autism spectrum disorders. FXS patients suffer multiple behavioral symptoms, including hyperactivity, disrupted circadian cycles, and learning and memory deficits. Recently, a study in the mouse FXS model showed that the tetracycline derivative minocycline effectively remediates the disease state via a proposed matrix metalloproteinase (MMP inhibition mechanism. Here, we use the well-characterized Drosophila FXS model to assess the effects of minocycline treatment on multiple neural circuit morphological defects and to investigate the MMP hypothesis. We first treat Drosophila Fmr1 (dfmr1 null animals with minocycline to assay the effects on mutant synaptic architecture in three disparate locations: the neuromuscular junction (NMJ, clock neurons in the circadian activity circuit and Kenyon cells in the mushroom body learning and memory center. We find that minocycline effectively restores normal synaptic structure in all three circuits, promising therapeutic potential for FXS treatment. We next tested the MMP hypothesis by assaying the effects of overexpressing the sole Drosophila tissue inhibitor of MMP (TIMP in dfmr1 null mutants. We find that TIMP overexpression effectively prevents defects in the NMJ synaptic architecture in dfmr1 mutants. Moreover, co-removal of dfmr1 similarly rescues TIMP overexpression phenotypes, including cellular tracheal defects and lethality. To further test the MMP hypothesis, we generated dfmr1;mmp1 double null mutants. Null mmp1 mutants are 100% lethal and display cellular tracheal defects, but co-removal of dfmr1 allows adult viability and prevents tracheal defects. Conversely, co-removal of mmp1 ameliorates the NMJ synaptic architecture defects in dfmr1 null mutants, despite the lack of detectable difference in MMP1 expression or gelatinase activity between the single

  15. Using Pulse Width Modulation for Wireless Transmission of Neural Signals in Multichannel Neural Recording Systems

    Science.gov (United States)

    Yin, Ming; Ghovanloo, Maysam

    2013-01-01

    We have used a well-known technique in wireless communication, pulse width modulation (PWM) of time division multiplexed (TDM) signals, within the architecture of a novel wireless integrated neural recording (WINeR) system. We have evaluated the performance of the PWM-based architecture and indicated its accuracy and potential sources of error through detailed theoretical analysis, simulations, and measurements on a setup consisting of a 15-channel WINeR prototype as the transmitter and two types of receivers; an Agilent 89600 vector signal analyzer and a custom wideband receiver, with 36 and 75 MHz of maximum bandwidth, respectively. Furthermore, we present simulation results from a realistic MATLAB-Simulink model of the entire WINeR system to observe the system behavior in response to changes in various parameters. We have concluded that the 15-ch WINeR prototype, which is fabricated in a 0.5-μm standard CMOS process and consumes 4.5 mW from ±1.5 V supplies, can acquire and wirelessly transmit up to 320 k-samples/s to a 75-MHz receiver with 8.4 bits of resolution, which is equivalent to a wireless data rate of ~ 2.26 Mb/s. PMID:19497823

  16. 49 CFR 232.609 - Handling of defective equipment with ECP brake systems.

    Science.gov (United States)

    2010-10-01

    ... (ECP) Braking Systems § 232.609 Handling of defective equipment with ECP brake systems. (a) Ninety-five... systems. 232.609 Section 232.609 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION BRAKE SYSTEM SAFETY STANDARDS FOR FREIGHT...

  17. Electronic transport properties of 1D-defects in graphene and other 2D-systems

    Energy Technology Data Exchange (ETDEWEB)

    Willke, P.; Wenderoth, M. [IV. Physical Institute, Solids and Nanostructures, Georg-August-University Goettingen (Germany); Schneider, M.A. [Lehrstuhl fuer Festkoerperphysik, Universitaet Erlangen-Nuernberg, Erlangen (Germany)

    2017-11-15

    The continuous progress in device miniaturization demands a thorough understanding of the electron transport processes involved. The influence of defects - discontinuities in the perfect and translational invariant crystal lattice - plays a crucial role here. For graphene in particular, they limit the carrier mobility often demanded for applications by contributing additional sources of scattering to the sample. Due to its two-dimensional nature graphene serves as an ideal system to study electron transport in the presence of defects, because one-dimensional defects like steps, grain boundaries and interfaces are easy to characterize and have profound effects on the transport properties. While their contribution to the resistance of a sample can be extracted by carefully conducted transport experiments, scanning probe methods are excellent tools to study the influence of defects locally. In this letter, the authors review the results of scattering at local defects in graphene and other 2D systems by scanning tunneling potentiometry, 4-point-probe microscopy, Kelvin probe force microscopy and conventional transport measurements. Besides the comparison of the different defect resistances important for device fabrication, the underlying scattering mechanisms are discussed giving insight into the general physics of electron scattering at defects. (copyright 2017 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  18. A Gamma Memory Neural Network for System Identification

    Science.gov (United States)

    Motter, Mark A.; Principe, Jose C.

    1992-01-01

    A gamma neural network topology is investigated for a system identification application. A discrete gamma memory structure is used in the input layer, providing delayed values of both the control inputs and the network output to the input layer. The discrete gamma memory structure implements a tapped dispersive delay line, with the amount of dispersion regulated by a single, adaptable parameter. The network is trained using static back propagation, but captures significant features of the system dynamics. The system dynamics identified with the network are the Mach number dynamics of the 16 Foot Transonic Tunnel at NASA Langley Research Center, Hampton, Virginia. The training data spans an operating range of Mach numbers from 0.4 to 1.3.

  19. Artificial neural network analysis of triple effect absorption refrigeration systems

    Energy Technology Data Exchange (ETDEWEB)

    Hajizadeh Aghdam, A. [Department of Mechanical Engineering, Islamic Azad University (Iran, Islamic Republic of)], email: a.hajizadeh@iaukashan.ac.ir; Nazmara, H.; Farzaneh, B. [Department of Mechanical Engineering, University of Tabriz (Iran, Islamic Republic of)], email: h.nazmara@nioec.org, email: b_farzaneh_ms@yahoo.com

    2011-07-01

    In this study, artificial neural networks are utilized to predict the performance of triple effect series and parallel flow absorption refrigeration systems, with lithium bromide/water as the working fluid. Important parameters such as high generator and evaporator temperatures were varied and their effects on the performance characteristics of the refrigeration unit were observed. Absorption refrigeration systems make energy savings possible because they can use heat energy to produce cooling, in place of the electricity used for conventional vapour compression chillers. In addition, non-conventional sources of energy (such as solar, waste heat, and geothermal) can be utilized as their primary energy input. Moreover, absorption units use environmentally friendly working fluid pairs instead of CFCs and HCFCs, which affect the ozone layer. Triple effect absorption cycles were analysed. Results apply for both series and parallel flow systems. A relative preference for parallel-flow over series-flow is also shown.

  20. 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

  1. Hybrid case-neural network (CNN) diagnostic system

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2010-01-01

    recently, the mobile health care has a great attention for the researcher and people all over the world. Case based reasoning (CBR) systems have proved their performance as world wide web (WWW) medical diagnostic systems. They were preferred rather than different reasoning approaches due to their high performance and results' explanation. But, their operations require a complex knowledge acquisition and management processes. On the other hand, it is found that, artificial neural network (ANN) has a great acceptance as a classifier methodology using a little amount of knowledge. But, ANN lacks of an explanation capability .The present research introduces a new web-based hybrid diagnostic system that can use the ANN inside the CBR , cycle.It can provide higher performance for the web diagnostic systems. Besides, the proposed system can be used as a web diagnostic system. It can be applied for diagnosis different types of systems in several domains. It has been applied in diagnosis of the cancer diseases that has a great spreading in recent years as a case of study . However, the suggested system has proved its acceptance in the manner.

  2. Stability Analysis of Neural Networks-Based System Identification

    Directory of Open Access Journals (Sweden)

    Talel Korkobi

    2008-01-01

    Full Text Available This paper treats some problems related to nonlinear systems identification. A stability analysis neural network model for identifying nonlinear dynamic systems is presented. A constrained adaptive stable backpropagation updating law is presented and used in the proposed identification approach. The proposed backpropagation training algorithm is modified to obtain an adaptive learning rate guarantying convergence stability. The proposed learning rule is the backpropagation algorithm under the condition that the learning rate belongs to a specified range defining the stability domain. Satisfying such condition, unstable phenomena during the learning process are avoided. A Lyapunov analysis leads to the computation of the expression of a convenient adaptive learning rate verifying the convergence stability criteria. Finally, the elaborated training algorithm is applied in several simulations. The results confirm the effectiveness of the CSBP algorithm.

  3. The exploitation of neural networks in automotive engine management systems

    Energy Technology Data Exchange (ETDEWEB)

    Shayler, P.J.; Goodman, M. [University of Nottingham (United Kingdom); Ma, T. [Ford Motor Company, Dagenham (United Kingdom). Research and Engineering Centre

    2000-07-01

    The use of electronic engine control systems on spark ignition engines has enabled a high degree of performance optimisation to be achieved. The range of functions performed by these systems, and the level of performance demanded, is rising and thus so are development times and costs. Neural networks have attracted attention as having the potential to simplify software development and improve the performance of this software. The scope and nature of possible applications is described. In particular, the pattern recognition and classification abilities of networks are applied to crankshaft speed fluctuation data for engine-fault diagnosis, and multidimensional mapping capabilities are investigated as an alternative to large 'lookup' tables and calibration functions. (author)

  4. A simple mechanical system for studying adaptive oscillatory neural networks

    DEFF Research Database (Denmark)

    Jouffroy, Guillaume; Jouffroy, Jerome

    Central Pattern Generators (CPG) are oscillatory systems that are responsible for generating rhythmic patterns at the origin of many biological activities such as for example locomotion or digestion. These systems are generally modelled as recurrent neural networks whose parameters are tuned so...... that the network oscillates in a suitable way, this tuning being a non trivial task. It also appears that the link with the physical body that these oscillatory entities control has a fundamental importance, and it seems that most bodies used for experimental validation in the literature (walking robots, lamprey...... a brief description of the Roller-Racer, we present as a preliminary study an RNN-based feed-forward controller whose parameters are obtained through the well-known teacher forcing learning algorithm, extended to learn signals with a continuous component....

  5. Direct process estimation from tomographic data using artificial neural systems

    Science.gov (United States)

    Mohamad-Saleh, Junita; Hoyle, Brian S.; Podd, Frank J.; Spink, D. M.

    2001-07-01

    The paper deals with the goal of component fraction estimation in multicomponent flows, a critical measurement in many processes. Electrical capacitance tomography (ECT) is a well-researched sensing technique for this task, due to its low-cost, non-intrusion, and fast response. However, typical systems, which include practicable real-time reconstruction algorithms, give inaccurate results, and existing approaches to direct component fraction measurement are flow-regime dependent. In the investigation described, an artificial neural network approach is used to directly estimate the component fractions in gas-oil, gas-water, and gas-oil-water flows from ECT measurements. A 2D finite- element electric field model of a 12-electrode ECT sensor is used to simulate ECT measurements of various flow conditions. The raw measurements are reduced to a mutually independent set using principal components analysis and used with their corresponding component fractions to train multilayer feed-forward neural networks (MLFFNNs). The trained MLFFNNs are tested with patterns consisting of unlearned ECT simulated and plant measurements. Results included in the paper have a mean absolute error of less than 1% for the estimation of various multicomponent fractions of the permittivity distribution. They are also shown to give improved component fraction estimation compared to a well known direct ECT method.

  6. p38 MAPK-Mediated Bmi-1 Down-Regulation and Defective Proliferation in ATM-Deficient Neural Stem Cells Can Be Restored by Akt Activation

    Science.gov (United States)

    Kim, Jeesun; Hwangbo, Jeon; Wong, Paul K. Y.

    2011-01-01

    A-T (ataxia telangiectasia) is a genetic disease caused by a mutation in the Atm (A-T mutated) gene that leads to neurodegeneration. Despite an increase in the numbers of studies in this area in recent years, the mechanisms underlying neurodegeneration in human A-T are still poorly understood. Previous studies demonstrated that neural stem cells (NSCs) isolated from the subventricular zone (SVZ) of Atm -/- mouse brains show defective self-renewal and proliferation, which is accompanied by activation of chronic p38 mitogen-activated protein kinase (MAPK) and a lower level of the polycomb protein Bmi-1. However, the mechanism underlying Bmi-1 down-regulation and its relevance to defective proliferation in Atm-/- NSCs remained unclear. Here, we show that over-expression of Bmi-1 increases self-renewal and proliferation of Atm-/- NSCs to normal, indicating that defective proliferation in Atm-/- NSCs is a consequence of down-regulation of Bmi-1. We also demonstrate that epidermal growth factor (EGF)-induced Akt phosphorylation renders Bmi-1 resistant to the proteasomal degradation, leading to its stabilization and accumulation in the nucleus. However, inhibition of the Akt-dependent Bmi-1 stabilizing process by p38 MAPK signaling reduces the levels of Bmi-1. Treatment of the Atm-/- NSCs with a specific p38 MAPK inhibitor SB203580 extended Bmi-1 posttranscriptional turnover and H2A ubiquitination in Atm-/- NSCs. Our observations demonstrate the molecular basis underlying the impairment of self-renewal and proliferation in Atm-/- NSCs through the p38 MAPK-Akt-Bmi-1-p21 signaling pathway. PMID:21305053

  7. Application of neural networks to connectional expert system for identification of transients in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Kim, Wan Joo; Chang, Soon Heung; Roh, Myung Sub

    1991-01-01

    The Back-propagation Neural Network (BPN) algorithm is applied to connectionist expert system for the identification of BWR transients. Several powerful features of neural network-based expert systems over traditional rule-based expert systems are described. The general mapping capability of the neural networks enables to identify transients easily. A number of case studies were performed with emphasis on the applicability of the neural networks to the diagnostic domain. It is revealed that the BPN algorithm can identify transients properly, even when incomplete or untrained symptoms are given. It is also shown that multiple transients are easily identified

  8. Real-time portable system for fabric defect detection using an ARM processor

    Science.gov (United States)

    Fernandez-Gallego, J. A.; Yañez-Puentes, J. P.; Ortiz-Jaramillo, B.; Alvarez, J.; Orjuela-Vargas, S. A.; Philips, W.

    2012-06-01

    Modern textile industry seeks to produce textiles as little defective as possible since the presence of defects can decrease the final price of products from 45% to 65%. Automated visual inspection (AVI) systems, based on image analysis, have become an important alternative for replacing traditional inspections methods that involve human tasks. An AVI system gives the advantage of repeatability when implemented within defined constrains, offering more objective and reliable results for particular tasks than human inspection. Costs of automated inspection systems development can be reduced using modular solutions with embedded systems, in which an important advantage is the low energy consumption. Among the possibilities for developing embedded systems, the ARM processor has been explored for acquisition, monitoring and simple signal processing tasks. In a recent approach we have explored the use of the ARM processor for defects detection by implementing the wavelet transform. However, the computation speed of the preprocessing was not yet sufficient for real time applications. In this approach we significantly improve the preprocessing speed of the algorithm, by optimizing matrix operations, such that it is adequate for a real time application. The system was tested for defect detection using different defect types. The paper is focused in giving a detailed description of the basis of the algorithm implementation, such that other algorithms may use of the ARM operations for fast implementations.

  9. Neural-network hybrid control for antilock braking systems.

    Science.gov (United States)

    Lin, Chih-Min; Hsu, C F

    2003-01-01

    The antilock braking systems are designed to maximize wheel traction by preventing the wheels from locking during braking, while also maintaining adequate vehicle steerability; however, the performance is often degraded under harsh road conditions. In this paper, a hybrid control system with a recurrent neural network (RNN) observer is developed for antilock braking systems. This hybrid control system is comprised of an ideal controller and a compensation controller. The ideal controller, containing an RNN uncertainty observer, is the principal controller; and the compensation controller is a compensator for the difference between the system uncertainty and the estimated uncertainty. Since for dynamic response the RNN has capabilities superior to the feedforward NN, it is utilized for the uncertainty observer. The Taylor linearization technique is employed to increase the learning ability of the RNN. In addition, the on-line parameter adaptation laws are derived based on a Lyapunov function, so the stability of the system can be guaranteed. Simulations are performed to demonstrate the effectiveness of the proposed NN hybrid control system for antilock braking control under various road conditions.

  10. BOOK REVIEW: Theory of Neural Information Processing Systems

    Science.gov (United States)

    Galla, Tobias

    2006-04-01

    It is difficult not to be amazed by the ability of the human brain to process, to structure and to memorize information. Even by the toughest standards the behaviour of this network of about 1011 neurons qualifies as complex, and both the scientific community and the public take great interest in the growing field of neuroscience. The scientific endeavour to learn more about the function of the brain as an information processing system is here a truly interdisciplinary one, with important contributions from biology, computer science, physics, engineering and mathematics as the authors quite rightly point out in the introduction of their book. The role of the theoretical disciplines here is to provide mathematical models of information processing systems and the tools to study them. These models and tools are at the centre of the material covered in the book by Coolen, Kühn and Sollich. The book is divided into five parts, providing basic introductory material on neural network models as well as the details of advanced techniques to study them. A mathematical appendix complements the main text. The range of topics is extremely broad, still the presentation is concise and the book well arranged. To stress the breadth of the book let me just mention a few keywords here: the material ranges from the basics of perceptrons and recurrent network architectures to more advanced aspects such as Bayesian learning and support vector machines; Shannon's theory of information and the definition of entropy are discussed, and a chapter on Amari's information geometry is not missing either. Finally the statistical mechanics chapters cover Gardner theory and the replica analysis of the Hopfield model, not without being preceded by a brief introduction of the basic concepts of equilibrium statistical physics. The book also contains a part on effective theories of the macroscopic dynamics of neural networks. Many dynamical aspects of neural networks are usually hard to find in the

  11. Stereomicroscopic evaluation of dentinal defects induced by new rotary system: "ProTaper NEXT".

    Science.gov (United States)

    Shori, Deepa Deepak; Shenoi, Pratima Ramakrishna; Baig, Arshia R; Kubde, Rajesh; Makade, Chetana; Pandey, Swapnil

    2015-01-01

    The objective of this study was to evaluate dentinal defects formed by new rotary system - Protaper next™ (PTN). Sixty single-rooted premolars were selected. All specimens were decoronated and divided into four groups, each group having 15 specimens. Group I specimens were prepared by Hand K-files (Mani), Group II with ProTaper Universal (PT; Dentsply Maillefer), Group III with Hero Shaper (HS; Micro-Mega, Besancon, France), and Group IV with PTN (Dentsply Maillefer). Roots of each specimen were sectioned at 3, 6, and 9mm from the apex and were then viewed under a stereomicroscope to evaluate presence or absence of dentinal defects. In roots prepared with hand files (HFs) showed lowest percentage of dentinal defects (6.7%); whereas in roots prepared with PT, HS, and PTN it was 40, 66.7, and 26.7%, respectively. There was significant difference between the HS group and the PTN group (P hand instruments induced minimal defects.

  12. Neural mechanism of facilitation system during physical fatigue.

    Directory of Open Access Journals (Sweden)

    Masaaki Tanaka

    Full Text Available An enhanced facilitation system caused by motivational input plays an important role in supporting performance during physical fatigue. We tried to clarify the neural mechanisms of the facilitation system during physical fatigue using magnetoencephalography (MEG and a classical conditioning technique. Twelve right-handed volunteers participated in this study. Participants underwent MEG recording during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. Thereafter, fatigue-inducing maximum handgrip trials were performed for 10 min; the metronome sounds were started 5 min after the beginning of the handgrip trials. The metronome sounds were used as conditioned stimuli and maximum handgrip trials as unconditioned stimuli. The next day, they were randomly assigned to two groups in a single-blinded, two-crossover fashion to undergo two types of MEG recordings, that is, for the control and motivation sessions, during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. The alpha-band event-related desynchronizations (ERDs of the motivation session relative to the control session within the time windows of 500 to 700 and 800 to 900 ms after the onset of handgrip cue sounds were identified in the sensorimotor areas. In addition, the alpha-band ERD within the time window of 400 to 500 ms was identified in the right dorsolateral prefrontal cortex (Brodmann's area 46. The ERD level in the right dorsolateral prefrontal cortex was positively associated with that in the sensorimotor areas within the time window of 500 to 700 ms. These results suggest that the right dorsolateral prefrontal cortex is involved in the neural substrates of the facilitation system and activates the sensorimotor areas during physical fatigue.

  13. Defect-related internal dissipation in mechanical resonators and the study of coupled mechanical systems.

    Energy Technology Data Exchange (ETDEWEB)

    Friedmann, Thomas Aquinas; Czaplewski, David A.; Sullivan, John Patrick; Modine, Normand Arthur; Wendt, Joel Robert; Aslam, Dean (Michigan State University, Lansing, MI); Sepulveda-Alancastro, Nelson (University of Puerto Rico, Mayaguez, PR)

    2007-01-01

    Understanding internal dissipation in resonant mechanical systems at the micro- and nanoscale is of great technological and fundamental interest. Resonant mechanical systems are central to many sensor technologies, and microscale resonators form the basis of a variety of scanning probe microscopies. Furthermore, coupled resonant mechanical systems are of great utility for the study of complex dynamics in systems ranging from biology to electronics to photonics. In this work, we report the detailed experimental study of internal dissipation in micro- and nanomechanical oscillators fabricated from amorphous and crystalline diamond materials, atomistic modeling of dissipation in amorphous, defect-free, and defect-containing crystalline silicon, and experimental work on the properties of one-dimensional and two-dimensional coupled mechanical oscillator arrays. We have identified that internal dissipation in most micro- and nanoscale oscillators is limited by defect relaxation processes, with large differences in the nature of the defects as the local order of the material ranges from amorphous to crystalline. Atomistic simulations also showed a dominant role of defect relaxation processes in controlling internal dissipation. Our studies of one-dimensional and two-dimensional coupled oscillator arrays revealed that it is possible to create mechanical systems that should be ideal for the study of non-linear dynamics and localization.

  14. Development of Geometry Normalized Electromagnetic System (GNES) instrument for metal defect detection

    Science.gov (United States)

    Zakaria, Zakaria; Surbakti, Muhammad Syukri; Syahreza, Saumi; Mat Jafri, Mohd. Zubir; Tan, Kok Chooi

    2017-10-01

    It has been already made, calibrated and tested a geometry normalized electromagnetic system (GNES) for metal defect examination. The GNES has an automatic data acquisition system which supporting the efficiency and accuracy of the measurement. The data will be displayed on the computer monitor as a graphic display then saved automatically in the Microsoft Excel format. The transmitter will transmit the frequency pair (FP) signals i.e. 112.5 Hz and 337.5 Hz; 112.5 Hz and 1012.5 Hz; 112.5 Hz and 3037.5 Hz; 337.5 Hz and 1012.5 Hz; 337.5 Hz and 3037.5 Hz. Simultaneous transmissions of two electromagnetic waves without distortions by the transmitter will induce an eddy current in the metal. This current, in turn, will produce secondary electromagnetic fields which are measured by the receiver together with the primary fields. Measurement of percent change of a vertical component of the fields will give the percent response caused by the metal or the defect. The response examinations were performed by the models with various type of defect for the master curves. The materials of samples as a plate were using Aluminum, Brass, and Copper. The more of the defects is the more reduction of the eddy current response. The defect contrasts were tended to decrease when the more depth of the defect position. The magnitude and phase of the eddy currents will affect the loading on the coil thus its impedance. The defect must interrupt the surface eddy current flow to be detected. Defect lying parallel to the current path will not cause any significant interruption and may not be detected. The main factors which affect the eddy current response are metal conductivity, permeability, frequency, and geometry.

  15. Limb defects associated with major congenital anomalies : Clinical and epidemiological study from the international clearinghouse for birth defects monitoring systems

    NARCIS (Netherlands)

    Rosano, A; Botto, LD; Olney, RS; Khoury, MJ; Ritvanen, A; Goujard, J; Stoll, C; Cocchi, G; Merlob, P; Mutchinick, O; Cornel, MC; Castilla, EE; Martinez-Frias, ML; Zampino, G; Erickson, JD; Mastroiacovo, P

    2000-01-01

    Although limb defects associated with other congenital anomalies are rarely studied, they may provide insights into limb development that may be useful for etiologic studies and public health monitoring, me pooled data from II birth defect registries that are part of the International Clearinghouse

  16. System reliability evaluation of a touch panel manufacturing system with defect rate and reworking

    International Nuclear Information System (INIS)

    Lin, Yi-Kuei; Huang, Cheng-Fu; Chang, Ping-Chen

    2013-01-01

    In recent years, portable consumer electronic products, such as cell phone, GPS, digital camera, tablet PC, and notebook are using touch panel as interface. With the demand of touch panel increases, performance assessment is essential for touch panel production. This paper develops a method to evaluate system reliability of a touch panel manufacturing system (TPMS) with defect rate of each workstation and takes reworking actions into account. The system reliability which evaluates the possibility of demand satisfaction can provide to managers with an understanding of the system capability and can indicate possible improvements. First, we construct a capacitated manufacturing network (CMN) for a TPMS. Second, a decomposition technique is developed to determine the input flow of each workstation based on the CMN. Finally, we generate the minimal capacity vectors that should be provided to satisfy the demand. The system reliability is subsequently evaluated in terms of the minimal capacity vectors. A further decision making issue is discussed to decide a reliable production strategy. -- Graphical abstract: The proposed procedure to evaluate system reliability of the touch panel manufacturing system (TPMS). Highlights: • The system reliability of a touch panel manufacturing system (TPMS) is evaluated. • The reworking actions are taken into account in the TPMS. • A capacitated manufacturing network is constructed for the TPMS. • A procedure is proposed to evaluate system reliability of TPMS

  17. Neural systems language: a formal modeling language for the systematic description, unambiguous communication, and automated digital curation of neural connectivity.

    Science.gov (United States)

    Brown, Ramsay A; Swanson, Larry W

    2013-09-01

    Systematic description and the unambiguous communication of findings and models remain among the unresolved fundamental challenges in systems neuroscience. No common descriptive frameworks exist to describe systematically the connective architecture of the nervous system, even at the grossest level of observation. Furthermore, the accelerating volume of novel data generated on neural connectivity outpaces the rate at which this data is curated into neuroinformatics databases to synthesize digitally systems-level insights from disjointed reports and observations. To help address these challenges, we propose the Neural Systems Language (NSyL). NSyL is a modeling language to be used by investigators to encode and communicate systematically reports of neural connectivity from neuroanatomy and brain imaging. NSyL engenders systematic description and communication of connectivity irrespective of the animal taxon described, experimental or observational technique implemented, or nomenclature referenced. As a language, NSyL is internally consistent, concise, and comprehensible to both humans and computers. NSyL is a promising development for systematizing the representation of neural architecture, effectively managing the increasing volume of data on neural connectivity and streamlining systems neuroscience research. Here we present similar precedent systems, how NSyL extends existing frameworks, and the reasoning behind NSyL's development. We explore NSyL's potential for balancing robustness and consistency in representation by encoding previously reported assertions of connectivity from the literature as examples. Finally, we propose and discuss the implications of a framework for how NSyL will be digitally implemented in the future to streamline curation of experimental results and bridge the gaps among anatomists, imagers, and neuroinformatics databases. Copyright © 2013 Wiley Periodicals, Inc.

  18. Stochastic Neural Field Theory and the System-Size Expansion

    KAUST Repository

    Bressloff, Paul C.

    2010-01-01

    We analyze a master equation formulation of stochastic neurodynamics for a network of synaptically coupled homogeneous neuronal populations each consisting of N identical neurons. The state of the network is specified by the fraction of active or spiking neurons in each population, and transition rates are chosen so that in the thermodynamic or deterministic limit (N → ∞) we recover standard activity-based or voltage-based rate models. We derive the lowest order corrections to these rate equations for large but finite N using two different approximation schemes, one based on the Van Kampen system-size expansion and the other based on path integral methods. Both methods yield the same series expansion of the moment equations, which at O(1/N) can be truncated to form a closed system of equations for the first-and second-order moments. Taking a continuum limit of the moment equations while keeping the system size N fixed generates a system of integrodifferential equations for the mean and covariance of the corresponding stochastic neural field model. We also show how the path integral approach can be used to study large deviation or rare event statistics underlying escape from the basin of attraction of a stable fixed point of the mean-field dynamics; such an analysis is not possible using the system-size expansion since the latter cannot accurately determine exponentially small transitions. © by SIAM.

  19. Decoupling control of vehicle chassis system based on neural network inverse system

    Science.gov (United States)

    Wang, Chunyan; Zhao, Wanzhong; Luan, Zhongkai; Gao, Qi; Deng, Ke

    2018-06-01

    Steering and suspension are two important subsystems affecting the handling stability and riding comfort of the chassis system. In order to avoid the interference and coupling of the control channels between active front steering (AFS) and active suspension subsystems (ASS), this paper presents a composite decoupling control method, which consists of a neural network inverse system and a robust controller. The neural network inverse system is composed of a static neural network with several integrators and state feedback of the original chassis system to approach the inverse system of the nonlinear systems. The existence of the inverse system for the chassis system is proved by the reversibility derivation of Interactor algorithm. The robust controller is based on the internal model control (IMC), which is designed to improve the robustness and anti-interference of the decoupled system by adding a pre-compensation controller to the pseudo linear system. The results of the simulation and vehicle test show that the proposed decoupling controller has excellent decoupling performance, which can transform the multivariable system into a number of single input and single output systems, and eliminate the mutual influence and interference. Furthermore, it has satisfactory tracking capability and robust performance, which can improve the comprehensive performance of the chassis system.

  20. Reliability analysis of digital radiography systems in the testing of real material defects

    International Nuclear Information System (INIS)

    Kanzler, Daniel

    2016-01-01

    Nondestructive testing (ndt) systems are essential for areas in our lives, in which there is a high risk for failures that would induce high costs or even damage to people and the environment (i.e. transportation, energy production, chemical industry). It is necessary to find and to characterise every defect in the material which might jeopardise the functionality of the tested part. But in the praxis the testing system will be used at their limits, i.e. for detecting small defects. Thus, there is a probability that critical defects might be overseen, which must be quantified. The evaluation is especially important for safety-relevant areas. The probability of detection (POD) characteristic is an objective number, which is widely used in these cases. It is used to provide a statement about the tested ndt system. The POD can provide the statement whether the system is working well enough to be accepted to find the defects. The original POD method was developed for one-dimensional defects in thin parts used in the aircraft industry. In reality, the evaluation is a compromise between statistics and costs. On the one hand, the real testing situation should be evaluated for the later use. On the other hand, the evaluation of real defects including the metallography and the comparison with the signals is a complex and expensive task. To find a coordinate system to compare the data is, therefore, an important prerequisite, before starting to evaluate. Therefore, this thesis will present a practical approach. The research community, as well, sees the POD of the real defects as a challenge. It is necessary to extend the one-parametric POD approach by evaluating the whole NDT indication. The area of the NDT indication is one important fact which should be included. The thesis will introduce two new aspects to the calculation of the POD: 1. The area of the indication will be introduced by using a smoothing algorithm, which is based on the known Observer-POD. The Observer

  1. Development of a Fibre-Phased Array Laser-EMAT Ultrasonic System for Defect Inspection

    International Nuclear Information System (INIS)

    Pei, C; Demachi, K; Koyama, K; Uesaka, M; Fukuchi, T; Chen, Z

    2014-01-01

    In this work, a phased array laser ultrasound system with using fibre optic delivery and a custom-designed focusing objective lens has been developed for enhancing the ultrasound generation. The fibre-phased array method is applied to improve the sensitivity and detecting ability of the laser-EMAT system for defect inspection

  2. Scanning Electron Microscope Mapping System Developed for Detecting Surface Defects in Fatigue Specimens

    Science.gov (United States)

    Bonacuse, Peter J.; Kantzos, Peter T.

    2002-01-01

    An automated two-degree-of-freedom specimen positioning stage has been developed at the NASA Glenn Research Center to map and monitor defects in fatigue specimens. This system expedites the examination of the entire gauge section of fatigue specimens so that defects can be found using scanning electron microscopy (SEM). Translation and rotation stages are driven by microprocessor-based controllers that are, in turn, interfaced to a computer running custom-designed software. This system is currently being used to find and record the location of ceramic inclusions in powder metallurgy materials. The mapped inclusions are periodically examined during interrupted fatigue experiments. The number of cycles to initiate cracks from these inclusions and the rate of growth of initiated cracks can then be quantified. This information is necessary to quantify the effect of this type of defect on the durability of powder metallurgy materials. This system was developed with support of the Ultra Safe program.

  3. Genetic defects in the oxidative phosphorylation (OXPHOS) system.

    NARCIS (Netherlands)

    Janssen, R.J.R.J.; Heuvel, L.P.W.J. van den; Smeitink, J.A.M.

    2004-01-01

    The oxidative phosphorylation (OXPHOS) system consists of five multiprotein complexes and two mobile electron carriers embedded in the lipid bilayer of the mitochondrial inner membrane. With the exception of complex II and the mobile carriers, the other parts of the OXPHOS system are under dual

  4. NNETS - NEURAL NETWORK ENVIRONMENT ON A TRANSPUTER SYSTEM

    Science.gov (United States)

    Villarreal, J.

    1994-01-01

    The primary purpose of NNETS (Neural Network Environment on a Transputer System) is to provide users a high degree of flexibility in creating and manipulating a wide variety of neural network topologies at processing speeds not found in conventional computing environments. To accomplish this purpose, NNETS supports back propagation and back propagation related algorithms. The back propagation algorithm used is an implementation of Rumelhart's Generalized Delta Rule. NNETS was developed on the INMOS Transputer. NNETS predefines a Back Propagation Network, a Jordan Network, and a Reinforcement Network to assist users in learning and defining their own networks. The program also allows users to configure other neural network paradigms from the NNETS basic architecture. The Jordan network is basically a feed forward network that has the outputs connected to a pseudo input layer. The state of the network is dependent on the inputs from the environment plus the state of the network. The Reinforcement network learns via a scalar feedback signal called reinforcement. The network propagates forward randomly. The environment looks at the outputs of the network to produce a reinforcement signal that is fed back to the network. NNETS was written for the INMOS C compiler D711B version 1.3 or later (MS-DOS version). A small portion of the software was written in the OCCAM language to perform the communications routing between processors. NNETS is configured to operate on a 4 X 10 array of Transputers in sequence with a Transputer based graphics processor controlled by a master IBM PC 286 (or better) Transputer. A RGB monitor is required which must be capable of 512 X 512 resolution. It must be able to receive red, green, and blue signals via BNC connectors. NNETS is meant for experienced Transputer users only. The program is distributed on 5.25 inch 1.2Mb MS-DOS format diskettes. NNETS was developed in 1991. Transputer and OCCAM are registered trademarks of Inmos Corporation. MS

  5. Symptom based diagnostic system using artificial neural networks

    International Nuclear Information System (INIS)

    Santosh; Vinod, Gopika; Saraf, R.K.

    2003-01-01

    Nuclear power plant experiences a number of transients during its operations. In case of such an undesired plant condition generally known as an initiating event, the operator has to carry out diagnostic and corrective actions. The operator's response may be too late to mitigate or minimize the negative consequences in such scenarios. The objective of this work is to develop an operator support system based on artificial neural networks that will assist the operator to identify the initiating events at the earliest stages of their developments. A symptom based diagnostic system has been developed to investigate the initiating events. Neutral networks are utilized for carrying out the event identification by continuously monitoring process parameters. Whenever an event is detected, the system will display the necessary operator actions along with the initiating event. The system will also show the graphical trend of process parameters that are relevant to the event. This paper describes the features of the software that is used to monitor the reactor. (author)

  6. Adaptive Neural Control for a Class of Outputs Time-Delay Nonlinear Systems

    Directory of Open Access Journals (Sweden)

    Ruliang Wang

    2012-01-01

    Full Text Available This paper considers an adaptive neural control for a class of outputs time-delay nonlinear systems with perturbed or no. Based on RBF neural networks, the radius basis function (RBF neural networks is employed to estimate the unknown continuous functions. The proposed control guarantees that all closed-loop signals remain bounded. The simulation results demonstrate the effectiveness of the proposed control scheme.

  7. Predictive Control of Hydronic Floor Heating Systems using Neural Networks and Genetic Algorithms

    DEFF Research Database (Denmark)

    Vinther, Kasper; Green, Torben; Østergaard, Søren

    2017-01-01

    This paper presents the use a neural network and a micro genetic algorithm to optimize future set-points in existing hydronic floor heating systems for improved energy efficiency. The neural network can be trained to predict the impact of changes in set-points on future room temperatures. Additio...... space is not guaranteed. Evaluation of the performance of multiple neural networks is performed, using different levels of information, and optimization results are presented on a detailed house simulation model....

  8. Algebraic and adaptive learning in neural control systems

    Science.gov (United States)

    Ferrari, Silvia

    A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

  9. A System for Measuring Defect Induced Beam Modulation on Inertial Confinement Fusion-class Laser Optics

    International Nuclear Information System (INIS)

    Runkel, M; Hawley-Fedder, R; Widmayer, C; Williams, W; Weinzapfel, C; Roberts, D

    2005-01-01

    A multi-wavelength laser based system has been constructed to measure defect induced beam modulation (diffraction) from ICF class laser optics. The Nd:YLF-based modulation measurement system (MMS) uses simple beam collimation and imaging to capture diffraction patterns from optical defects onto an 8-bit digital camera at 1053, 527 and 351 nm. The imaging system has a field of view of 4.5 x 2.8 mm 2 and is capable of imaging any plane from 0 to 30 cm downstream from the defect. The system is calibrated using a 477 micron chromium dot on glass for which the downstream diffraction patterns were calculated numerically. Under nominal conditions the system can measure maximum peak modulations of approximately 7:1. An image division algorithm is used to calculate the peak modulation from the diffracted and empty field images after the baseline residual light background is subtracted from both. The peak modulation can then be plotted versus downstream position. The system includes a stage capable of holding optics up to 50 pounds with x and y translation of 40 cm and has been used to measure beam modulation due to solgel coating defects, surface digs on KDP crystals, lenslets in bulk fused silica and laser damage sites mitigated with CO 2 lasers

  10. A System for Measuring Defect Induced Beam Modulation on Inertial Confinement Fusion-class Laser Optics

    Energy Technology Data Exchange (ETDEWEB)

    Runkel, M; Hawley-Fedder, R; Widmayer, C; Williams, W; Weinzapfel, C; Roberts, D

    2005-10-18

    A multi-wavelength laser based system has been constructed to measure defect induced beam modulation (diffraction) from ICF class laser optics. The Nd:YLF-based modulation measurement system (MMS) uses simple beam collimation and imaging to capture diffraction patterns from optical defects onto an 8-bit digital camera at 1053, 527 and 351 nm. The imaging system has a field of view of 4.5 x 2.8 mm{sup 2} and is capable of imaging any plane from 0 to 30 cm downstream from the defect. The system is calibrated using a 477 micron chromium dot on glass for which the downstream diffraction patterns were calculated numerically. Under nominal conditions the system can measure maximum peak modulations of approximately 7:1. An image division algorithm is used to calculate the peak modulation from the diffracted and empty field images after the baseline residual light background is subtracted from both. The peak modulation can then be plotted versus downstream position. The system includes a stage capable of holding optics up to 50 pounds with x and y translation of 40 cm and has been used to measure beam modulation due to solgel coating defects, surface digs on KDP crystals, lenslets in bulk fused silica and laser damage sites mitigated with CO{sub 2} lasers.

  11. Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

    Science.gov (United States)

    Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

    2015-08-01

    A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed

  12. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...

  13. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...... choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...

  14. Gastrointestinal system malformations in children are associated with congenital heart defects.

    Science.gov (United States)

    Orün, Utku Arman; Bilici, Meki; Demirçeken, Fulya G; Tosun, Mahya; Ocal, Burhan; Cavuşoğlu, Yusuf Hakan; Erdoğan, Derya; Senocak, Filiz; Karademir, Selmin

    2011-03-01

    To determine the frequency of congenital heart defects (CHD) in children with gastrointestinal malformations (GISM) and mortality rates in patients with GISM. Two hundred and forty two consecutive children patients with GISM followed up in Pediatric Surgery Clinics of our hospital were examined for cardiovascular anomaly by the Department of Pediatric Cardiology, and the CHD incidence was investigated by examining the records of the patients retrospectively. Chi-square test was used for the statistical analysis of data. Two hundred and forty two patients with gastrointestinal system malformations were included in the study. Of 242 patients, 135 (55.8%) were male and 107 (44.2%) were female, and their age range was 0-15 years. The most frequent GISM were anorectal malformations (43.2%), atresia involving stomach, ileum or colon (21%) and esophageal atresia/tracheoesophageal fistula (18.3%). Congenital heart defects were observed in 28.5% of the participants. The most frequent defects were as follows; atrial septal defect (31 patients, 44.9%) a, ventricular septal defect (17 patients, 24.6%) and patent ductus arteriosus (5 patients, 7.2%). There was no significant difference (p>0.05) in mortality rate in patients with CHD (16.7%) and without CHD (13.3%) undergoing operations for GISM. We would like to emphasize the importance of the earliest possible cardiological evaluation of all patients with gastrointestinal system malformations.

  15. Plasma folate levels and associated factors in women planning to become pregnant in a population with high prevalence of neural tube defects.

    Science.gov (United States)

    Ma, Rui; Wang, Linlin; Jin, Lei; Li, Zhiwen; Ren, Aiguo

    2017-07-17

    Optimal blood folate levels of women before pregnancy are critical to the prevention of neural tube defects (NTDs). However, few studies have focused on blood folate levels of women planning to become pregnant. The aims of this study were to assess plasma folate levels in women who planned to become pregnant in a population with high prevalence of NTDs, to identify factors associated with plasma folate levels, and to evaluate the risk of NTDs at the population level. A total of 2065 women were enrolled at the time of premarital health check-up in two rural counties in northern China from November 2009 to December 2012. Fasting venous blood samples were collected and plasma folate concentrations were measured by microbiological method. The overall median of plasma folate was 10.5 nmol/L. 50% of the women had a plasma folate level below 10.5 nmol/L, a cutoff for megaloblastic anemia, and 88% below 18 nmol/L, a proposed optimal plasma folate level for the prevention of NTDs. Folic acid supplementation was the only factor to be associated with plasma folate concentrations, but only 1.9% of the women reported having taken folic acid supplements. A population risk of 29.3 NTD cases per 10,000 births was predicted. Women who planned to become pregnant had very low plasma folate in the population. Folic acid supplementation was the only factor to be associated with a high plasma folate concentration. High NTD risk would remain if women would get pregnant without having taken folic acid supplements. Birth Defects Research 109:1039-1047, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  16. On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses.

    Science.gov (United States)

    Song, Tao; Xu, Jinbang; Pan, Linqiang

    2015-12-01

    Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neurons (using extended spiking rules) or with 39 neurons (using standard spiking rules) is Turing universal. In this work, this number is improved to 6. Specifically, we construct a Turing universal spiking neural P system with rules on synapses having 6 neurons, which can generate any set of Turing computable natural numbers. As well, it is obtained that spiking neural P system with rules on synapses having less than two neurons are not Turing universal: i) such systems having one neuron can characterize the family of finite sets of natural numbers; ii) the family of sets of numbers generated by the systems having two neurons is included in the family of semi-linear sets of natural numbers.

  17. 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.

  18. Adaptive fuzzy-neural-network control for maglev transportation system.

    Science.gov (United States)

    Wai, Rong-Jong; Lee, Jeng-Dao

    2008-01-01

    A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies.

  19. An alternative respiratory sounds classification system utilizing artificial neural networks

    Directory of Open Access Journals (Sweden)

    Rami J Oweis

    2015-04-01

    Full Text Available Background: Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills. Methods: This work revolves around exploiting autocorrelation in the feature extraction stage. All process stages were implemented in MATLAB. The classification process was performed comparatively using both artificial neural networks (ANNs and adaptive neuro-fuzzy inference systems (ANFIS toolboxes. The methods have been applied to 10 different respiratory sounds for classification. Results: The ANN was superior to the ANFIS system and returned superior performance parameters. Its accuracy, specificity, and sensitivity were 98.6%, 100%, and 97.8%, respectively. The obtained parameters showed superiority to many recent approaches. Conclusions: The promising proposed method is an efficient fast tool for the intended purpose as manifested in the performance parameters, specifically, accuracy, specificity, and sensitivity. Furthermore, it may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.

  20. Flood forecasting within urban drainage systems using NARX neural network.

    Science.gov (United States)

    Abou Rjeily, Yves; Abbas, Oras; Sadek, Marwan; Shahrour, Isam; Hage Chehade, Fadi

    2017-11-01

    Urbanization activity and climate change increase the runoff volumes, and consequently the surcharge of the urban drainage systems (UDS). In addition, age and structural failures of these utilities limit their capacities, and thus generate hydraulic operation shortages, leading to flooding events. The large increase in floods within urban areas requires rapid actions from the UDS operators. The proactivity in taking the appropriate actions is a key element in applying efficient management and flood mitigation. Therefore, this work focuses on developing a flooding forecast system (FFS), able to alert in advance the UDS managers for possible flooding. For a forecasted storm event, a quick estimation of the water depth variation within critical manholes allows a reliable evaluation of the flood risk. The Nonlinear Auto Regressive with eXogenous inputs (NARX) neural network was chosen to develop the FFS as due to its calculation nature it is capable of relating water depth variation in manholes to rainfall intensities. The campus of the University of Lille is used as an experimental site to test and evaluate the FFS proposed in this paper.

  1. PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET

    Directory of Open Access Journals (Sweden)

    S. Devaraju

    2014-04-01

    Full Text Available Intrusion Detection Systems are challenging task for finding the user as normal user or attack user in any organizational information systems or IT Industry. The Intrusion Detection System is an effective method to deal with the kinds of problem in networks. Different classifiers are used to detect the different kinds of attacks in networks. In this paper, the performance of intrusion detection is compared with various neural network classifiers. In the proposed research the four types of classifiers used are Feed Forward Neural Network (FFNN, Generalized Regression Neural Network (GRNN, Probabilistic Neural Network (PNN and Radial Basis Neural Network (RBNN. The performance of the full featured KDD Cup 1999 dataset is compared with that of the reduced featured KDD Cup 1999 dataset. The MATLAB software is used to train and test the dataset and the efficiency and False Alarm Rate is measured. It is proved that the reduced dataset is performing better than the full featured dataset.

  2. Review: the role of neural crest cells in the endocrine system.

    Science.gov (United States)

    Adams, Meghan Sara; Bronner-Fraser, Marianne

    2009-01-01

    The neural crest is a pluripotent population of cells that arises at the junction of the neural tube and the dorsal ectoderm. These highly migratory cells form diverse derivatives including neurons and glia of the sensory, sympathetic, and enteric nervous systems, melanocytes, and the bones, cartilage, and connective tissues of the face. The neural crest has long been associated with the endocrine system, although not always correctly. According to current understanding, neural crest cells give rise to the chromaffin cells of the adrenal medulla, chief cells of the extra-adrenal paraganglia, and thyroid C cells. The endocrine tumors that correspond to these cell types are pheochromocytomas, extra-adrenal paragangliomas, and medullary thyroid carcinomas. Although controversies concerning embryological origin appear to have mostly been resolved, questions persist concerning the pathobiology of each tumor type and its basis in neural crest embryology. Here we present a brief history of the work on neural crest development, both in general and in application to the endocrine system. In particular, we present findings related to the plasticity and pluripotency of neural crest cells as well as a discussion of several different neural crest tumors in the endocrine system.

  3. A neural network method for solving a system of linear variational inequalities

    International Nuclear Information System (INIS)

    Lan Hengyou; Cui Yishun

    2009-01-01

    In this paper, we transmute the solution for a new system of linear variational inequalities to an equilibrium point of neural networks, and by using analytic technique, some sufficient conditions are presented. Further, the estimation of the exponential convergence rates of the neural networks is investigated. The new and useful results obtained in this paper generalize and improve the corresponding results of recent works.

  4. Neural network models for biological waste-gas treatment systems.

    Science.gov (United States)

    Rene, Eldon R; Estefanía López, M; Veiga, María C; Kennes, Christian

    2011-12-15

    This paper outlines the procedure for developing artificial neural network (ANN) based models for three bioreactor configurations used for waste-gas treatment. The three bioreactor configurations chosen for this modelling work were: biofilter (BF), continuous stirred tank bioreactor (CSTB) and monolith bioreactor (MB). Using styrene as the model pollutant, this paper also serves as a general database of information pertaining to the bioreactor operation and important factors affecting gas-phase styrene removal in these biological systems. Biological waste-gas treatment systems are considered to be both advantageous and economically effective in treating a stream of polluted air containing low to moderate concentrations of the target contaminant, over a rather wide range of gas-flow rates. The bioreactors were inoculated with the fungus Sporothrix variecibatus, and their performances were evaluated at different empty bed residence times (EBRT), and at different inlet styrene concentrations (C(i)). The experimental data from these bioreactors were modelled to predict the bioreactors performance in terms of their removal efficiency (RE, %), by adequate training and testing of a three-layered back propagation neural network (input layer-hidden layer-output layer). Two models (BIOF1 and BIOF2) were developed for the BF with different combinations of easily measurable BF parameters as the inputs, that is concentration (gm(-3)), unit flow (h(-1)) and pressure drop (cm of H(2)O). The model developed for the CSTB used two inputs (concentration and unit flow), while the model for the MB had three inputs (concentration, G/L (gas/liquid) ratio, and pressure drop). Sensitivity analysis in the form of absolute average sensitivity (AAS) was performed for all the developed ANN models to ascertain the importance of the different input parameters, and to assess their direct effect on the bioreactors performance. The performance of the models was estimated by the regression

  5. Hierarchical neural network model of the visual system determining figure/ground relation

    Science.gov (United States)

    Kikuchi, Masayuki

    2017-07-01

    One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.

  6. Abstract computation in schizophrenia detection through artificial neural network based systems.

    Science.gov (United States)

    Cardoso, L; Marins, F; Magalhães, R; Marins, N; Oliveira, T; Vicente, H; Abelha, A; Machado, J; Neves, J

    2015-01-01

    Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

  7. Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

    Directory of Open Access Journals (Sweden)

    L. Cardoso

    2015-01-01

    Full Text Available Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason of defective information.

  8. Modeling of the height control system using artificial neural networks

    Directory of Open Access Journals (Sweden)

    A. R Tahavvor

    2016-09-01

    Full Text Available Introduction Automation of agricultural and machinery construction has generally been enhanced by intelligent control systems due to utility and efficiency rising, ease of use, profitability and upgrading according to market demand. A broad variety of industrial merchandise are now supplied with computerized control systems of earth moving processes to be performed by construction and agriculture field vehicle such as grader, backhoe, tractor and scraper machines. A height control machine which is used in measuring base thickness is consisted of two mechanical and electronic parts. The mechanical part is consisted of conveyor belt, main body, electrical engine and invertors while the electronic part is consisted of ultrasonic, wave transmitter and receiver sensor, electronic board, control set, and microcontroller. The main job of these controlling devices consists of the topographic surveying, cutting and filling of elevated and spotted low area, and these actions fundamentally dependent onthe machine's ability in elevation and thickness measurement and control. In this study, machine was first tested and then some experiments were conducted for data collection. Study of system modeling in artificial neural networks (ANN was done for measuring, controlling the height for bases by input variable input vectors such as sampling time, probe speed, conveyer speed, sound wave speed and speed sensor are finally the maximum and minimum probe output vector on various conditions. The result reveals the capability of this procedure for experimental recognition of sensors' behavior and improvement of field machine control systems. Inspection, calibration and response, diagnosis of the elevation control system in combination with machine function can also be evaluated by some extra development of this system. Materials and Methods Designing and manufacture of the planned apparatus classified in three dissimilar, mechanical and electronic module, courses of

  9. DYRK1A-mediated Cyclin D1 Degradation in Neural Stem Cells Contributes to the Neurogenic Cortical Defects in Down Syndrome

    Directory of Open Access Journals (Sweden)

    Sònia Najas

    2015-02-01

    Full Text Available Alterations in cerebral cortex connectivity lead to intellectual disability and in Down syndrome, this is associated with a deficit in cortical neurons that arises during prenatal development. However, the pathogenic mechanisms that cause this deficit have not yet been defined. Here we show that the human DYRK1A kinase on chromosome 21 tightly regulates the nuclear levels of Cyclin D1 in embryonic cortical stem (radial glia cells, and that a modest increase in DYRK1A protein in transgenic embryos lengthens the G1 phase in these progenitors. These alterations promote asymmetric proliferative divisions at the expense of neurogenic divisions, producing a deficit in cortical projection neurons that persists in postnatal stages. Moreover, radial glial progenitors in the Ts65Dn mouse model of Down syndrome have less Cyclin D1, and Dyrk1a is the triplicated gene that causes both early cortical neurogenic defects and decreased nuclear Cyclin D1 levels in this model. These data provide insights into the mechanisms that couple cell cycle regulation and neuron production in cortical neural stem cells, emphasizing that the deleterious effect of DYRK1A triplication in the formation of the cerebral cortex begins at the onset of neurogenesis, which is relevant to the search for early therapeutic interventions in Down syndrome.

  10. Tissue-Specific Methylation of Long Interspersed Nucleotide Element-1 of Homo Sapiens (L1Hs) During Human Embryogenesis and Roles in Neural Tube Defects.

    Science.gov (United States)

    Wang, L; Chang, S; Guan, J; Shangguan, S; Lu, X; Wang, Z; Wu, L; Zou, J; Zhao, H; Bao, Y; Qiu, Z; Niu, B; Zhang, T

    2015-01-01

    Epigenetic regulation of long interspersed nucleotide element-1 (LINE-1) retrotransposition events plays crucial roles during early development. Previously we showed that LINE-1 hypomethylation in neuronal tissues is associated with pathogenesis of neural tube defect (NTD). Herein, we further evaluated LINE-1 Homo sapiens (L1Hs) methylation in tissues derived from three germ layers of stillborn NTD fetuses, to define patterns of tissue specific methylation and site-specific hypomethylation at CpG sites within an L1Hs promoter region. Stable, tissue-specific L1Hs methylation patterns throughout three germ layer lineages of the fetus, placenta, and maternal peripheral blood were observed. Samples from maternal peripheral blood exhibited the highest level of L1Hs methylation (64.95%) and that from placenta showed the lowest (26.82%). Between samples from NTDs and controls, decrease in L1Hs methylation was only significant in NTD-affected brain tissue at 7.35%, especially in females (8.98%). L1Hs hypomethylation in NTDs was also associated with a significant increase in expression level of an L1Hs-encoded transcript in females (r = -0.846, p = 0.004). This could be due to genomic DNA instability and alternation in chromatins accessibility resulted from abnormal L1Hs hypomethylation, as showed in this study with HCT-15 cells treated with methylation inhibitor 5-Aza.

  11. Association of neural tube defects in children of mothers with MTHFR 677TT genotype and abnormal carbohydrate metabolism risk: a case-control study.

    Science.gov (United States)

    Cadenas-Benitez, N M; Yanes-Sosa, F; Gonzalez-Meneses, A; Cerrillos, L; Acosta, D; Praena-Fernandez, J M; Neth, O; Gomez de Terreros, I; Ybot-González, P

    2014-03-26

    Abnormalities in maternal folate and carbohydrate metabolism have both been shown to induce neural tube defects (NTD) in humans and animal models. However, the relationship between these two factors in the development of NTDs remains unclear. Data from mothers of children with spina bifida seen at the Unidad de Espina Bífida del Hospital Infantil Virgen del Rocío (case group) were compared to mothers of healthy children with no NTD (control group) who were randomly selected from patients seen at the outpatient ward in the same hospital. There were 25 individuals in the case group and 41 in the control group. Analysis of genotypes for the methylenetetrahydrofolate reductase (MTHFR) 677CT polymorphism in women with or without risk factors for abnormal carbohydrate metabolism revealed that mothers who were homozygous for the MTHFR 677TT polymorphism and at risk of abnormal carbohydrate metabolism were more likely to have offspring with spina bifida and high levels of homocysteine, compared to the control group. The increased incidence of NTDs in mothers homozygous for the MTHFR 677TT polymorphism and at risk of abnormal carbohydrate metabolism stresses the need for careful metabolic screening in pregnant women, and, if necessary, determination of the MTHFR 677CT genotype in those mothers at risk of developing abnormal carbohydrate metabolism.

  12. A novel neural-wavelet approach for process diagnostics and complex system modeling

    Science.gov (United States)

    Gao, Rong

    Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

  13. Artificial Neural Network-Based System for PET Volume Segmentation

    Directory of Open Access Journals (Sweden)

    Mhd Saeed Sharif

    2010-01-01

    Full Text Available Tumour detection, classification, and quantification in positron emission tomography (PET imaging at early stage of disease are important issues for clinical diagnosis, assessment of response to treatment, and radiotherapy planning. Many techniques have been proposed for segmenting medical imaging data; however, some of the approaches have poor performance, large inaccuracy, and require substantial computation time for analysing large medical volumes. Artificial intelligence (AI approaches can provide improved accuracy and save decent amount of time. Artificial neural networks (ANNs, as one of the best AI techniques, have the capability to classify and quantify precisely lesions and model the clinical evaluation for a specific problem. This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation. ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented. The best number of neurons in the hidden layer is determined according to the experimental results, which is also stated Levenberg-Marquardt backpropagation training algorithm as the best training approach for the proposed application. The proposed intelligent system results are compared with those obtained using conventional techniques including thresholding and clustering based approaches. Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.

  14. A new evolutionary system for evolving artificial neural networks.

    Science.gov (United States)

    Yao, X; Liu, Y

    1997-01-01

    This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

  15. A neural network approach to the study of dynamics and structure of molecular systems

    International Nuclear Information System (INIS)

    Getino, C.; Sumpter, B.G.; Noid, D.W.

    1994-01-01

    Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions

  16. Fault diagnosis for temperature, flow rate and pressure sensors in VAV systems using wavelet neural network

    Energy Technology Data Exchange (ETDEWEB)

    Du, Zhimin; Jin, Xinqiao; Yang, Yunyu [School of Mechanical Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, Shanghai (China)

    2009-09-15

    Wavelet neural network, the integration of wavelet analysis and neural network, is presented to diagnose the faults of sensors including temperature, flow rate and pressure in variable air volume (VAV) systems to ensure well capacity of energy conservation. Wavelet analysis is used to process the original data collected from the building automation first. With three-level wavelet decomposition, the series of characteristic information representing various operation conditions of the system are obtained. In addition, neural network is developed to diagnose the source of the fault. To improve the diagnosis efficiency, three data groups based on several physical models or balances are classified and constructed. Using the data decomposed by three-level wavelet, the neural network can be well trained and series of convergent networks are obtained. Finally, the new measurements to diagnose are similarly processed by wavelet. And the well-trained convergent neural networks are used to identify the operation condition and isolate the source of the fault. (author)

  17. Compensating for Channel Fading in DS-CDMA Communication Systems Employing ICA Neural Network Detectors

    Directory of Open Access Journals (Sweden)

    David Overbye

    2005-06-01

    Full Text Available In this paper we examine the impact of channel fading on the bit error rate of a DS-CDMA communication system. The system employs detectors that incorporate neural networks effecting methods of independent component analysis (ICA, subspace estimation of channel noise, and Hopfield type neural networks. The Rayleigh fading channel model is used. When employed in a Rayleigh fading environment, the ICA neural network detectors that give superior performance in a flat fading channel did not retain this superior performance. We then present a new method of compensating for channel fading based on the incorporation of priors in the ICA neural network learning algorithms. When the ICA neural network detectors were compensated using the incorporation of priors, they give significantly better performance than the traditional detectors and the uncompensated ICA detectors. Keywords: CDMA, Multi-user Detection, Rayleigh Fading, Multipath Detection, Independent Component Analysis, Prior Probability Hebbian Learning, Natural Gradient

  18. Radial basis function neural network for power system load-flow

    International Nuclear Information System (INIS)

    Karami, A.; Mohammadi, M.S.

    2008-01-01

    This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)

  19. A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

    OpenAIRE

    Xiangyu He; Shanghong He

    2014-01-01

    Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then served as the fault determinant to diagnose test faults and the work condition of the hydraulic system was identified. Several typical faults of the hydraulic system were used to verify the fault diagnosis approach. Experiment re...

  20. An artificial neural network for modeling reliability, availability and maintainability of a repairable system

    International Nuclear Information System (INIS)

    Rajpal, P.S.; Shishodia, K.S.; Sekhon, G.S.

    2006-01-01

    The paper explores the application of artificial neural networks to model the behaviour of a complex, repairable system. A composite measure of reliability, availability and maintainability parameters has been proposed for measuring the system performance. The artificial neural network has been trained using past data of a helicopter transportation facility. It is used to simulate behaviour of the facility under various constraints. The insights obtained from results of simulation are useful in formulating strategies for optimal operation of the system

  1. Development of the disable software reporting system on the basis of the neural network

    Science.gov (United States)

    Gavrylenko, S.; Babenko, O.; Ignatova, E.

    2018-04-01

    The PE structure of malicious and secure software is analyzed, features are highlighted, binary sign vectors are obtained and used as inputs for training the neural network. A software model for detecting malware based on the ART-1 neural network was developed, optimal similarity coefficients were found, and testing was performed. The obtained research results showed the possibility of using the developed system of identifying malicious software in computer systems protection systems

  2. Statistical mechanics of complex neural systems and high dimensional data

    International Nuclear Information System (INIS)

    Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

    2013-01-01

    Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks. (paper)

  3. Neutron spectrometry and dosimetry by means of Bonner spheres system and artificial neural networks applying robust design of artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Martinez B, M.R.; Ortiz R, J.M.; Vega C, H.R. [UAZ, Av. Ramon Lopez Velarde No. 801, 98000 Zacatecas (Mexico)

    2006-07-01

    An Artificial Neural Network has been designed, trained and tested to unfold neutron spectra and simultaneously to calculate equivalent doses. A set of 187 neutron spectra compiled by the International Atomic Energy Agency and 13 equivalent doses were used in the artificial neural network designed, trained and tested. In order to design the neural network was used the robust design of artificial neural networks methodology, which assures that the quality of the neural networks takes into account from the design stage. Unless previous works, here, for first time a group of neural networks were designed and trained to unfold 187 neutron spectra and at the same time to calculate 13 equivalent doses, starting from the count rates coming from the Bonner spheres system by using a systematic and experimental strategy. (Author)

  4. Neutron spectrometry and dosimetry by means of Bonner spheres system and artificial neural networks applying robust design of artificial neural networks

    International Nuclear Information System (INIS)

    Martinez B, M.R.; Ortiz R, J.M.; Vega C, H.R.

    2006-01-01

    An Artificial Neural Network has been designed, trained and tested to unfold neutron spectra and simultaneously to calculate equivalent doses. A set of 187 neutron spectra compiled by the International Atomic Energy Agency and 13 equivalent doses were used in the artificial neural network designed, trained and tested. In order to design the neural network was used the robust design of artificial neural networks methodology, which assures that the quality of the neural networks takes into account from the design stage. Unless previous works, here, for first time a group of neural networks were designed and trained to unfold 187 neutron spectra and at the same time to calculate 13 equivalent doses, starting from the count rates coming from the Bonner spheres system by using a systematic and experimental strategy. (Author)

  5. An intelligent system for real time automatic defect inspection on specular coated surfaces

    Science.gov (United States)

    Li, Jinhua; Parker, Johné M.; Hou, Zhen

    2005-07-01

    Product visual inspection is still performed manually or semi automatically in most industries from simple ceramic tile grading to complex automotive body panel paint defect and surface quality inspection. Moreover, specular surfaces present additional challenge to conventional vision systems due to specular reflections, which may mask the true location of objects and lead to incorrect measurements. There are some sophisticated visual inspection methods developed in recent years. Unfortunately, most of them are highly computational. Systems built on those methods are either inapplicable or very costly to achieve real time inspection. In this paper, we describe an integrated low-cost intelligent system developed to automatically capture, extract, and segment defects on specular surfaces with uniform color coatings. The system inspects and locates regular surface defects with lateral dimensions as small as a millimeter. The proposed system is implemented on a group of smart cameras using its on-board processing ability to achieve real time inspection. The experimental results on real test panels demonstrate the effectiveness and robustness of proposed system.

  6. The Decision Support System in the Domain of Casting Defects Diagnosis

    Directory of Open Access Journals (Sweden)

    Wilk-Kołodziejczyk D.

    2014-08-01

    Full Text Available This article presents a computer system for the identification of casting defects using the methodology of Case-Based Reasoning. The system is a decision support tool in the diagnosis of defects in castings and is designed for small and medium-sized plants, where it is not possible to take advantage of multi-criteria data. Without access to complete process data, the diagnosis of casting defects requires the use of methods which process the information based on the experience and observations of a technologist responsible for the inspection of ready castings. The problem, known and studied for a long time, was decided to be solved with a computer system using a CBR (Case-Based Reasoning methodology. The CBR methodology not only allows using expert knowledge accumulated in the implementation phase, but also provides the system with an opportunity to “learn” by collecting new cases solved earlier by this system. The authors present a solution to the system of inference based on the accumulated cases, in which the main principle of operation is searching for similarities between the cases observed and cases stored in the knowledge base.

  7. Influence of defects on the vibrations of rotating systems; Influence de defauts sur le comportement vibratoire des systemes tournants

    Energy Technology Data Exchange (ETDEWEB)

    Lazarus, A. [CEA Saclay, Dept. Modelisation de Systemes et Structures (DEN/DANS/DM2S/SEMT), 91 - Gif sur Yvette (France)

    2008-07-01

    For high rotation speeds, the imperfections (cracks, anisotropy...) of rotating machinery of the energy sector lead to a specific vibratory behavior which can damage the machine. The simulation of rotating machinery are usually realized for systems without defect. The aim of this thesis is to understand the influence of defects and to propose an algorithm to predict the dynamical behavior. In a first part the author studies the simplified rotating oscillators to propose a numerical method in order to taking into account the dynamic of these systems. This method is then applied to real rotating machinery with the Cast3m software. The numerical results are validated with experiments. (A.L.B.)

  8. 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.

  9. Construction of HMI Network System for Individualized Maternity Intervention Service against Birth Defects in Community

    Institute of Scientific and Technical Information of China (English)

    Xu-huai HU

    2007-01-01

    The paper expounds the community maternity service system against birth defects,from the viewpoint of individualized service in family planning. We have utilized modern information technology to develop health management information (HMI) network with individualized maternity, and to establish the community service system for intervention of birth defects. The service system applied the concept of modern health management information to implementing informational management for screening,treatment, following up, outcome monitoring, so as to provide a base for promotion of health, diagnosis, treatment as well as scientific research, with the prenatal screening of Down's syndrome as a model. The introduction to informational network during the processes of service has been carried out with regards to its composition, function and application, while introducing the effects of computerized case record individualized in prevention, management and research of Down's syndrome.

  10. Identification of Complex Dynamical Systems with Neural Networks (2/2)

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

  11. Identification of Complex Dynamical Systems with Neural Networks (1/2)

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

  12. Computational neural network regression model for Host based Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Sunil Kumar Gautam

    2016-09-01

    Full Text Available The current scenario of information gathering and storing in secure system is a challenging task due to increasing cyber-attacks. There exists computational neural network techniques designed for intrusion detection system, which provide security to single machine and entire network's machine. In this paper, we have used two types of computational neural network models, namely, Generalized Regression Neural Network (GRNN model and Multilayer Perceptron Neural Network (MPNN model for Host based Intrusion Detection System using log files that are generated by a single personal computer. The simulation results show correctly classified percentage of normal and abnormal (intrusion class using confusion matrix. On the basis of results and discussion, we found that the Host based Intrusion Systems Model (HISM significantly improved the detection accuracy while retaining minimum false alarm rate.

  13. The theory of dissipative structures of the kinetic system for defects of nonlinear physical system 'metal+loading+irradiation'. Part 3

    International Nuclear Information System (INIS)

    Tarasov, V.A.; Borikov, T.L.; Kryzhanovskaya, T.V.; Chernezhenko, S.A.; Rusov, V.D.

    2007-01-01

    The kinetic system for defects of physical nonlinear system 'metal + load + irradiation' is specified [1, 2, 3]. Developing the approaches offered in [4], where distinctions of mechanisms of radiating creep and areas of their applicability are formalized (depending on external parameters) for fuel and constructional metals, division of kinetic systems for defects of constructional and fuel metals is carrying out. Thus the accent on the autocatalytic features of kinetic system for defects of reactor fuel metals, resulting from the exoenergic autocatalytic character of nuclear fission reactions being the main point defect source is done. In this part of the article the basic attention is given to the kinetic of sink drains for point defects. For kinetic systems of sinks-sources new approaches for the task of boundary conditions are offered. The possible structure of the computer program modelling kinetic system for defects of nonlinear physical system 'metal + load + irradiation' is considered

  14. Differences in neural crest sensitivity to ethanol account for the infrequency of anterior segment defects in the eye compared with craniofacial anomalies in a zebrafish model of fetal alcohol syndrome.

    Science.gov (United States)

    Eason, Jessica; Williams, Antionette L; Chawla, Bahaar; Apsey, Christian; Bohnsack, Brenda L

    2017-09-01

    Ethanol (ETOH) exposure during pregnancy is associated with craniofacial and neurologic abnormalities, but infrequently disrupts the anterior segment of the eye. In these studies, we used zebrafish to investigate differences in the teratogenic effect of ETOH on craniofacial, periocular, and ocular neural crest. Zebrafish eye and neural crest development was analyzed by means of live imaging, TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) assay, immunostaining, detection of reactive oxygen species, and in situ hybridization. Our studies demonstrated that foxd3-positive neural crest cells in the periocular mesenchyme and developing eye were less sensitive to ETOH than sox10-positive craniofacial neural crest cells that form the pharyngeal arches and jaw. ETOH increased apoptosis in the retina, but did not affect survival of periocular and ocular neural crest cells. ETOH also did not increase reactive oxygen species within the eye. In contrast, ETOH increased ventral neural crest apoptosis and reactive oxygen species production in the facial mesenchyme. In the eye and craniofacial region, sod2 showed high levels of expression in the anterior segment and in the setting of Sod2 knockdown, low levels of ETOH decreased migration of foxd3-positive neural crest cells into the developing eye. However, ETOH had minimal effect on the periocular and ocular expression of transcription factors (pitx2 and foxc1) that regulate anterior segment development. Neural crest cells contributing to the anterior segment of the eye exhibit increased ability to withstand ETOH-induced oxidative stress and apoptosis. These studies explain the rarity of anterior segment dysgenesis despite the frequent craniofacial abnormalities in fetal alcohol syndrome. Birth Defects Research 109:1212-1227, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  15. SWANN: The Snow Water Artificial Neural Network Modelling System

    Science.gov (United States)

    Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

    2017-12-01

    Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

  16. Developing a database management system to support birth defects surveillance in Florida.

    Science.gov (United States)

    Salemi, Jason L; Hauser, Kimberlea W; Tanner, Jean Paul; Sampat, Diana; Correia, Jane A; Watkins, Sharon M; Kirby, Russell S

    2010-01-01

    The value of any public health surveillance program is derived from the ways in which data are managed and used to improve the public's health. Although birth defects surveillance programs vary in their case volume, budgets, staff, and objectives, the capacity to operate efficiently and maximize resources remains critical to long-term survival. The development of a fully-integrated relational database management system (DBMS) can enrich a surveillance program's data and improve efficiency. To build upon the Florida Birth Defects Registry--a statewide registry relying solely on linkage of administrative datasets and unconfirmed diagnosis codes-the Florida Department of Health provided funding to the University of South Florida to develop and pilot an enhanced surveillance system in targeted areas with a more comprehensive approach to case identification and diagnosis confirmation. To manage operational and administrative complexities, a DBMS was developed, capable of managing transmission of project data from multiple sources, tracking abstractor time during record reviews, offering tools for defect coding and case classification, and providing reports to DBMS users. Since its inception, the DBMS has been used as part of our surveillance projects to guide the receipt of over 200 case lists and review of 12,924 fetuses and infants (with associated maternal records) suspected of having selected birth defects in over 90 birthing and transfer facilities in Florida. The DBMS has provided both anticipated and unexpected benefits. Automation of the processes for managing incoming case lists has reduced clerical workload considerably, while improving accuracy of working lists for field abstraction. Data quality has improved through more effective use of internal edits and comparisons with values for other data elements, while simultaneously increasing abstractor efficiency in completion of case abstraction. We anticipate continual enhancement to the DBMS in the future

  17. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  18. A Sliding Mode Control-based on a RBF Neural Network for Deburring Industry Robotic Systems

    OpenAIRE

    Tao, Yong; Zheng, Jiaqi; Lin, Yuanchang

    2016-01-01

    A sliding mode control method based on radial basis function (RBF) neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC) has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network par...

  19. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  20. Neural networks for combined control of capacitor banks and voltage regulators in distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Z.; Rizy, D.T.

    1996-02-01

    A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I{sup 2}R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks an d one nine tap line regulator to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

  1. Dynamics of Defects and Dopants in Complex Systems: Si and Oxide Surfaces and Interfaces

    Science.gov (United States)

    Kirichenko, Taras; Yu, Decai; Banarjee, Sanjay; Hwang, Gyeong

    2004-10-01

    Fabrication of forthcoming nanometer scale electronic devices faces many difficulties including formation of extremely shallow and highly doped junctions. At present, ultra-low-energy ion implantation followed by high-temperature thermal annealing is most widely used to fabricate such ultra-shallow junctions. In the process, a great challenge lies in achieving precise control of redistribution and electrical activation of dopant impurities. Native defects (such as vacancies and interstitials) generated during implantation are known to be mainly responsible for the TED and also influence significantly the electrical activation/deactivation. Defect-dopant dynamics is rather well understood in crystalline Si and SiO2. However, little is known about their diffusion and annihilation (or precipitation) at the surfaces and interfaces, despite its growing importance in determining junction profiles as device dimensions get smaller. In this talk, we will present our density functional theory calculation results on the atomic and electronic structure and dynamical behavior of native defects and dopant-defect complexes in disordered/strained Si and oxide systems, such as i) clean and absorbent-modified Si(100) surface and subsurface layers, ii) amorphous-crystalline Si interfaces and iii) amorphous SiO2/Si interfaces. The fundamental understanding and data is essential in developing a comprehensive kinetic model for junction formation, which would contribute greatly in improving current process technologies.

  2. Stereomicroscopic evaluation of dentinal defects induced by new rotary system: “ProTaper NEXT”

    Science.gov (United States)

    Shori, Deepa Deepak; Shenoi, Pratima Ramakrishna; Baig, Arshia R; Kubde, Rajesh; Makade, Chetana; Pandey, Swapnil

    2015-01-01

    Introduction: The objective of this study was to evaluate dentinal defects formed by new rotary system — Protaper next™ (PTN). Materials and Methods: Sixty single-rooted premolars were selected. All specimens were decoronated and divided into four groups, each group having 15 specimens. Group I specimens were prepared by Hand K-files (Mani), Group II with ProTaper Universal (PT; Dentsply Maillefer), Group III with Hero Shaper (HS; Micro-Mega, Besancon, France), and Group IV with PTN (Dentsply Maillefer). Roots of each specimen were sectioned at 3, 6, and 9mm from the apex and were then viewed under a stereomicroscope to evaluate presence or absence of dentinal defects. Results: In roots prepared with hand files (HFs) showed lowest percentage of dentinal defects (6.7%); whereas in roots prepared with PT, HS, and PTN it was 40, 66.7, and 26.7%, respectively. There was significant difference between the HS group and the PTN group (P hand instruments induced minimal defects. PMID:26069406

  3. Automated implementation of rule-based expert systems with neural networks for time-critical applications

    Science.gov (United States)

    Ramamoorthy, P. A.; Huang, Song; Govind, Girish

    1991-01-01

    In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

  4. Fundamentals of computational intelligence neural networks, fuzzy systems, and evolutionary computation

    CERN Document Server

    Keller, James M; Fogel, David B

    2016-01-01

    This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basi function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzz...

  5. Epidemiologic study of neural tube defects in Los Angeles County. II. Etiologic factors in an area with low prevalence at birth

    Energy Technology Data Exchange (ETDEWEB)

    Sever, L.E.

    1982-01-01

    Epidemiologic characteristics of neural tube defect (NTD) births occurring in Los Angeles County, California, residents during the period 1966-1972 are presented. The prevalence at birth was 0.52/1000 births for anencephalus, 0.51/1000 for spina bifida, and 0.08/1000 for encephalocele, rates considered to be low for a predominantly white population. We hypothesized that environmental (nongenetic) factors are of less etiologic importance in a low-prevalence population than in areas or time periods with high prevalence. We tested that hypothesis by examining epidemiologic characteristics of NTDs in Los Angeles County and comparing them with high-prevalence populations. The data did not support a major etiologic role for environmental factors: (1) no significant differences between rates by month of birth or conception; (2) no significant association with maternal age or parity for anencephalus; for spina bifida a significant maternal age effect (P < 0.01) and for encephalocele a parity effect (P < 0.02); and (3) no significant relationship with father's occupational class for either anencephalus or encephalocele but a marginally significant (P < 0.05) inverse association for spina bifida when a statistic based on ordinal relationships was used. Findings supporting the importance of genetic factors in etiology included: (1) a high percentage of males; (2) a higher twin concordance rate than in high-prevalence populations; and (3) an anencephalus rate among blacks comparable with rates for blacks in other United States populations. Our findings in conjunction with those from other areas and times of low prevalence suggest environmental factors play a relatively insignificant role in the etiology of NTDs in such populations.

  6. Knowledge and periconceptional use of folic acid for the prevention of neural tube defects in ethnic communities in the United Kingdom: systematic review and meta-analysis.

    Science.gov (United States)

    Peake, Jordana N; Copp, Andrew J; Shawe, Jill

    2013-07-01

    It is widely accepted that periconceptional supplementation with folic acid can prevent a significant proportion of neural tube defects (NTDs). The present study evaluated how folic acid knowledge and periconceptional use for NTD prevention varies by ethnicity in the United Kingdom (U.K.). A literature search was conducted to identify studies that included assessment of folic acid knowledge or use in U.K. women of different ethnicities. Only research and referenced sources published after 1991, the year of the landmark Medical Research Council's Vitamin Study, were included. A meta-analysis was performed of studies that assessed preconceptional folic acid use in Caucasians and non-Caucasians. Five studies met the inclusion criteria for assessment of knowledge and/or use of folic acid supplements in U.K. women including non-Caucasians. The available evidence indicates that South Asians specifically have less knowledge and lower periconceptional use of folic acid than Caucasians; one study found that West Indian and African women also had lower folic acid uptake. A synthesis of results from three of the studies, in a meta-analysis, shows that Caucasians are almost three times more likely to take folic acid before conception than non-Caucasians. From the limited evidence available, U.K. women of non-Caucasian ethnicity appear to have less knowledge and a lower uptake of folic acid supplementation than Caucasians during the periconceptional period. Implementing targeted, innovative education campaigns together with a mandatory fortification policy, including the fortification of ethnic minority foods, will be required for maximum prevention of folic acid-preventable NTDs across different ethnic groups. Copyright © 2013 Wiley Periodicals, Inc.

  7. Formate supplementation enhances folate-dependent nucleotide biosynthesis and prevents spina bifida in a mouse model of folic acid-resistant neural tube defects.

    Science.gov (United States)

    Sudiwala, Sonia; De Castro, Sandra C P; Leung, Kit-Yi; Brosnan, John T; Brosnan, Margaret E; Mills, Kevin; Copp, Andrew J; Greene, Nicholas D E

    2016-07-01

    The curly tail mouse provides a model for neural tube defects (spina bifida and exencephaly) that are resistant to prevention by folic acid. The major ct gene, responsible for spina bifida, corresponds to a hypomorphic allele of grainyhead-like 3 (Grhl3) but the frequency of NTDs is strongly influenced by modifiers in the genetic background. Moreover, exencephaly in the curly tail strain is not prevented by reinstatement of Grhl3 expression. In the current study we found that expression of Mthfd1L, encoding a key component of mitochondrial folate one-carbon metabolism (FOCM), is significantly reduced in ct/ct embryos compared to a partially congenic wild-type strain. This expression change is not attributable to regulation by Grhl3 or the genetic background at the Mthfd1L locus. Mitochondrial FOCM provides one-carbon units as formate for FOCM reactions in the cytosol. We found that maternal supplementation with formate prevented NTDs in curly tail embryos and also resulted in increased litter size. Analysis of the folate profile of neurulation-stage embryos showed that formate supplementation resulted in an increased proportion of formyl-THF and THF but a reduction in proportion of 5-methyl THF. In contrast, THF decreased and 5-methyl THF was relatively more abundant in the liver of supplemented dams than in controls. In embryos cultured through the period of spinal neurulation, incorporation of labelled thymidine and adenine into genomic DNA was suppressed by supplemental formate, suggesting that de novo folate-dependent biosynthesis of nucleotides (thymidylate and purines) was enhanced. We hypothesise that reduced Mthfd1L expression may contribute to susceptibility to NTDs in the curly tail strain and that formate acts as a one-carbon donor to prevent NTDs. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  8. Diagnosis of mechanical pumping system using neural networks and system parameters analysis

    International Nuclear Information System (INIS)

    Tsai, Tai Ming; Wang, Wei Hui

    2009-01-01

    Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended

  9. Diagnosis of mechanical pumping system using neural networks and system parameters analysis

    Energy Technology Data Exchange (ETDEWEB)

    Tsai, Tai Ming; Wang, Wei Hui [National Taiwan Ocean University, Keelung (China)

    2009-01-15

    Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended

  10. Computer simulation system of neural PID control on nuclear reactor

    International Nuclear Information System (INIS)

    Chen Yuzhong; Yang Kaijun; Shen Yongping

    2001-01-01

    Neural network proportional integral differential (PID) controller on nuclear reactor is designed, and the control process is simulated by computer. The simulation result show that neutral network PID controller can automatically adjust its parameter to ideal state, and good control result can be gotten in reactor control process

  11. A graphical automated detection system to locate hardwood log surface defects using high-resolution three-dimensional laser scan data

    Science.gov (United States)

    Liya Thomas; R. Edward. Thomas

    2011-01-01

    We have developed an automated defect detection system and a state-of-the-art Graphic User Interface (GUI) for hardwood logs. The algorithm identifies defects at least 0.5 inch high and at least 3 inches in diameter on barked hardwood log and stem surfaces. To summarize defect features and to build a knowledge base, hundreds of defects were measured, photographed, and...

  12. Intelligent neural network and fuzzy logic control of industrial and power systems

    Science.gov (United States)

    Kuljaca, Ognjen

    The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

  13. Compact holographic optical neural network system for real-time pattern recognition

    Science.gov (United States)

    Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

    1996-08-01

    One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

  14. System-Level Design of a 64-Channel Low Power Neural Spike Recording Sensor.

    Science.gov (United States)

    Delgado-Restituto, Manuel; Rodriguez-Perez, Alberto; Darie, Angela; Soto-Sanchez, Cristina; Fernandez-Jover, Eduardo; Rodriguez-Vazquez, Angel

    2017-04-01

    This paper reports an integrated 64-channel neural spike recording sensor, together with all the circuitry to process and configure the channels, process the neural data, transmit via a wireless link the information and receive the required instructions. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration algorithm which individually configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by the embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330 μW.

  15. Inductive differentiation of two neural lineages reconstituted in a microculture system from Xenopus early gastrula cells.

    Science.gov (United States)

    Mitani, S; Okamoto, H

    1991-05-01

    Neural induction of ectoderm cells has been reconstituted and examined in a microculture system derived from dissociated early gastrula cells of Xenopus laevis. We have used monoclonal antibodies as specific markers to monitor cellular differentiation from three distinct ectoderm lineages in culture (N1 for CNS neurons from neural tube, Me1 for melanophores from neural crest and E3 for skin epidermal cells from epidermal lineages). CNS neurons and melanophores differentiate when deep layer cells of the ventral ectoderm (VE, prospective epidermis region; 150 cells/culture) and an appropriate region of the marginal zone (MZ, prospective mesoderm region; 5-150 cells/culture) are co-cultured, but not in cultures of either cell type on their own; VE cells cultured alone yield epidermal cells as we have previously reported. The extent of inductive neural differentiation in the co-culture system strongly depends on the origin and number of MZ cells initially added to culture wells. The potency to induce CNS neurons is highest for dorsal MZ cells and sharply decreases as more ventrally located cells are used. The same dorsoventral distribution of potency is seen in the ability of MZ cells to inhibit epidermal differentiation. In contrast, the ability of MZ cells to induce melanophores shows the reverse polarity, ventral to dorsal. These data indicate that separate developmental mechanisms are used for the induction of neural tube and neural crest lineages. Co-differentiation of CNS neurons or melanophores with epidermal cells can be obtained in a single well of co-cultures of VE cells (150) and a wide range of numbers of MZ cells (5 to 100). Further, reproducible differentiation of both neural lineages requires intimate association between cells from the two gastrula regions; virtually no differentiation is obtained when cells from the VE and MZ are separated in a culture well. These results indicate that the inducing signals from MZ cells for both neural tube and neural

  16. Adaptive neural network/expert system that learns fault diagnosis for different structures

    Science.gov (United States)

    Simon, Solomon H.

    1992-08-01

    Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

  17. Prosthetic rehabilitation of severe Siebert′s Class III defect with modified Andrews bridge system

    Directory of Open Access Journals (Sweden)

    Manu Rathee

    2015-01-01

    Full Text Available Prosthetic dentistry involves the replacement of missing and contiguous tissues with artificial substitutes to restore and maintain the oral functions, appearance, and health of the patient. The treatment of edentulous areas with ridge defects poses a challenging task for the dentist. Management of such cases involves a wide range of treatment options comprising mainly of surgical interventions and non surgical techniques such as use of removable, fixed or fixed- removable partial dentures. But each treatment plan undertaken should be customized according to patient needs. A variety of factors such as quality and quantity of existing contiguous hard and soft tissues, systemic condition and economic status of the patient play an important role in treatment planning, clinical outcome and prognosis. This case report presents the restoration of a Seibert′s Class III ridge defect by an economical modification of Andrews Bridge in a 32 Year old patient.

  18. Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

    Science.gov (United States)

    Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

    2014-09-01

    Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

  19. Soft computing integrating evolutionary, neural, and fuzzy systems

    CERN Document Server

    Tettamanzi, Andrea

    2001-01-01

    Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

  20. Identification and adaptive neural network control of a DC motor system with dead-zone characteristics.

    Science.gov (United States)

    Peng, Jinzhu; Dubay, Rickey

    2011-10-01

    In this paper, an adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics (DZC), where two neural networks are proposed to formulate the traditional identification and control approaches. First, a Wiener-type neural network (WNN) is proposed to identify the motor DZC, which formulates the Wiener model with a linear dynamic block in cascade with a nonlinear static gain. Second, a feedforward neural network is proposed to formulate the traditional PID controller, termed as PID-type neural network (PIDNN), which is then used to control and compensate for the DZC. In this way, the DC motor system with DZC is identified by the WNN identifier, which provides model information to the PIDNN controller in order to make it adaptive. Back-propagation algorithms are used to train both neural networks. Also, stability and convergence analysis are conducted using the Lyapunov theorem. Finally, experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone with improved control performance over the conventional PID control. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Psychological Processing in Chronic Pain: A Neural Systems Approach

    OpenAIRE

    Simons, Laura; Elman, Igor; Borsook, David

    2013-01-01

    Our understanding of chronic pain involves complex brain circuits that include sensory, emotional, cognitive and interoceptive processing. The feed-forward interactions between physical (e.g., trauma) and emotional pain and the consequences of altered psychological status on the expression of pain have made the evaluation and treatment of chronic pain a challenge in the clinic. By understanding the neural circuits involved in psychological processes, a mechanistic approach to the implementati...

  2. What Are Neural Tube Defects?

    Science.gov (United States)

    ... are born with spina bifida will have normal intelligence, but some will have learning or intellectual disabilities . 1 There are several common types of spina bifida: Spina bifida occulta (pronounced o- ...

  3. Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

    Science.gov (United States)

    Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

    2017-08-01

    Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a

  4. Emerging economic viability of grid defection in a northern climate using solar hybrid systems

    International Nuclear Information System (INIS)

    Kantamneni, Abhilash; Winkler, Richelle; Gauchia, Lucia; Pearce, Joshua M.

    2016-01-01

    High demand for photovoltaic (PV), battery, and small-scale combined heat and power (CHP) technologies are driving a virtuous cycle of technological improvements and cost reductions in off-grid electric systems that increasingly compete with the grid market. Using a case study in the Upper Peninsula of Michigan, this paper quantifies the economic viability of off-grid PV+battery+CHP adoption and evaluates potential implications for grid-based utility models. The analysis shows that already some households could save money by switching to a solar hybrid off-grid system in comparison to the effective electric rates they are currently paying. Across the region by 2020, 92% of seasonal households and ~75% of year-round households are projected to meet electricity demands with lower costs. Furthermore, ~65% of all Upper Peninsula single-family owner-occupied households will both meet grid parity and be able to afford the systems by 2020. The results imply that economic circumstances could spur a positive feedback loop whereby grid electricity prices continue to rise and increasing numbers of customers choose alternatives (sometimes referred to as a “utility death spiral”), particularly in areas with relatively high electric utility rates. Utility companies and policy makers must take the potential for grid defection seriously when evaluating energy supply strategies. - Highlights: •Quantifies the economic viability of off-grid hybrid photovoltaic (PV) systems. •PV is backed up with batteries and combined heat and power (CHP). •Case study in Michigan by household size (energy demand) and income. •By 2020, majority of single-family owner-occupied households can defect. •To prevent mass-scale grid defection policies needed for grid-tied PV systems.

  5. Integrated Markov-neural reliability computation method: A case for multiple automated guided vehicle system

    International Nuclear Information System (INIS)

    Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep

    2015-01-01

    This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks

  6. Fault detection and classification in electrical power transmission system using artificial neural network.

    Science.gov (United States)

    Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

    2015-01-01

    This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

  7. Adaptive Control of Nonlinear Discrete-Time Systems by Using OS-ELM Neural Networks

    Directory of Open Access Journals (Sweden)

    Xiao-Li Li

    2014-01-01

    Full Text Available As a kind of novel feedforward neural network with single hidden layer, ELM (extreme learning machine neural networks are studied for the identification and control of nonlinear dynamic systems. The property of simple structure and fast convergence of ELM can be shown clearly. In this paper, we are interested in adaptive control of nonlinear dynamic plants by using OS-ELM (online sequential extreme learning machine neural networks. Based on data scope division, the problem that training process of ELM neural network is sensitive to the initial training data is also solved. According to the output range of the controlled plant, the data corresponding to this range will be used to initialize ELM. Furthermore, due to the drawback of conventional adaptive control, when the OS-ELM neural network is used for adaptive control of the system with jumping parameters, the topological structure of the neural network can be adjusted dynamically by using multiple model switching strategy, and an MMAC (multiple model adaptive control will be used to improve the control performance. Simulation results are included to complement the theoretical results.

  8. A Comparative Study of Neural Networks and Fuzzy Systems in Modeling of a Nonlinear Dynamic System

    Directory of Open Access Journals (Sweden)

    Metin Demirtas

    2011-07-01

    Full Text Available The aim of this paper is to compare the neural networks and fuzzy modeling approaches on a nonlinear system. We have taken Permanent Magnet Brushless Direct Current (PMBDC motor data and have generated models using both approaches. The predictive performance of both methods was compared on the data set for model configurations. The paper describes the results of these tests and discusses the effects of changing model parameters on predictive and practical performance. Modeling sensitivity was used to compare for two methods.

  9. Artificial frame filling using adaptive neural fuzzy inference system for particle image velocimetry dataset

    Science.gov (United States)

    Akdemir, Bayram; Doǧan, Sercan; Aksoy, Muharrem H.; Canli, Eyüp; Özgören, Muammer

    2015-03-01

    Liquid behaviors are very important for many areas especially for Mechanical Engineering. Fast camera is a way to observe and search the liquid behaviors. Camera traces the dust or colored markers travelling in the liquid and takes many pictures in a second as possible as. Every image has large data structure due to resolution. For fast liquid velocity, there is not easy to evaluate or make a fluent frame after the taken images. Artificial intelligence has much popularity in science to solve the nonlinear problems. Adaptive neural fuzzy inference system is a common artificial intelligence in literature. Any particle velocity in a liquid has two dimension speed and its derivatives. Adaptive Neural Fuzzy Inference System has been used to create an artificial frame between previous and post frames as offline. Adaptive neural fuzzy inference system uses velocities and vorticities to create a crossing point vector between previous and post points. In this study, Adaptive Neural Fuzzy Inference System has been used to fill virtual frames among the real frames in order to improve image continuity. So this evaluation makes the images much understandable at chaotic or vorticity points. After executed adaptive neural fuzzy inference system, the image dataset increase two times and has a sequence as virtual and real, respectively. The obtained success is evaluated using R2 testing and mean squared error. R2 testing has a statistical importance about similarity and 0.82, 0.81, 0.85 and 0.8 were obtained for velocities and derivatives, respectively.

  10. A modular neural network scheme applied to fault diagnosis in electric power systems.

    Science.gov (United States)

    Flores, Agustín; Quiles, Eduardo; García, Emilio; Morant, Francisco; Correcher, Antonio

    2014-01-01

    This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

  11. A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems

    Directory of Open Access Journals (Sweden)

    Agustín Flores

    2014-01-01

    Full Text Available This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

  12. Development of Laser Based Remote Sensing System for Inner-Concrete Defects

    Science.gov (United States)

    Shimada, Yoshinori; Kotyaev, Oleg

    Laser-based remote sensing using a vibration detection system has been developed using a photorefractive crystal to reduce the effect of concrete surface-roughness. An electric field was applied to the crystal and the reference beam was phase shifted to increase the detection efficiency (DE). The DE increased by factor of 8.5 times compared to that when no voltage and no phase shifting were applied. Vibration from concrete defects can be detected at a distance of 5 m from the system. A vibration-canceling system has also developed that appears to be promising for canceling vibrations between the laser system and the concrete. Finally, we have constructed a prototype system that can be transported in a small truck.

  13. Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network

    International Nuclear Information System (INIS)

    Wei Duqu; Luo Xiaoshu; Zou Yanli

    2008-01-01

    We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network

  14. Fuzzy wavelet plus a quantum neural network as a design base for power system stability enhancement.

    Science.gov (United States)

    Ganjefar, Soheil; Tofighi, Morteza; Karami, Hamidreza

    2015-11-01

    In this study, we introduce an indirect adaptive fuzzy wavelet neural controller (IAFWNC) as a power system stabilizer to damp inter-area modes of oscillations in a multi-machine power system. Quantum computing is an efficient method for improving the computational efficiency of neural networks, so we developed an identifier based on a quantum neural network (QNN) to train the IAFWNC in the proposed scheme. All of the controller parameters are tuned online based on the Lyapunov stability theory to guarantee the closed-loop stability. A two-machine, two-area power system equipped with a static synchronous series compensator as a series flexible ac transmission system was used to demonstrate the effectiveness of the proposed controller. The simulation and experimental results demonstrated that the proposed IAFWNC scheme can achieve favorable control performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Coding of level of ambiguity within neural systems mediating choice.

    Science.gov (United States)

    Lopez-Paniagua, Dan; Seger, Carol A

    2013-01-01

    Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common "fronto-parietal-striatal" network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum).

  16. Child Maltreatment and Neural Systems Underlying Emotion Regulation.

    Science.gov (United States)

    McLaughlin, Katie A; Peverill, Matthew; Gold, Andrea L; Alves, Sonia; Sheridan, Margaret A

    2015-09-01

    The strong associations between child maltreatment and psychopathology have generated interest in identifying neurodevelopmental processes that are disrupted following maltreatment. Previous research has focused largely on neural response to negative facial emotion. We determined whether child maltreatment was associated with neural responses during passive viewing of negative and positive emotional stimuli and effortful attempts to regulate emotional responses. A total of 42 adolescents aged 13 to 19 years, half with exposure to physical and/or sexual abuse, participated. Blood oxygen level-dependent (BOLD) response was measured during passive viewing of negative and positive emotional stimuli and attempts to modulate emotional responses using cognitive reappraisal. Maltreated adolescents exhibited heightened response in multiple nodes of the salience network, including amygdala, putamen, and anterior insula, to negative relative to neutral stimuli. During attempts to decrease responses to negative stimuli relative to passive viewing, maltreatment was associated with greater recruitment of superior frontal gyrus, dorsal anterior cingulate cortex, and frontal pole; adolescents with and without maltreatment down-regulated amygdala response to a similar degree. No associations were observed between maltreatment and neural response to positive emotional stimuli during passive viewing or effortful regulation. Child maltreatment heightens the salience of negative emotional stimuli. Although maltreated adolescents modulate amygdala responses to negative cues to a degree similar to that of non-maltreated youths, they use regions involved in effortful control to a greater degree to do so, potentially because greater effort is required to modulate heightened amygdala responses. These findings are promising, given the centrality of cognitive restructuring in trauma-focused treatments for children. Copyright © 2015 American Academy of Child and Adolescent Psychiatry

  17. Sign Language Recognition System using Neural Network for Digital Hardware Implementation

    International Nuclear Information System (INIS)

    Vargas, Lorena P; Barba, Leiner; Torres, C O; Mattos, L

    2011-01-01

    This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

  18. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  19. An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

    Science.gov (United States)

    Kuo, R J; Wu, P; Wang, C P

    2002-09-01

    Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

  20. Perforator chimerism for the reconstruction of complex defects: A new chimeric free flap classification system.

    Science.gov (United States)

    Kim, Jeong Tae; Kim, Youn Hwan; Ghanem, Ali M

    2015-11-01

    Complex defects present structural and functional challenges to reconstructive surgeons. When compared to multiple free flaps or staged reconstruction, the use of chimeric flaps to reconstruct such defects have many advantages such as reduced number of operative procedures and donor site morbidity as well as preservation of recipient vessels. With increased popularity of perforator flaps, chimeric flaps' harvest and design has benefited from 'perforator concept' towards more versatile and better reconstruction solutions. This article discusses perforator based chimeric flaps and presents a practice based classification system that incorporates the perforator flap concept into "Perforator Chimerism". The authors analyzed a variety of chimeric patterns used in 31 consecutive cases to present illustrative case series and their new classification system. Accordingly, chimeric flaps are classified into four types. Type I: Classical Chimerism, Type II: Anastomotic Chimerism, Type III: Perforator Chimerism and Type IV Mixed Chimerism. Types I on specific source vessel anatomy whilst Type II requires microvascular anastomosis to create the chimeric reconstructive solution. Type III chimeric flaps utilizes the perforator concept to raise two components of tissues without microvascular anastomosis between them. Type IV chimeric flaps are mixed type flaps comprising any combination of Types I to III. Incorporation of the perforator concept in planning and designing chimeric flaps has allowed safe, effective and aesthetically superior reconstruction of complex defects. The new classification system aids reconstructive surgeons and trainees to understand chimeric flaps design, facilitating effective incorporation of this important reconstructive technique into the armamentarium of the reconstruction toolbox. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  1. Distributed neural system for emotional intelligence revealed by lesion mapping.

    Science.gov (United States)

    Barbey, Aron K; Colom, Roberto; Grafman, Jordan

    2014-03-01

    Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease.

  2. Distributed neural system for emotional intelligence revealed by lesion mapping

    Science.gov (United States)

    Colom, Roberto; Grafman, Jordan

    2014-01-01

    Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease. PMID:23171618

  3. The novel mouse mutant, chuzhoi, has disruption of Ptk7 protein and exhibits defects in neural tube, heart and lung development and abnormal planar cell polarity in the ear

    Directory of Open Access Journals (Sweden)

    Paudyal Anju

    2010-08-01

    Full Text Available Abstract Background The planar cell polarity (PCP signalling pathway is fundamental to a number of key developmental events, including initiation of neural tube closure. Disruption of the PCP pathway causes the severe neural tube defect of craniorachischisis, in which almost the entire brain and spinal cord fails to close. Identification of mouse mutants with craniorachischisis has proven a powerful way of identifying molecules that are components or regulators of the PCP pathway. In addition, identification of an allelic series of mutants, including hypomorphs and neomorphs in addition to complete nulls, can provide novel genetic tools to help elucidate the function of the PCP proteins. Results We report the identification of a new N-ethyl-N-nitrosourea (ENU-induced mutant with craniorachischisis, which we have named chuzhoi (chz. We demonstrate that chuzhoi mutant embryos fail to undergo initiation of neural tube closure, and have characteristics consistent with defective convergent extension. These characteristics include a broadened midline and reduced rate of increase of their length-to-width ratio. In addition, we demonstrate disruption in the orientation of outer hair cells in the inner ear, and defects in heart and lung development in chuzhoi mutants. We demonstrate a genetic interaction between chuzhoi mutants and both Vangl2Lp and Celsr1Crsh mutants, strengthening the hypothesis that chuzhoi is involved in regulating the PCP pathway. We demonstrate that chuzhoi maps to Chromosome 17 and carries a splice site mutation in Ptk7. This mutation results in the insertion of three amino acids into the Ptk7 protein and causes disruption of Ptk7 protein expression in chuzhoi mutants. Conclusions The chuzhoi mutant provides an additional genetic resource to help investigate the developmental basis of several congenital abnormalities including neural tube, heart and lung defects and their relationship to disruption of PCP. The chuzhoi mutation

  4. Color Image Encryption Algorithm Based on TD-ERCS System and Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Kun Zhang

    2015-01-01

    Full Text Available In order to solve the security problem of transmission image across public networks, a new image encryption algorithm based on TD-ERCS system and wavelet neural network is proposed in this paper. According to the permutation process and the binary XOR operation from the chaotic series by producing TD-ERCS system and wavelet neural network, it can achieve image encryption. This encryption algorithm is a reversible algorithm, and it can achieve original image in the rule inverse process of encryption algorithm. Finally, through computer simulation, the experiment results show that the new chaotic encryption algorithm based on TD-ERCS system and wavelet neural network is valid and has higher security.

  5. Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

    CERN Document Server

    Melin, Patricia

    2012-01-01

    This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

  6. Computer Vision System For Locating And Identifying Defects In Hardwood Lumber

    Science.gov (United States)

    Conners, Richard W.; Ng, Chong T.; Cho, Tai-Hoon; McMillin, Charles W.

    1989-03-01

    This paper describes research aimed at developing an automatic cutup system for use in the rough mills of the hardwood furniture and fixture industry. In particular, this paper describes attempts to create the vision system that will power this automatic cutup system. There are a number of factors that make the development of such a vision system a challenge. First there is the innate variability of the wood material itself. No two species look exactly the same, in fact, they can have a significant visual difference in appearance among species. Yet a truly robust vision system must be able to handle a variety of such species, preferably with no operator intervention required when changing from one species to another. Secondly, there is a good deal of variability in the definition of what constitutes a removable defect. The hardwood furniture and fixture industry is diverse in the nature of the products that it makes. The products range from hardwood flooring to fancy hardwood furniture, from simple mill work to kitchen cabinets. Thus depending on the manufacturer, the product, and the quality of the product the nature of what constitutes a removable defect can and does vary. The vision system must be such that it can be tailored to meet each of these unique needs, preferably without any additional program modifications. This paper will describe the vision system that has been developed. It will assess the current system capabilities, and it will discuss the directions for future research. It will be argued that artificial intelligence methods provide a natural mechanism for attacking this computer vision application.

  7. Neural network modeling of nonlinear systems based on Volterra series extension of a linear model

    Science.gov (United States)

    Soloway, Donald I.; Bialasiewicz, Jan T.

    1992-01-01

    A Volterra series approach was applied to the identification of nonlinear systems which are described by a neural network model. A procedure is outlined by which a mathematical model can be developed from experimental data obtained from the network structure. Applications of the results to the control of robotic systems are discussed.

  8. Absolute stability of nonlinear systems with time delays and applications to neural networks

    Directory of Open Access Journals (Sweden)

    Xinzhi Liu

    2001-01-01

    Full Text Available In this paper, absolute stability of nonlinear systems with time delays is investigated. Sufficient conditions on absolute stability are derived by using the comparison principle and differential inequalities. These conditions are simple and easy to check. In addition, exponential stability conditions for some special cases of nonlinear delay systems are discussed. Applications of those results to cellular neural networks are presented.

  9. An overview of erosion corrosion models and reliability assessment for corrosion defects in piping system

    International Nuclear Information System (INIS)

    Srividya, A.; Suresh, H.N.; Verma, A.K.; Gopika, V.; Santosh

    2006-01-01

    Piping systems are part of passive structural elements in power plants. The analysis of the piping systems and their quantification in terms of failure probability is of utmost importance. The piping systems may fail due to various degradation mechanisms like thermal fatigue, erosion-corrosion, stress corrosion cracking and vibration fatigue. On examination of previous results, erosion corrosion was more prevalent and wall thinning is a time dependent phenomenon. The paper is intended to consolidate the work done by various investigators on erosion corrosion in estimating the erosion corrosion rate and reliability predictions. A comparison of various erosion corrosion models is made. The reliability predictions based on remaining strength of corroded pipelines by wall thinning is also attempted. Variables in the limit state functions are modelled using normal distributions and Reliability assessment is carried out using some of the existing failure pressure models. A steady state corrosion rate is assumed to estimate the corrosion defect and First Order Reliability Method (FORM) is used to find the probability of failure associated with corrosion defects over time using the software for Component Reliability evaluation (COMREL). (author)

  10. An Improved Recurrent Neural Network for Complex-Valued Systems of Linear Equation and Its Application to Robotic Motion Tracking.

    Science.gov (United States)

    Ding, Lei; Xiao, Lin; Liao, Bolin; Lu, Rongbo; Peng, Hua

    2017-01-01

    To obtain the online solution of complex-valued systems of linear equation in complex domain with higher precision and higher convergence rate, a new neural network based on Zhang neural network (ZNN) is investigated in this paper. First, this new neural network for complex-valued systems of linear equation in complex domain is proposed and theoretically proved to be convergent within finite time. Then, the illustrative results show that the new neural network model has the higher precision and the higher convergence rate, as compared with the gradient neural network (GNN) model and the ZNN model. Finally, the application for controlling the robot using the proposed method for the complex-valued systems of linear equation is realized, and the simulation results verify the effectiveness and superiorness of the new neural network for the complex-valued systems of linear equation.

  11. Efficient decoding with steady-state Kalman filter in neural interface systems.

    Science.gov (United States)

    Malik, Wasim Q; Truccolo, Wilson; Brown, Emery N; Hochberg, Leigh R

    2011-02-01

    The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5±0.5 s (mean ±s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25±3 single units by a factor of 7.0±0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems.

  12. Requirement of mouse BCCIP for neural development and progenitor proliferation.

    Directory of Open Access Journals (Sweden)

    Yi-Yuan Huang

    Full Text Available Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.

  13. 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

  14. Artificial neural systems for interpretation and inversion of seismic data

    Science.gov (United States)

    Calderon-Macias, Carlos

    The goal of this work is to investigate the feasibility of using neural network (NN) models for solving geophysical exploration problems. First, a feedforward neural network (FNN) is used to solve inverse problems. The operational characteristics of a FNN are primarily controlled by a set of weights and a nonlinear function that performs a mapping between two sets of data. In a process known as training, the FNN weights are iteratively adjusted to perform the mapping. After training, the computed weights encode important features of the data that enable one pattern to be distinguished from another. Synthetic data computed from an ensemble of earth models and the corresponding models provide the training data. Two training methods are studied: the backpropagation method which is a gradient scheme, and a global optimization method called very fast simulated annealing (VFSA). A trained network is then used to predict models from new data (e.g., data from a new location) in a one-step procedure. The application of this method to the problems of obtaining formation resistivities and layer thicknesses from resistivity sounding data and 1D velocity models from seismic data shows that trained FNNs produce reasonably accurate earth models when observed data are input to the FNNs. In a second application, a FNN is used for automating the NMO correction process of seismic reflection data. The task of the FNN is to map CMP data at control locations along a seismic line into subsurface velocities. The network is trained while the velocity analyses are performed at the control locations. Once trained, the computed weights are used as an operator that acts on the remaining CMP data as a velocity interpolator, resulting in a fast method for NMO correction. The second part of this dissertation describes the application of a Hopfield neural network (HNN) to the problems of deconvolution and multiple attenuation. In these applications, the unknown parameters (reflection coefficients

  15. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L [School of Aeronautics and Astronautics, Tongji University, Shanghai (China); Zhang, Y Y [Chinese-German School of Postgraduate Studies, Tongji University (China); Ding, L [Chinese-German School of Postgraduate Studies, Tongji University (China)

    2006-10-15

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  16. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Science.gov (United States)

    Wang, L.; Zhang, Y. Y.; Ding, L.

    2006-10-01

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  17. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    International Nuclear Information System (INIS)

    Wang, L; Zhang, Y Y; Ding, L

    2006-01-01

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module

  18. ISC feedforward control of gasoline engine. Adaptive system using neural network; Jidoshayo gasoline engine no ISC feedforward seigyo. Neural network wo mochiita tekioka

    Energy Technology Data Exchange (ETDEWEB)

    Kinugawa, N; Morita, S; Takiyama, T [Osaka City University, Osaka (Japan)

    1997-10-01

    For fuel economy and a good driver`s feeling, it is necessary for idle-speed to keep at a constant low speed. But keeping low speed has danger of engine stall when the engine torque is disturbed by the alternator, and so on. In this paper, adaptive feedforward idle-speed control system against electrical loads was investigated. This system was based on the reversed tansfer functions of the object system, and a neural network was used to adapt this system for aging. Then, this neural network was also used for creating feedforward table map. Good experimental results were obtained. 2 refs., 11 figs.

  19. Evolving networks and the development of neural systems

    International Nuclear Information System (INIS)

    Johnson, Samuel; Marro, J; Torres, Joaquín J

    2010-01-01

    It is now generally assumed that the heterogeneity of most networks in nature probably arises via preferential attachment of some sort. However, the origin of various other topological features, such as degree–degree correlations and related characteristics, is often not clear, and they may arise from specific functional conditions. We show how it is possible to analyse a very general scenario in which nodes can gain or lose edges according to any (e.g., nonlinear) function of local and/or global degree information. Applying our method to two rather different examples of brain development—synaptic pruning in humans and the neural network of the worm C. Elegans—we find that simple biologically motivated assumptions lead to very good agreement with experimental data. In particular, many nontrivial topological features of the worm's brain arise naturally at a critical point

  20. Neural Networks for Self-tuning Control Systems

    Directory of Open Access Journals (Sweden)

    A. Noriega Ponce

    2004-01-01

    Full Text Available In this paper, we presented a self-tuning control algorithm based on a three layers perceptron type neural network. The proposed algorithm is advantageous in the sense that practically a previous training of the net is not required and some changes in the set-point are generally enough to adjust the learning coefficient. Optionally, it is possible to introduce a self-tuning mechanism of the learning coefficient although by the moment it is not possible to give final conclusions about this possibility. The proposed algorithm has the special feature that the regulation error instead of the net output error is retropropagated for the weighting coefficients modifications. 

  1. System Identification Using Multilayer Differential Neural Networks: A New Result

    Directory of Open Access Journals (Sweden)

    J. Humberto Pérez-Cruz

    2012-01-01

    Full Text Available In previous works, a learning law with a dead zone function was developed for multilayer differential neural networks. This scheme requires strictly a priori knowledge of an upper bound for the unmodeled dynamics. In this paper, the learning law is modified in such a way that this condition is relaxed. By this modification, the tuning process is simpler and the dead-zone function is not required anymore. On the basis of this modification and by using a Lyapunov-like analysis, a stronger result is here demonstrated: the exponential convergence of the identification error to a bounded zone. Besides, a value for upper bound of such zone is provided. The workability of this approach is tested by a simulation example.

  2. Sampling inspection for the evaluation of time-dependent reliability of deteriorating systems under imperfect defect detection

    International Nuclear Information System (INIS)

    Kuniewski, Sebastian P.; Weide, Johannes A.M. van der; Noortwijk, Jan M. van

    2009-01-01

    The paper presents a sampling-inspection strategy for the evaluation of time-dependent reliability of deteriorating systems, where the deterioration is assumed to initiate at random times and at random locations. After initiation, defects are weakening the system's resistance. The system becomes unacceptable when at least one defect reaches a critical depth. The defects are assumed to initiate at random times modeled as event times of a non-homogeneous Poisson process (NHPP) and to develop according to a non-decreasing time-dependent gamma process. The intensity rate of the NHPP is assumed to be a combination of a known time-dependent shape function and an unknown proportionality constant. When sampling inspection (i.e. inspection of a selected subregion of the system) results in a number of defect initiations, Bayes' theorem can be used to update prior beliefs about the proportionality constant of the NHPP intensity rate to the posterior distribution. On the basis of a time- and space-dependent Poisson process for the defect initiation, an adaptive Bayesian model for sampling inspection is developed to determine the predictive probability distribution of the time to failure. A potential application is, for instance, the inspection of a large vessel or pipeline suffering pitting/localized corrosion in the oil industry. The possibility of imperfect defect detection is also incorporated in the model.

  3. A Knowledge-Based System For Analysis, Intervention Planning and Prevention of Defects in Immovable Cultural Heritage Objects and Monuments

    Science.gov (United States)

    Valach, J.; Cacciotti, R.; Kuneš, P.; ČerÅanský, M.; Bláha, J.

    2012-04-01

    The paper presents a project aiming to develop a knowledge-based system for documentation and analysis of defects of cultural heritage objects and monuments. The MONDIS information system concentrates knowledge on damage of immovable structures due to various causes, and preventive/remedial actions performed to protect/repair them, where possible. The currently built system is to provide for understanding of causal relationships between a defect, materials, external load, and environment of built object. Foundation for the knowledge-based system will be the systemized and formalized knowledge on defects and their mitigation acquired in the process of analysis of a representative set of cases documented in the past. On the basis of design comparability, used technologies, materials and the nature of the external forces and surroundings, the developed software system has the capacity to indicate the most likely risks of new defect occurrence or the extension of the existing ones. The system will also allow for a comparison of the actual failure with similar cases documented and will propose a suitable technical intervention plan. The system will provide conservationists, administrators and owners of historical objects with a toolkit for defect documentation for their objects. Also, advanced artificial intelligence methods will offer accumulated knowledge to users and will also enable them to get oriented in relevant techniques of preventive interventions and reconstructions based on similarity with their case.

  4. Mathematical Modeling of Radiant Heat Transfer in Mirror Systems Considering Deep Reflecting Surface Defects

    Directory of Open Access Journals (Sweden)

    V. V. Leonov

    2014-01-01

    Full Text Available When designing large-sized mirror concentrating systems (MCS for high-temperature solar power plants, one must have at disposal reasonably reliable and economical methods and tools, making it possible to analyze its characteristics, to predict them depending on the operation conditions and accordingly to choose the most suitable system for the solution of particular task.Experimental determination of MCS characteristics requires complicated and expensive experimentation, having significant limitations on interpretation of the results, as well as limitations imposed due to the size of the structure. Therefore it is of particular interest to develop a mathematical model capable of estimating power characteristics of MCS considering the influence of operating conditions, design features, roughness and other surface defects.For efficient solution of the tasks the model must ensure simulation of solar radiant flux as well as simulation of geometrical and optical characteristics of reflection surface and their interaction. In this connection a statistical mathematical model of radiation heat exchange based on use of Monte Carlo methods and Finite Element Method was developed and realized in the software complex, making it possible to determine main characteristics of the MCS.In this paper the main attention is given to definition of MCS radiation characteristics with account for deep reflecting surface defects (cavities, craters. Deep cavities are not typical for MCS, but their occurrence is possible during operation as a result of erosion or any physical damage. For example, for space technology it is primarily micrometeorite erosion.

  5. The ubiquitin-proteasome system and autophagy are defective in the taurine-deficient heart.

    Science.gov (United States)

    Jong, Chian Ju; Ito, Takashi; Schaffer, Stephen W

    2015-12-01

    Taurine depletion leads to impaired mitochondrial function, as characterized by reduced ATP production and elevated superoxide generation. These defects can fundamentally alter cardiomyocyte function and if left unchanged can result in cell death. To protect against these stresses, cardiomyocytes possess quality control processes, such as the ubiquitin-proteasome system (UPS) and autophagy, which can rejuvenate cells through the degradation of damaged proteins and organelles. Hence, the present study tested the hypothesis that reactive oxygen species generated by damaged mitochondria initiates UPS and autophagy in the taurine-deficient heart. Using transgenic mice lacking the taurine transporter (TauTKO) as a model of taurine deficiency, it was shown that the levels of ubiquitinated protein were elevated, an effect associated with a decrease in ATP-dependent 26S β5 proteasome activity. Treating the TauTKO mouse with the mitochondria-specific antioxidant, mitoTEMPO, largely abolished the increase in ubiquitinated protein content. The TauTKO heart was also associated with impaired autophagy, characterized by an increase in the initiator, Beclin-1, and autophagosome content, but a defect in the generation of active autophagolysosomes. Although mitoTEMPO treatment only restores the oxidative balance within the mitochondria, it appeared to completely disrupt the crosstalk between the damaged mitochondria and the quality control processes. Thus, mitochondrial oxidative stress is the main trigger initiating the quality control systems in the taurine-deficient heart. We conclude that the activation of the UPS and autophagy is another fundamental function of mitochondria.

  6. Systemic Teriparatide Administration Promotes Osseous Regeneration of an Intrabony Defect: A Case Report.

    Science.gov (United States)

    Bashutski, Jill D; Kinney, Janet S; Benavides, Erika; Maitra, Samopriyo; Braun, Thomas M; Giannobile, William V; McCauley, Laurie K; Eber, Robert M

    2012-05-01

    Teriparatide comprises the first 34 amino acids of parathyroid hormone and is a systemic anabolic agent that is Food and Drug Administration approved for the treatment of osteoporosis but not for periodontitis. To our knowledge, this is the first clinical case report to document the treatment of a patient with severe periodontitis using an open-flap debridement procedure in conjunction with teriparatide. A 45-year-old female patient was diagnosed with severe chronic periodontitis, including the presence of an intrabony defect on tooth #6. She received open-flap debridement surgery in conjunction with daily systemic administration of 20 µg teriparatide, oral vitamin D, and calcium supplements for 6 weeks. Radiographic, clinical, gingival crevicular fluid (pyridinoline cross-linked carboxy-terminal propeptide of type I procollagen, procollagen type 1 N-propeptide, and osteocalcin), and serum parameters (parathyroid hormone, bone alkaline phosphatase, calcium, and 25-hydroxyvitamin D) were assessed. Treatment outcomes were evaluated over 4 years, with successful radiographic and clinical results throughout the follow-up period. Teriparatide administration in conjunction with traditional open-flap debridement surgery offers potential for the treatment of severe intrabony defects resulting from chronic periodontitis.

  7. Study on algorithm of process neural network for soft sensing in sewage disposal system

    Science.gov (United States)

    Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

    2006-11-01

    A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

  8. A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

    Science.gov (United States)

    Huang, Darong; Bai, Xing-Rong

    Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

  9. Neural Stem Cells: Implications for the Conventional Radiotherapy of Central Nervous System Malignancies

    International Nuclear Information System (INIS)

    Barani, Igor J.; Benedict, Stanley H.; Lin, Peck-Sun

    2007-01-01

    Advances in basic neuroscience related to neural stem cells and their malignant counterparts are challenging traditional models of central nervous system tumorigenesis and intrinsic brain repair. Neurogenesis persists into adulthood predominantly in two neurogenic centers: subventricular zone and subgranular zone. Subventricular zone is situated adjacent to lateral ventricles and subgranular zone is confined to the dentate gyrus of the hippocampus. Neural stem cells not only self-renew and differentiate along multiple lineages in these regions, but also contribute to intrinsic brain plasticity and repair. Ionizing radiation can depopulate these exquisitely sensitive regions directly or impair in situ neurogenesis by indirect, dose-dependent and inflammation-mediated mechanisms, even at doses <2 Gy. This review discusses the fundamental neural stem cell concepts within the framework of cumulative clinical experience with the treatment of central nervous system malignancies using conventional radiotherapy

  10. Towards an Irritable Bowel Syndrome Control System Based on Artificial Neural Networks

    Science.gov (United States)

    Podolski, Ina; Rettberg, Achim

    To solve health problems with medical applications that use complex algorithms is a trend nowadays. It could also be a chance to help patients with critical problems caused from nerve irritations to overcome them and provide a better living situation. In this paper a system for monitoring and controlling the nerves from the intestine is described on a theoretical basis. The presented system could be applied to the irritable bowel syndrome. For control a neural network is used. The advantages for using a neural network for the control of irritable bowel syndrome are the adaptation and learning. These two aspects are important because the syndrome behavior varies from patient to patient and have also concerning the time a lot of variations with respect to each patient. The developed neural network is implemented and can be simulated. Therefore, it can be shown how the network monitor and control the nerves for individual input parameters.

  11. Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle.

    Science.gov (United States)

    Xu, Bin; Yang, Chenguang; Pan, Yongping

    2015-10-01

    This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.

  12. Biological neural networks as model systems for designing future parallel processing computers

    Science.gov (United States)

    Ross, Muriel D.

    1991-01-01

    One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.

  13. Neural mirroring and social interaction: Motor system involvement during action observation relates to early peer cooperation.

    Science.gov (United States)

    Endedijk, H M; Meyer, M; Bekkering, H; Cillessen, A H N; Hunnius, S

    2017-04-01

    Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other's actions and is therefore considered important for social interaction. Still, to date, it is unknown whether interindividual differences in neural mirroring play a role in interpersonal coordination during different instances of social interaction. A relation between neural mirroring and interpersonal coordination has particularly relevant implications for early childhood, since successful early interaction with peers is predictive of a more favorable social development. We examined the relation between neural mirroring and children's interpersonal coordination during peer interaction using EEG and longitudinal behavioral data. Results showed that 4-year-old children with higher levels of motor system involvement during action observation (as indicated by lower beta-power) were more successful in early peer cooperation. This is the first evidence for a relation between motor system involvement during action observation and interpersonal coordination during other instances of social interaction. The findings suggest that interindividual differences in neural mirroring are related to interpersonal coordination and thus successful social interaction. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  15. Estimating the behavior of RC beams strengthened with NSM system using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Seyed Rohollah Hosseini Vaez

    2017-12-01

    Full Text Available In the last decade, conventional materials such as steel and concrete are being replaced by fiber reinforced polymer (FRP materials for the strengthening of concrete structures. Among the strengthening techniques based on Fiber Reinforced Polymer composites, the use of near-surface mounted (NSM FRP rods is emerging as a promising technology for increasing flexural and shear strength of deficient concrete, masonry and timber members. An artificial neural network is an information processing tool that is inspired by the way biological nervous systems (such as the brain process the information. The key element of this tool is the novel structure of the information processing system. In engineering applications, a neural network can be a vector mapper which maps an input vector to an output one. In the present study, a new approach is developed to predict the behavior of strengthened concrete beam using a large number of experimental data by applying artificial neural networks. Having parameters used as input nodes in ANN modeling such as elastic modulus of the FRP reinforcement, the ratio of the steel longitudinal reinforcement, dimensions of the beam section, the ratio of the NSM-FRP reinforcement and characteristics of concrete, the output node was the flexural strength of beams. The idealized neural network was employed to generate empirical charts and equations to be used in design. The aim of this study is to investigate the behavior of strengthened RC beam using artificial neural networks.

  16. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    Science.gov (United States)

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  17. Prevalência e distribuição espacial de defeitos do tubo neural no Estado de São Paulo, Brasil, antes e após a fortificação de farinhas com ácido fólico Prevalencia y distribución espacial de defectos del tubo neural en el Estado de São Paulo, Brasil, antes y después del enriquecimiento de harinas con ácido fólico Prevalence and spatial distribution of neural tube defects in São Paulo State, Brazil, before and after folic acid flour fortification

    Directory of Open Access Journals (Sweden)

    Elizabeth Fujimori

    2013-01-01

    Full Text Available Estudo transversal que analisou prevalência e distribuição espacial de defeitos do tubo neural, antes e após a fortificação das farinhas de trigo e milho com ácido fólico no Estado de São Paulo, Brasil, com uso do Sistema de Informações sobre Nascidos Vivos (SINASC. São apresentadas prevalências segundo características maternas por meio de odds ratio (OR e intervalos de 95% de confiança (IC95%. Para análise temporal e espacial, foram utilizados, respectivamente, regressão polinomial e mapas com suavização bayesiana empírica. A prevalência diminuiu 35%, de 0,57 para 0,37 por mil nascidos vivos após a fortificação (OR = 0,65; IC95%: 0,59-0,72. Verificou-se redução para mulheres de todas as idades (exceto Estudio transversal que analizó la prevalencia y distribución espacial de defectos del tubo neural, antes y después del enriquecimiento de las harinas de trigo y maíz con ácido fólico en el Estado de Sao Paulo, Brasil, con el uso del Sistema de Información sobre Nacidos Vivos (SINASC. Se presentaron prevalencias, según características maternas, mediante odds ratio (OR e intervalos de un 95% de confianza (IC95%. Para un análisis temporal y espacial, fueron utilizados, respectivamente, regresión polinomial y mapas con suavizamiento bayesiano empírico. La prevalencia disminuyó un 35%, de 0,57 a 0,37 por mil nacidos vivos tras el enriquecimiento (OR = 0,65; IC95%: 0,59-0,72. Se verificó la reducción en mujeres de todas las edades (excepto This cross-sectional study analyzed the prevalence and spatial distribution of neural tube defects before and after folic acid flour fortification. The study used the Information System on Live Births (SINASC and presented prevalence rates according to maternal characteristics with odds ratios (OR and 95% confidence intervals (95%CI. Polynomial regression was used in time trend analysis and empirical Bayesian smoothed maps for spatial analysis. Total prevalence of neural tube

  18. Real-time camera-based face detection using a modified LAMSTAR neural network system

    Science.gov (United States)

    Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

    2003-03-01

    This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.

  19. Differences between otolith- and semicircular canal-activated neural circuitry in the vestibular system.

    Science.gov (United States)

    Uchino, Yoshio; Kushiro, Keisuke

    2011-12-01

    In the last two decades, we have focused on establishing a reliable technique for focal stimulation of vestibular receptors to evaluate neural connectivity. Here, we summarize the vestibular-related neuronal circuits for the vestibulo-ocular reflex, vestibulocollic reflex, and vestibulospinal reflex arcs. The focal stimulating technique also uncovered some hidden neural mechanisms. In the otolith system, we identified two hidden neural mechanisms that enhance otolith receptor sensitivity. The first is commissural inhibition, which boosts sensitivity by incorporating inputs from bilateral otolith receptors, the existence of which was in contradiction to the classical understanding of the otolith system but was observed in the utricular system. The second mechanism, cross-striolar inhibition, intensifies the sensitivity of inputs from both sides of receptive cells across the striola in a single otolith sensor. This was an entirely novel finding and is typically observed in the saccular system. We discuss the possible functional meaning of commissural and cross-striolar inhibition. Finally, our focal stimulating technique was applied to elucidate the different constructions of axonal projections from each vestibular receptor to the spinal cord. We also discuss the possible function of the unique neural connectivity observed in each vestibular receptor system. Copyright © 2011 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

  20. Container-code recognition system based on computer vision and deep neural networks

    Science.gov (United States)

    Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

    2018-04-01

    Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

  1. Fiber-Optic Defect and Damage Locator System for Wind Turbine Blades

    Energy Technology Data Exchange (ETDEWEB)

    Dr. Vahid Sotoudeh; Dr. Richard J. Black; Dr. Behzad Moslehi; Mr. Aleks Plavsic

    2010-10-30

    IFOS in collaboration with Auburn University demonstrated the feasibility of a Fiber Bragg Grating (FBG) integrated sensor system capable of providing real time in-situ defect detection, localization and quantification of damage. In addition, the system is capable of validating wind turbine blade structural models, using recent advances in non-contact, non-destructive dynamic testing of composite structures. This new generation method makes it possible to analyze wind turbine blades not only non-destructively, but also without physically contacting or implanting intrusive electrical elements and transducers into the structure. Phase I successfully demonstrated the feasibility of the technology with the construction of a 1.5 kHz sensor interrogator and preliminary instrumentation and testing of both composite material coupons and a wind turbine blade.

  2. Neural coding in the visual system of Drosophila melanogaster: How do small neural populations support visually guided behaviours?

    Science.gov (United States)

    Dewar, Alex D M; Wystrach, Antoine; Philippides, Andrew; Graham, Paul

    2017-10-01

    All organisms wishing to survive and reproduce must be able to respond adaptively to a complex, changing world. Yet the computational power available is constrained by biology and evolution, favouring mechanisms that are parsimonious yet robust. Here we investigate the information carried in small populations of visually responsive neurons in Drosophila melanogaster. These so-called 'ring neurons', projecting to the ellipsoid body of the central complex, are reported to be necessary for complex visual tasks such as pattern recognition and visual navigation. Recently the receptive fields of these neurons have been mapped, allowing us to investigate how well they can support such behaviours. For instance, in a simulation of classic pattern discrimination experiments, we show that the pattern of output from the ring neurons matches observed fly behaviour. However, performance of the neurons (as with flies) is not perfect and can be easily improved with the addition of extra neurons, suggesting the neurons' receptive fields are not optimised for recognising abstract shapes, a conclusion which casts doubt on cognitive explanations of fly behaviour in pattern recognition assays. Using artificial neural networks, we then assess how easy it is to decode more general information about stimulus shape from the ring neuron population codes. We show that these neurons are well suited for encoding information about size, position and orientation, which are more relevant behavioural parameters for a fly than abstract pattern properties. This leads us to suggest that in order to understand the properties of neural systems, one must consider how perceptual circuits put information at the service of behaviour.

  3. Study on application of adaptive fuzzy control and neural network in the automatic leveling system

    Science.gov (United States)

    Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng

    2015-04-01

    This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.

  4. A Neural Networks Based Operation Guidance System for Procedure Presentation and Validation

    International Nuclear Information System (INIS)

    Seung, Kun Mo; Lee, Seung Jun; Seong, Poong Hyun

    2006-01-01

    In this paper, a neural network based operator support system is proposed to reduce operator's errors in abnormal situations in nuclear power plants (NPPs). There are many complicated situations, in which regular and suitable operations should be done by operators accordingly. In order to regulate and validate operators' operations, it is necessary to develop an operator support system which includes computer based procedures with the functions for operation validation. Many computerized procedures systems (CPS) have been recently developed. Focusing on the human machine interface (HMI) design and procedures' computerization, most of CPSs used various methodologies to enhance system's convenience, reliability and accessibility. Other than only showing procedures, the proposed system integrates a simple CPS and an operation validation system (OVS) by using artificial neural network (ANN) for operational permission and quantitative evaluation

  5. Directive Nanophysical Cues for Regenerative Neural Cell Systems

    Science.gov (United States)

    Ayres, Virginia; Tiryaki, Volkan Mujdat; Ahmed, Ijaz; Shreiber, David

    Until recently, implantables such as stents, probes, wafers and scaffolds have been viewed as passive vehicles for the delivery of physical, pharmacological and cellular interventions. Recent research, however, indicates that the physical environments that implantables present supply directive cues in their own right that work in conjunction with biochemical cues and produce a jointly-directed outcome. We will present our research in CNS repairs using advanced scanning probe microscopy, electron microscopies and contact angle measurements to quantitatively describe the nanoscale elasticity, surface roughness, work of adhesion and surface polarity for investigation of scaffold environments. We will also present