efficient neural conversion: Topics by Science.gov

Sample records for efficient neural conversion

Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.

PubMed

Rueckauer, Bodo; Lungu, Iulia-Alexandra; Hu, Yuhuang; Pfeiffer, Michael; Liu, Shih-Chii

2017-01-01

Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.
Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification

PubMed Central

Rueckauer, Bodo; Lungu, Iulia-Alexandra; Hu, Yuhuang; Pfeiffer, Michael; Liu, Shih-Chii

2017-01-01

Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications. PMID:29375284
Configurable analog-digital conversion using the neural engineering framework

PubMed Central

Mayr, Christian G.; Partzsch, Johannes; Noack, Marko; Schüffny, Rene

2014-01-01

Efficient Analog-Digital Converters (ADC) are one of the mainstays of mixed-signal integrated circuit design. Besides the conventional ADCs used in mainstream ICs, there have been various attempts in the past to utilize neuromorphic networks to accomplish an efficient crossing between analog and digital domains, i.e., to build neurally inspired ADCs. Generally, these have suffered from the same problems as conventional ADCs, that is they require high-precision, handcrafted analog circuits and are thus not technology portable. In this paper, we present an ADC based on the Neural Engineering Framework (NEF). It carries out a large fraction of the overall ADC process in the digital domain, i.e., it is easily portable across technologies. The analog-digital conversion takes full advantage of the high degree of parallelism inherent in neuromorphic networks, making for a very scalable ADC. In addition, it has a number of features not commonly found in conventional ADCs, such as a runtime reconfigurability of the ADC sampling rate, resolution and transfer characteristic. PMID:25100933
Generation of H1 PAX6WT/EGFP reporter cells to purify PAX6 positive neural stem/progenitor cells.

PubMed

Wu, Wei; Liu, Juli; Su, Zhenghui; Li, Zhonghao; Ma, Ning; Huang, Ke; Zhou, Tiancheng; Wang, Linli

2018-08-25

Neural conversion from human pluripotent cells (hPSCs) is a potential therapy to neurological disease in the future. However, this is still limited by efficiency and stability of existed protocols used for neural induction from hPSCs. To overcome this obstacle, we developed a reporter system to screen PAX6 + neural progenitor/stem cells using transcription activator like effector nuclease (TALEN). We found that knock-in 2 A-EGFP cassette into PAX6 exon of human embryonic stem cells H1 with TALEN-based homology recombination could establish PAX6 WT/EGFP H1 reporter cell line fast and efficiently. This reporter cell line could differentiate into PAX6 and EGFP double positive neural progenitor/stem cells (NPCs/NSCs) after neural induction. Those PAX6 WT/EGFP NPCs could be purified, expanded and specified to post-mitotic neurons in vitro efficiently. With this reporter cell line, we also screened out 1 NPC-specific microRNA, hsa-miR-99a-5p, and 3 ESCs-enriched miRNAs, hsa-miR-302c-5p, hsa-miR-512-3p and hsa-miR-518 b. In conclusion, the TALEN-based neural stem cell screening system is safe and efficient and could help researcher to acquire adequate and pure neural progenitor cells for further application. Copyright © 2018 Elsevier Inc. All rights reserved.
Efficient implementation of neural network deinterlacing

NASA Astrophysics Data System (ADS)

Seo, Guiwon; Choi, Hyunsoo; Lee, Chulhee

2009-02-01

Interlaced scanning has been widely used in most broadcasting systems. However, there are some undesirable artifacts such as jagged patterns, flickering, and line twitters. Moreover, most recent TV monitors utilize flat panel display technologies such as LCD or PDP monitors and these monitors require progressive formats. Consequently, the conversion of interlaced video into progressive video is required in many applications and a number of deinterlacing methods have been proposed. Recently deinterlacing methods based on neural network have been proposed with good results. On the other hand, with high resolution video contents such as HDTV, the amount of video data to be processed is very large. As a result, the processing time and hardware complexity become an important issue. In this paper, we propose an efficient implementation of neural network deinterlacing using polynomial approximation of the sigmoid function. Experimental results show that these approximations provide equivalent performance with a considerable reduction of complexity. This implementation of neural network deinterlacing can be efficiently incorporated in HW implementation.
Naive-like Conversion Overcomes the Limited Differentiation Capacity of Induced Pluripotent Stem Cells*

PubMed Central

Honda, Arata; Hatori, Masanori; Hirose, Michiko; Honda, Chizumi; Izu, Haruna; Inoue, Kimiko; Hirasawa, Ryutaro; Matoba, Shogo; Togayachi, Sumie; Miyoshi, Hiroyuki; Ogura, Atsuo

2013-01-01

Although induced pluripotent stem (iPS) cells are indistinguishable from ES cells in their expression of pluripotent markers, their differentiation into targeted cells is often limited. Here, we examined whether the limited capacity of iPS cells to differentiate into neural lineage cells could be mitigated by improving their base-line level of pluripotency, i.e. by converting them into the so-called “naive” state. In this study, we used rabbit iPS and ES cells because of the easy availability of both cell types and their typical primed state characters. Repeated passages of the iPS cells permitted their differentiation into early neural cell types (neural stem cells, neurons, and glial astrocytes) with efficiencies similar to ES cells. However, unlike ES cells, their ability to differentiate later into neural cells (oligodendrocytes) was severely compromised. In contrast, after these iPS cells had been converted to a naive-like state, they readily differentiated into mature oligodendrocytes developing characteristic ramified branches, which could not be attained even with ES cells. These results suggest that the naive-like conversion of iPS cells might endow them with a higher differentiation capacity. PMID:23880763
A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

PubMed

Naveros, Francisco; Luque, Niceto R; Garrido, Jesús A; Carrillo, Richard R; Anguita, Mancia; Ros, Eduardo

2015-07-01

Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simulation methods in CPUs and time-driven simulation methods in graphic processing units (GPUs) can outperform CPU time-driven methods under certain conditions. With this performance improvement in mind, we have developed an event-and-time-driven spiking neural network simulator suitable for a hybrid CPU-GPU platform. Our neural simulator is able to efficiently simulate bio-inspired spiking neural networks consisting of different neural models, which can be distributed heterogeneously in both small layers and large layers or subsystems. For the sake of efficiency, the low-activity parts of the neural network can be simulated in CPU using event-driven methods while the high-activity subsystems can be simulated in either CPU (a few neurons) or GPU (thousands or millions of neurons) using time-driven methods. In this brief, we have undertaken a comparative study of these different simulation methods. For benchmarking the different simulation methods and platforms, we have used a cerebellar-inspired neural-network model consisting of a very dense granular layer and a Purkinje layer with a smaller number of cells (according to biological ratios). Thus, this cerebellar-like network includes a dense diverging neural layer (increasing the dimensionality of its internal representation and sparse coding) and a converging neural layer (integration) similar to many other biologically inspired and also artificial neural networks.
Materials for Neural Differentiation, Trans-Differentiation, and Modeling of Neurological Disease.

PubMed

Gong, Lulu; Cao, Lining; Shen, Zhenmin; Shao, Li; Gao, Shaorong; Zhang, Chao; Lu, Jianfeng; Li, Weida

2018-04-01

Neuron regeneration from pluripotent stem cells (PSCs) differentiation or somatic cells trans-differentiation is a promising approach for cell replacement in neurodegenerative diseases and provides a powerful tool for investigating neural development, modeling neurological diseases, and uncovering the mechanisms that underlie diseases. Advancing the materials that are applied in neural differentiation and trans-differentiation promotes the safety, efficiency, and efficacy of neuron regeneration. In the neural differentiation process, matrix materials, either natural or synthetic, not only provide a structural and biochemical support for the monolayer or three-dimensional (3D) cultured cells but also assist in cell adhesion and cell-to-cell communication. They play important roles in directing the differentiation of PSCs into neural cells and modeling neurological diseases. For the trans-differentiation of neural cells, several materials have been used to make the conversion feasible for future therapy. Here, the most current applications of materials for neural differentiation for PSCs, neuronal trans-differentiation, and neurological disease modeling is summarized and discussed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Generation of diverse neural cell types through direct conversion

PubMed Central

Petersen, Gayle F; Strappe, Padraig M

2016-01-01

A characteristic of neurological disorders is the loss of critical populations of cells that the body is unable to replace, thus there has been much interest in identifying methods of generating clinically relevant numbers of cells to replace those that have been damaged or lost. The process of neural direct conversion, in which cells of one lineage are converted into cells of a neural lineage without first inducing pluripotency, shows great potential, with evidence of the generation of a range of functional neural cell types both in vitro and in vivo, through viral and non-viral delivery of exogenous factors, as well as chemical induction methods. Induced neural cells have been proposed as an attractive alternative to neural cells derived from embryonic or induced pluripotent stem cells, with prospective roles in the investigation of neurological disorders, including neurodegenerative disease modelling, drug screening, and cellular replacement for regenerative medicine applications, however further investigations into improving the efficacy and safety of these methods need to be performed before neural direct conversion becomes a clinically viable option. In this review, we describe the generation of diverse neural cell types via direct conversion of somatic cells, with comparison against stem cell-based approaches, as well as discussion of their potential research and clinical applications. PMID:26981169
Aberrant transcriptional networks in step-wise neurogenesis of paroxysmal kinesigenic dyskinesia-induced pluripotent stem cells.

PubMed

Li, Chun; Ma, Yu; Zhang, Kunshan; Gu, Junjie; Tang, Fan; Chen, Shengdi; Cao, Li; Li, Siguang; Jin, Ying

2016-08-16

Paroxysmal kinesigenic dyskinesia (PKD) is an episodic movement disorder with autosomal-dominant inheritance and marked variability in clinical manifestations.Proline-rich transmembrane protein 2 (PRRT2) has been identified as a causative gene of PKD, but the molecular mechanism underlying the pathogenesis of PKD still remains a mystery. The phenotypes and transcriptional patterns of the PKD disease need further clarification. Here, we report the generation and neural differentiation of iPSC lines from two familial PKD patients with c.487C>T (p. Gln163X) and c.573dupT (p. Gly192Trpfs*8) PRRT2 mutations, respectively. Notably, an extremely lower efficiency in neural conversion from PKD-iPSCs than control-iPSCs is observed by a step-wise neural differentiation method of dual inhibition of SMAD signaling. Moreover, we show the high expression level of PRRT2 throughout the human brain and the expression pattern of PRRT2 in other human tissues for the first time. To gain molecular insight into the development of the disease, we conduct global gene expression profiling of PKD cells at four different stages of neural induction and identify altered gene expression patterns, which peculiarly reflect dysregulated neural transcriptome signatures and a differentiation tendency to mesodermal development, in comparison to control-iPSCs. Additionally, functional and signaling pathway analyses indicate significantly different cell fate determination between PKD-iPSCs and control-iPSCs. Together, the establishment of PKD-specific in vitro models and the illustration of transcriptome features in PKD cells would certainly help us with better understanding of the defects in neural conversion as well as further investigations in the pathogenesis of the PKD disease.
Neural circuits. Labeling of active neural circuits in vivo with designed calcium integrators.

PubMed

Fosque, Benjamin F; Sun, Yi; Dana, Hod; Yang, Chao-Tsung; Ohyama, Tomoko; Tadross, Michael R; Patel, Ronak; Zlatic, Marta; Kim, Douglas S; Ahrens, Misha B; Jayaraman, Vivek; Looger, Loren L; Schreiter, Eric R

2015-02-13

The identification of active neurons and circuits in vivo is a fundamental challenge in understanding the neural basis of behavior. Genetically encoded calcium (Ca(2+)) indicators (GECIs) enable quantitative monitoring of cellular-resolution activity during behavior. However, such indicators require online monitoring within a limited field of view. Alternatively, post hoc staining of immediate early genes (IEGs) indicates highly active cells within the entire brain, albeit with poor temporal resolution. We designed a fluorescent sensor, CaMPARI, that combines the genetic targetability and quantitative link to neural activity of GECIs with the permanent, large-scale labeling of IEGs, allowing a temporally precise "activity snapshot" of a large tissue volume. CaMPARI undergoes efficient and irreversible green-to-red conversion only when elevated intracellular Ca(2+) and experimenter-controlled illumination coincide. We demonstrate the utility of CaMPARI in freely moving larvae of zebrafish and flies, and in head-fixed mice and adult flies. Copyright © 2015, American Association for the Advancement of Science.
An Efficient Approach for Lipase-Catalyzed Synthesis of Retinyl Laurate Nutraceutical by Combining Ultrasound Assistance and Artificial Neural Network Optimization.

PubMed

Huang, Shang-Ming; Li, Hsin-Ju; Liu, Yung-Chuan; Kuo, Chia-Hung; Shieh, Chwen-Jen

2017-11-15

Although retinol is an important nutrient, retinol is highly sensitive to oxidation. At present, some ester forms of retinol are generally used in nutritional supplements because of its stability and bioavailability. However, such esters are commonly synthesized by chemical procedures which are harmful to the environment. Thus, this study utilized a green method using lipase as a catalyst with sonication assistance to produce a retinol derivative named retinyl laurate. Moreover, the process was optimized by an artificial neural network (ANN). First, a three-level-four-factor central composite design (CCD) was employed to design 27 experiments, which the highest relative conversion was 82.64%. Further, the optimal architecture of the CCD-employing ANN was developed, including the learning Levenberg-Marquardt algorithm, the transfer function (hyperbolic tangent), iterations (10,000), and the nodes of the hidden layer (6). The best performance of the ANN was evaluated by the root mean squared error (RMSE) and the coefficient of determination ( R ²) from predicting and observed data, which displayed a good data-fitting property. Finally, the process performed with optimal parameters actually obtained a relative conversion of 88.31% without long-term reactions, and the lipase showed great reusability for biosynthesis. Thus, this study utilizes green technology to efficiently produce retinyl laurate, and the bioprocess is well established by ANN-mediated modeling and optimization.
Naïve-like conversion enhances the difference in innate in vitro differentiation capacity between rabbit ES cells and iPS cells

PubMed Central

HONSHO, Kimiko; HIROSE, Michiko; HATORI, Masanori; YASMIN, Lubna; IZU, Haruna; MATOBA, Shogo; TOGAYACHI, Sumie; MIYOSHI, Hiroyuki; SANKAI, Tadashi; OGURA, Atsuo; HONDA, Arata

2014-01-01

Quality evaluation of pluripotent stem cells using appropriate animal models needs to be improved for human regenerative medicine. Previously, we demonstrated that although the in vitro neural differentiating capacity of rabbit induced pluripotent stem cells (iPSCs) can be mitigated by improving their baseline level of pluripotency, i.e., by converting them into the so-called “naïve-like” state, the effect after such conversion of rabbit embryonic stem cells (ESCs) remains to be elucidated. Here we found that naïve-like conversion enhanced the differences in innate in vitro differentiation capacity between ESCs and iPSCs. Naïve-like rabbit ESCs exhibited several features indicating pluripotency, including the capacity for teratoma formation. They differentiated into mature oligodendrocytes much more effectively (3.3–7.2 times) than naïve-like iPSCs. This suggests an inherent variation in differentiation potential in vitro among PSC lines. When naïve-like ESCs were injected into preimplantation rabbit embryos, although they contributed efficiently to forming the inner cell mass of blastocysts, no chimeric pups were obtained. Thus, in vitro neural differentiation following naïve-like conversion is a promising option for determining the quality of PSCs without the need to demonstrate chimeric contribution. These results provide an opportunity to evaluate which pluripotent stem cells or treatments are best suited for therapeutic use. PMID:25345855
Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting.

PubMed

Wöllmer, Martin; Marchi, Erik; Squartini, Stefano; Schuller, Björn

2011-09-01

Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today's automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database-a corpus containing emotionally colored conversations with a cognitive system for "Sensitive Artificial Listening".
Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations.

PubMed

Gómez-Villafuertes, Rosa; Paniagua-Herranz, Lucía; Gascon, Sergio; de Agustín-Durán, David; Ferreras, María de la O; Gil-Redondo, Juan Carlos; Queipo, María José; Menendez-Mendez, Aida; Pérez-Sen, Ráquel; Delicado, Esmerilda G; Gualix, Javier; Costa, Marcos R; Schroeder, Timm; Miras-Portugal, María Teresa; Ortega, Felipe

2017-12-16

Understanding the mechanisms that control critical biological events of neural cell populations, such as proliferation, differentiation, or cell fate decisions, will be crucial to design therapeutic strategies for many diseases affecting the nervous system. Current methods to track cell populations rely on their final outcomes in still images and they generally fail to provide sufficient temporal resolution to identify behavioral features in single cells. Moreover, variations in cell death, behavioral heterogeneity within a cell population, dilution, spreading, or the low efficiency of the markers used to analyze cells are all important handicaps that will lead to incomplete or incorrect read-outs of the results. Conversely, performing live imaging and single cell tracking under appropriate conditions represents a powerful tool to monitor each of these events. Here, a time-lapse video-microscopy protocol, followed by post-processing, is described to track neural populations with single cell resolution, employing specific software. The methods described enable researchers to address essential questions regarding the cell biology and lineage progression of distinct neural populations.
BMP-induced reprogramming of the neural retina into retinal pigment epithelium requires Wnt signalling

PubMed Central

Steinfeld, Jörg; Steinfeld, Ichie; Bausch, Alexander; Coronato, Nicola; Hampel, Meggi-Lee; Depner, Heike; Layer, Paul G.

2017-01-01

ABSTRACT In vertebrates, the retinal pigment epithelium (RPE) and photoreceptors of the neural retina (NR) comprise a functional unit required for vision. During vertebrate eye development, a conversion of the RPE into NR can be induced by growth factors in vivo at optic cup stages, but the reverse process, the conversion of NR tissue into RPE, has not been reported. Here, we show that bone morphogenetic protein (BMP) signalling can reprogram the NR into RPE at optic cup stages in chick. Shortly after BMP application, expression of Microphthalmia-associated transcription factor (Mitf) is induced in the NR and selective cell death on the basal side of the NR induces an RPE-like morphology. The newly induced RPE differentiates and expresses Melanosomalmatrix protein 115 (Mmp115) and RPE65. BMP-induced Wnt2b expression is observed in regions of the NR that become pigmented. Loss of function studies show that conversion of the NR into RPE requires both BMP and Wnt signalling. Simultaneous to the appearance of ectopic RPE tissue, BMP application reprogrammed the proximal RPE into multi-layered retinal tissue. The newly induced NR expresses visual segment homeobox-containing gene (Vsx2), and the ganglion and photoreceptor cell markers Brn3α and Visinin are detected. Our results show that high BMP concentrations are required to induce the conversion of NR into RPE, while low BMP concentrations can still induce transdifferentiation of the RPE into NR. This knowledge may contribute to the development of efficient standardized protocols for RPE and NR generation for cell replacement therapies. PMID:28546339
Consequences of converting graded to action potentials upon neural information coding and energy efficiency.

PubMed

Sengupta, Biswa; Laughlin, Simon Barry; Niven, Jeremy Edward

2014-01-01

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na(+) and K(+) channels, with generator potential and graded potential models lacking voltage-gated Na(+) channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na(+) channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a 'footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.
Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

PubMed Central

Sengupta, Biswa; Laughlin, Simon Barry; Niven, Jeremy Edward

2014-01-01

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation. PMID:24465197
A New Module in Neural Differentiation Control: Two MicroRNAs Upregulated by Retinoic Acid, miR-9 and -103, Target the Differentiation Inhibitor ID2

PubMed Central

Savino, Mauro; Laneve, Pietro; Caffarelli, Elisa; Nasi, Sergio

2012-01-01

The transcription factor ID2 is an important repressor of neural differentiation strongly implicated in nervous system cancers. MicroRNAs (miRNAs) are increasingly involved in differentiation control and cancer development. Here we show that two miRNAs upregulated on differentiation of neuroblastoma cells – miR-9 and miR-103 – restrain ID2 expression by directly targeting the coding sequence and 3′ untranslated region of the ID2 encoding messenger RNA, respectively. Notably, the two miRNAs show an inverse correlation with ID2 during neuroblastoma cell differentiation induced by retinoic acid. Overexpression of miR-9 and miR-103 in neuroblastoma cells reduces proliferation and promotes differentiation, as it was shown to occur upon ID2 inhibition. Conversely, an ID2 mutant that cannot be targeted by either miRNA prevents retinoic acid-induced differentiation more efficient than wild-type ID2. These findings reveal a new regulatory module involving two microRNAs upregulated during neural differentiation that directly target expression of the key differentiation inhibitor ID2, suggesting that its alteration may be involved in neural cancer development. PMID:22848373
A new module in neural differentiation control: two microRNAs upregulated by retinoic acid, miR-9 and -103, target the differentiation inhibitor ID2.

PubMed

Annibali, Daniela; Gioia, Ubaldo; Savino, Mauro; Laneve, Pietro; Caffarelli, Elisa; Nasi, Sergio

2012-01-01

The transcription factor ID2 is an important repressor of neural differentiation strongly implicated in nervous system cancers. MicroRNAs (miRNAs) are increasingly involved in differentiation control and cancer development. Here we show that two miRNAs upregulated on differentiation of neuroblastoma cells--miR-9 and miR-103--restrain ID2 expression by directly targeting the coding sequence and 3' untranslated region of the ID2 encoding messenger RNA, respectively. Notably, the two miRNAs show an inverse correlation with ID2 during neuroblastoma cell differentiation induced by retinoic acid. Overexpression of miR-9 and miR-103 in neuroblastoma cells reduces proliferation and promotes differentiation, as it was shown to occur upon ID2 inhibition. Conversely, an ID2 mutant that cannot be targeted by either miRNA prevents retinoic acid-induced differentiation more efficient than wild-type ID2. These findings reveal a new regulatory module involving two microRNAs upregulated during neural differentiation that directly target expression of the key differentiation inhibitor ID2, suggesting that its alteration may be involved in neural cancer development.

Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG.

PubMed

Duru, Adil Deniz; Assem, Moataz

2018-02-01

Neural efficiency is proposed as one of the neural mechanisms underlying elite athletic performances. Previous sports studies examined neural efficiency using tasks that involve motor functions. In this study we investigate the extent of neural efficiency beyond motor tasks by using a mental subtraction task. A group of elite karate athletes are compared to a matched group of non-athletes. Electroencephalogram is used to measure cognitive dynamics during resting and increased mental workload periods. Mainly posterior alpha band power of the karate players was found to be higher than control subjects under both tasks. Moreover, event related synchronization/desynchronization has been computed to investigate the neural efficiency hypothesis among subjects. Finally, this study is the first study to examine neural efficiency related to a cognitive task, not a motor task, in elite karate players using ERD/ERS analysis. The results suggest that the effect of neural efficiency in the brain is global rather than local and thus might be contributing to the elite athletic performances. Also the results are in line with the neural efficiency hypothesis tested for motor performance studies.
Neural Correlates of Single- and Dual-Task Walking in the Real World

PubMed Central

Pizzamiglio, Sara; Naeem, Usman; Abdalla, Hassan; Turner, Duncan L.

2017-01-01

Recent developments in mobile brain-body imaging (MoBI) technologies have enabled studies of human locomotion where subjects are able to move freely in more ecologically valid scenarios. In this study, MoBI was employed to describe the behavioral and neurophysiological aspects of three different commonly occurring walking conditions in healthy adults. The experimental conditions were self-paced walking, walking while conversing with a friend and lastly walking while texting with a smartphone. We hypothesized that gait performance would decrease with increased cognitive demands and that condition-specific neural activation would involve condition-specific brain areas. Gait kinematics and high density electroencephalography (EEG) were recorded whilst walking around a university campus. Conditions with dual tasks were accompanied by decreased gait performance. Walking while conversing was associated with an increase of theta (θ) and beta (β) neural power in electrodes located over left-frontal and right parietal regions, whereas walking while texting was associated with a decrease of β neural power in a cluster of electrodes over the frontal-premotor and sensorimotor cortices when compared to walking whilst conversing. In conclusion, the behavioral “signatures” of common real-life activities performed outside the laboratory environment were accompanied by differing frequency-specific neural “biomarkers”. The current findings encourage the study of the neural biomarkers of disrupted gait control in neurologically impaired patients. PMID:28959199
Rapid Optimization of External Quantum Efficiency of Thin Film Solar Cells Using Surrogate Modeling of Absorptivity.

PubMed

Kaya, Mine; Hajimirza, Shima

2018-05-25

This paper uses surrogate modeling for very fast design of thin film solar cells with improved solar-to-electricity conversion efficiency. We demonstrate that the wavelength-specific optical absorptivity of a thin film multi-layered amorphous-silicon-based solar cell can be modeled accurately with Neural Networks and can be efficiently approximated as a function of cell geometry and wavelength. Consequently, the external quantum efficiency can be computed by averaging surrogate absorption and carrier recombination contributions over the entire irradiance spectrum in an efficient way. Using this framework, we optimize a multi-layer structure consisting of ITO front coating, metallic back-reflector and oxide layers for achieving maximum efficiency. Our required computation time for an entire model fitting and optimization is 5 to 20 times less than the best previous optimization results based on direct Finite Difference Time Domain (FDTD) simulations, therefore proving the value of surrogate modeling. The resulting optimization solution suggests at least 50% improvement in the external quantum efficiency compared to bare silicon, and 25% improvement compared to a random design.
NEURAL NETWORK MODELLING OF CARDIAC DOSE CONVERSION COEFFICIENT FOR ARBITRARY X-RAY SPECTRA.

PubMed

Kadri, O; Manai, K

2016-12-01

In this article, an approach to compute the dose conversion coefficients (DCCs) is described for the computational voxel phantom 'High-Definition Reference Korean-Man' (HDRK-Man) using artificial neural networks (ANN). For this purpose, the voxel phantom was implemented into the Monte Carlo (MC) transport toolkit GEANT4, and the DCCs for more than 30 tissues and organs, due to a broad parallel beam of monoenergetic photons with energy ranging from 15 to 150 keV by a step of 5 keV, were calculated. To study the influence of patient size on DCC values, DCC calculation was performed, for a representative body size population, using five different sizes covering the range of 80-120 % magnification of the original HDRK-Man. The focus of the present study was on the computation of DCC for the human heart. ANN calculation and MC simulation results were compared, and good agreement was observed showing that ANNs can be used as an efficient tool for modelling DCCs for the computational voxel phantom. ANN approach appears to be a significant advance over the time-consuming MC methods for DCC calculation. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
SMAD7 directly converts human embryonic stem cells to telencephalic fate by a default mechanism

PubMed Central

Ozair, Mohammad Zeeshan; Noggle, Scott; Warmflash, Aryeh; Krzyspiak, Joanna Ela; Brivanlou, Ali H.

2013-01-01

Human embryonic stem cells (hESCs) provide a valuable window into the dissection of the molecular circuitry underlying the early formation of the human forebrain. However, dissection of signaling events in forebrain development using current protocols is complicated by non-neural contamination and fluctuation of extrinsic influences. Here we show that SMAD7, a cell-intrinsic inhibitor of TGFβ signaling, is sufficient to directly convert pluripotent hESCs to an anterior neural fate. Time-course gene expression revealed down-regulation of MAPK components, and combining MEK1/2 inhibition with SMAD7-mediated TGFβ inhibition promoted telencephalic conversion. FGF-MEK and TGFβ-SMAD signaling maintain hESCs by promoting pluripotency genes and repressing neural genes. Our findings suggest that in the absence of these cues, pluripotent cells simply revert to a program of neural conversion. Hence the “primed” state of hESCs requires inhibition of the “default” state of neural fate acquisition. This has parallels in amphibians, suggesting an evolutionarily conserved mechanism. PMID:23034881
Social Context-Dependent Activity in Marmoset Frontal Cortex Populations during Natural Conversations

PubMed Central

de la Mothe, Lisa; Miller, Cory T.

2017-01-01

Communication is an inherently interactive process that weaves together the fabric of both human and nonhuman primate societies. To investigate the properties of the primate brain during active social signaling, we recorded the responses of frontal cortex neurons as freely moving marmosets engaged in conversational exchanges with a visually occluded virtual marmoset. We found that small changes in firing rate (∼1 Hz) occurred across a broadly distributed population of frontal cortex neurons when marmosets heard a conspecific vocalization, and that these changes corresponded to subjects' likelihood of producing or withholding a vocal reply. Although the contributions of individual neurons were relatively small, large populations of neurons were able to clearly distinguish between these social contexts. Most significantly, this social context-dependent change in firing rate was evident even before subjects heard the vocalization, indicating that the probability of a conversational exchange was determined by the state of the frontal cortex at the time a vocalization was heard, and not by a decision driven by acoustic characteristics of the vocalization. We found that changes in neural activity scaled with the length of the conversation, with greater changes in firing rate evident for longer conversations. These data reveal specific and important facets of this neural activity that constrain its possible roles in active social signaling, and we hypothesize that the close coupling between frontal cortex activity and this natural, active primate social-signaling behavior facilitates social-monitoring mechanisms critical to conversational exchanges. SIGNIFICANCE STATEMENT We provide evidence for a novel pattern of neural activity in the frontal cortex of freely moving, naturally behaving, marmoset monkeys that may facilitate natural primate conversations. We discovered small (∼1 Hz), but reliable, changes in neural activity that occurred before marmosets even heard a conspecific vocalization that, as a population, almost perfectly predicted whether subjects would produce a vocalization in response. The change in the state of the frontal cortex persisted throughout the conversation and its magnitude scaled linearly with the length of the interaction. We hypothesize that this social context-dependent change in frontal cortex activity is supported by several mechanisms, such as social arousal and attention, and facilitates social monitoring critical for vocal coordination characteristic of human and nonhuman primate conversations. PMID:28630255
Training Deep Spiking Neural Networks Using Backpropagation.

PubMed

Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.
Neural computing for numeric-to-symbolic conversion in control systems

NASA Technical Reports Server (NTRS)

Passino, Kevin M.; Sartori, Michael A.; Antsaklis, Panos J.

1989-01-01

A type of neural network, the multilayer perceptron, is used to classify numeric data and assign appropriate symbols to various classes. This numeric-to-symbolic conversion results in a type of information extraction, which is similar to what is called data reduction in pattern recognition. The use of the neural network as a numeric-to-symbolic converter is introduced, its application in autonomous control is discussed, and several applications are studied. The perceptron is used as a numeric-to-symbolic converter for a discrete-event system controller supervising a continuous variable dynamic system. It is also shown how the perceptron can implement fault trees, which provide useful information (alarms) in a biological system and information for failure diagnosis and control purposes in an aircraft example.
Chromatin remodeling and histone modification in the conversion of oligodendrocyte precursors to neural stem cells

PubMed Central

Kondo, Toru; Raff, Martin

2004-01-01

We showed previously that purified rat oligodendrocyte precursor cells (OPCs) can be induced by extracellular signals to convert to multipotent neural stem-like cells (NSLCs), which can then generate both neurons and glial cells. Because the conversion of precursor cells to stem-like cells is of both intellectual and practical interest, it is important to understand its molecular basis. We show here that the conversion of OPCs to NSLCs depends on the reactivation of the sox2 gene, which in turn depends on the recruitment of the tumor suppressor protein Brca1 and the chromatin-remodeling protein Brahma (Brm) to an enhancer in the sox2 promoter. Moreover, we show that the conversion is associated with the modification of Lys 4 and Lys 9 of histone H3 at the same enhancer. Our findings suggest that the conversion of OPCs to NSLCs depends on progressive chromatin remodeling, mediated in part by Brca1 and Brm. PMID:15574597
Supervised artificial neural network-based method for conversion of solar radiation data (case study: Algeria)

NASA Astrophysics Data System (ADS)

Laidi, Maamar; Hanini, Salah; Rezrazi, Ahmed; Yaiche, Mohamed Redha; El Hadj, Abdallah Abdallah; Chellali, Farouk

2017-04-01

In this study, a backpropagation artificial neural network (BP-ANN) model is used as an alternative approach to predict solar radiation on tilted surfaces (SRT) using a number of variables involved in physical process. These variables are namely the latitude of the site, mean temperature and relative humidity, Linke turbidity factor and Angstrom coefficient, extraterrestrial solar radiation, solar radiation data measured on horizontal surfaces (SRH), and solar zenith angle. Experimental solar radiation data from 13 stations spread all over Algeria around the year (2004) were used for training/validation and testing the artificial neural networks (ANNs), and one station was used to make the interpolation of the designed ANN. The ANN model was trained, validated, and tested using 60, 20, and 20 % of all data, respectively. The configuration 8-35-1 (8 inputs, 35 hidden, and 1 output neurons) presented an excellent agreement between the prediction and the experimental data during the test stage with determination coefficient of 0.99 and root meat squared error of 5.75 Wh/m2, considering a three-layer feedforward backpropagation neural network with Levenberg-Marquardt training algorithm, a hyperbolic tangent sigmoid and linear transfer function at the hidden and the output layer, respectively. This novel model could be used by researchers or scientists to design high-efficiency solar devices that are usually tilted at an optimum angle to increase the solar incident on the surface.
Increasing conversion efficiency of two-step photon up-conversion solar cell with a voltage booster hetero-interface.

PubMed

Asahi, Shigeo; Kusaki, Kazuki; Harada, Yukihiro; Kita, Takashi

2018-01-17

Development of high-efficiency solar cells is one of the attractive challenges in renewable energy technologies. Photon up-conversion can reduce the transmission loss and is one of the promising concepts which improve conversion efficiency. Here we present an analysis of the conversion efficiency, which can be increased by up-conversion in a single-junction solar cell with a hetero-interface that boosts the output voltage. We confirm that an increase in the quasi-Fermi gap and substantial photocurrent generation result in a high conversion efficiency.
Induced neural stem cells as a means of treatment in Huntington's disease.

PubMed

Choi, Kyung-Ah; Hong, Sunghoi

2017-11-01

Huntington's disease (HD) is an inherited neurodegenerative disease characterized by chorea, dementia, and depression caused by progressive nerve cell degeneration, which is triggered by expanded CAG repeats in the huntingtin (Htt) gene. Currently, there is no cure for this disease, nor is there an effective medicine available to delay or improve the physical, mental, and behavioral severities caused by it. Areas covered: In this review, the authors describe the use of induced neural stem cells (iNSCs) by direct conversion technology, which offers great advantages as a therapeutic cell type to treat HD. Expert opinion: Cell conversion of somatic cells into a desired stem cell type is one of the most promising treatments for HD because it could be facilitated for the generation of patient-specific neural stem cells. The induced pluripotent stem cells (iPSCs) have a powerful potential for differentiation into neurons, but they may cause teratoma formation due to an undifferentiated pluripotent stem cell after transplantation Therefore, direct conversion of somatic cells into iNSCs is a promising alternative technology in regenerative medicine and the iNSCs may be provided as a therapeutic cell source for Huntington's disease.
Ecological conversion efficiency and its influencers in twelve species of fish in the Yellow Sea Ecosystem

NASA Astrophysics Data System (ADS)

Tang, Qisheng; Guo, Xuewu; Sun, Yao; Zhang, Bo

2007-09-01

The ecological conversion efficiencies in twelve species of fish in the Yellow Sea Ecosystem, i.e., anchovy ( Engraulis japonicus), rednose anchovy ( Thrissa kammalensis), chub mackerel ( Scomber japonicus), halfbeak ( Hyporhamphus sajori), gizzard shad ( Konosirus punctatus), sand lance ( Ammodytes personatus), red seabream ( Pagrus major), black porgy ( Acanthopagrus schlegeli), black rockfish ( Sebastes schlegeli), finespot goby ( Chaeturichthys stigmatias), tiger puffer ( Takifugu rubripes), and fat greenling ( Hexagrammos otakii), were estimated through experiments conducted either in situ or in a laboratory. The ecological conversion efficiencies were significantly different among these species. As indicated, the food conversion efficiencies and the energy conversion efficiencies varied from 12.9% to 42.1% and from 12.7% to 43.0%, respectively. Water temperature and ration level are the main factors influencing the ecological conversion efficiencies of marine fish. The higher conversion efficiency of a given species in a natural ecosystem is acquired only under the moderate environment conditions. A negative relationship between ecological conversion efficiency and trophic level among ten species was observed. Such a relationship indicates that the ecological efficiency in the upper trophic levels would increase after fishing down marine food web in the Yellow Sea ecosystem.
Histone modifications controlling native and induced neural stem cell identity.

PubMed

Broccoli, Vania; Colasante, Gaia; Sessa, Alessandro; Rubio, Alicia

2015-10-01

During development, neural progenitor cells (NPCs) that are capable of self-renewing maintain a proliferative cellular pool while generating all differentiated neural cell components. Although the genetic network of transcription factors (TFs) required for neural specification has been well characterized, the unique set of histone modifications that accompanies this process has only recently started to be investigated. In vitro neural differentiation of pluripotent stem cells is emerging as a powerful system to examine epigenetic programs. Deciphering the histone code and how it shapes the chromatin environment will reveal the intimate link between epigenetic changes and mechanisms for neural fate determination in the developing nervous system. Furthermore, it will offer a molecular framework for a stringent comparison between native and induced neural stem cells (iNSCs) generated by direct neural cell conversion. Copyright © 2015 Elsevier Ltd. All rights reserved.
Modulating inhibitory control with direct current stimulation of the superior medial frontal cortex.

PubMed

Hsu, Tzu-Yu; Tseng, Lin-Yuan; Yu, Jia-Xin; Kuo, Wen-Jui; Hung, Daisy L; Tzeng, Ovid J L; Walsh, Vincent; Muggleton, Neil G; Juan, Chi-Hung

2011-06-15

The executive control of voluntary action involves not only choosing from a range of possible actions but also the inhibition of responses as circumstances demand. Recent studies have demonstrated that many clinical populations, such as people with attention-deficit hyperactivity disorder, exhibit difficulties in inhibitory control. One prefrontal area that has been particularly associated with inhibitory control is the pre-supplementary motor area (Pre-SMA). Here we applied non-invasive transcranial direct current stimulation (tDCS) over Pre-SMA to test its role in this behavior. tDCS allows for current to be applied in two directions to selectively excite or suppress the neural activity of Pre-SMA. Our results showed that anodal tDCS improved efficiency of inhibitory control. Conversely, cathodal tDCS showed a tendency towards impaired inhibitory control. To our knowledge, this is the first demonstration of non-invasive intervention tDCS altering subjects' inhibitory control. These results further our understanding of the neural bases of inhibitory control and suggest a possible therapeutic intervention method for clinical populations. Copyright © 2011 Elsevier Inc. All rights reserved.
A Programmable High-Voltage Compliance Neural Stimulator for Deep Brain Stimulation in Vivo

PubMed Central

Gong, Cihun-Siyong Alex; Lai, Hsin-Yi; Huang, Sy-Han; Lo, Yu-Chun; Lee, Nicole; Chen, Pin-Yuan; Tu, Po-Hsun; Yang, Chia-Yen; Lin, James Chang-Chieh; Chen, You-Yin

2015-01-01

Deep brain stimulation (DBS) is one of the most effective therapies for movement and other disorders. The DBS neurosurgical procedure involves the implantation of a DBS device and a battery-operated neurotransmitter, which delivers electrical impulses to treatment targets through implanted electrodes. The DBS modulates the neuronal activities in the brain nucleus for improving physiological responses as long as an electric discharge above the stimulation threshold can be achieved. In an effort to improve the performance of an implanted DBS device, the device size, implementation cost, and power efficiency are among the most important DBS device design aspects. This study aims to present preliminary research results of an efficient stimulator, with emphasis on conversion efficiency. The prototype stimulator features high-voltage compliance, implemented with only a standard semiconductor process, without the use of extra masks in the foundry through our proposed circuit structure. The results of animal experiments, including evaluation of evoked responses induced by thalamic electrical stimuli with our fabricated chip, were shown to demonstrate the proof of concept of our design. PMID:26029954
This Neural Implant is designed to be implanted in the Human Central and Nervous System

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

A new class of neural implants being developed at the Livermore Lab are the first clinical quality devices capable of two-way conversations with the human nervous systems. Unlike existing interfaces that only sense or only stimulate, these devices are capable of stimulating and sensing using both electric and chemical signals.
Temporal Context in Speech Processing and Attentional Stream Selection: A Behavioral and Neural Perspective

ERIC Educational Resources Information Center

Golumbic, Elana M. Zion; Poeppel, David; Schroeder, Charles E.

2012-01-01

The human capacity for processing speech is remarkable, especially given that information in speech unfolds over multiple time scales concurrently. Similarly notable is our ability to filter out of extraneous sounds and focus our attention on one conversation, epitomized by the "Cocktail Party" effect. Yet, the neural mechanisms underlying on-line…
This Neural Implant is designed to be implanted in the Human Central and Nervous System

ScienceCinema

None

2018-06-12

A new class of neural implants being developed at the Livermore Lab are the first clinical quality devices capable of two-way conversations with the human nervous systems. Unlike existing interfaces that only sense or only stimulate, these devices are capable of stimulating and sensing using both electric and chemical signals.
Nicotinamide alone accelerates the conversion of mouse embryonic stem cells into mature neuronal populations

PubMed Central

Griffin, Síle M.; Pickard, Mark R.; Orme, Rowan P.; Hawkins, Clive P.; Williams, Adrian C.

2017-01-01

Introduction Vitamin B3 has been shown to play an important role during embryogenesis. Specifically, there is growing evidence that nicotinamide, the biologically active form of vitamin B3, plays a critical role as a morphogen in the differentiation of stem cells to mature cell phenotypes, including those of the central nervous system (CNS). Detailed knowledge of the action of small molecules during neuronal differentiation is not only critical for uncovering mechanisms underlying lineage-specification, but also to establish more effective differentiation protocols to obtain clinically relevant cells for regenerative therapies for neurodegenerative conditions such as Huntington’s disease (HD). Thus, this study aimed to investigate the potential of nicotinamide to promote the conversion of stem cells to mature CNS neurons. Methods Nicotinamide was applied to differentiating mouse embryonic stem cells (mESC; Sox1GFP knock-in 46C cell line) during their conversion towards a neural fate. Cells were assessed for changes in their proliferation, differentiation and maturation; using immunocytochemistry and morphometric analysis methods. Results Results presented indicate that 10 mM nicotinamide, when added at the initial stages of differentiation, promoted accelerated progression of ESCs to a neural lineage in adherent monolayer cultures. By 14 days in vitro (DIV), early exposure to nicotinamide was shown to increase the numbers of differentiated βIII-tubulin-positive neurons. Nicotinamide decreased the proportion of pluripotent stem cells, concomitantly increasing numbers of neural progenitors at 4 DIV. These progenitors then underwent rapid conversion to neurons, observed by a reduction in Sox 1 expression and decreased numbers of neural progenitors in the cultures at 14 DIV. Furthermore, GABAergic neurons generated in the presence of nicotinamide showed increased maturity and complexity of neurites at 14 DIV. Therefore, addition of nicotinamide alone caused an accelerated passage of pluripotent cells through lineage specification and further to non-dividing mature neurons. Conclusions Our results show that, within an optimal dose range, nicotinamide is able to singly and selectively direct the conversion of embryonic stem cells to mature neurons, and therefore may be a critical factor for normal brain development, thus supporting previous evidence of the fundamental role of vitamins and their metabolites during early CNS development. In addition, nicotinamide may offer a simple effective supplement to enhance the conversion of stem cells to clinically relevant neurons. PMID:28817722

Conversion Disorder- Mind versus Body: A Review.

PubMed

Ali, Shahid; Jabeen, Shagufta; Pate, Rebecca J; Shahid, Marwah; Chinala, Sandhya; Nathani, Milankumar; Shah, Rida

2015-01-01

In this article, the authors accentuate the signs and symptoms of conversion disorder and the significance of clinical judgment and expertise in order to reach the right diagnosis. The authors review the literature and provide information on the etiology, prevalence, diagnostic criteria, and the treatment methods currently employed in the management of conversion disorder. Of note, the advancements of neuropsychology and brain imaging have led to emergence of a relatively sophisticated picture of the neuroscientific psychopathology of complex mental illnesses, including conversion disorder. The available evidence suggests new methods with which to test hypotheses about the neural circuits underlying conversion symptoms. In context of this, the authors also explore the neurobiological understanding of conversion disorder.
Conversion Disorder— Mind versus Body: A Review

PubMed Central

Jabeen, Shagufta; Pate, Rebecca J.; Shahid, Marwah; Chinala, Sandhya; Nathani, Milankumar; Shah, Rida

2015-01-01

In this article, the authors accentuate the signs and symptoms of conversion disorder and the significance of clinical judgment and expertise in order to reach the right diagnosis. The authors review the literature and provide information on the etiology, prevalence, diagnostic criteria, and the treatment methods currently employed in the management of conversion disorder. Of note, the advancements of neuropsychology and brain imaging have led to emergence of a relatively sophisticated picture of the neuroscientific psychopathology of complex mental illnesses, including conversion disorder. The available evidence suggests new methods with which to test hypotheses about the neural circuits underlying conversion symptoms. In context of this, the authors also explore the neurobiological understanding of conversion disorder. PMID:26155375
Optimization of Neutral Atom Imagers

NASA Technical Reports Server (NTRS)

Shappirio, M.; Coplan, M.; Balsamo, E.; Chornay, D.; Collier, M.; Hughes, P.; Keller, J.; Ogilvie, K.; Williams, E.

2008-01-01

The interactions between plasma structures and neutral atom populations in interplanetary space can be effectively studied with energetic neutral atom imagers. For neutral atoms with energies less than 1 keV, the most efficient detection method that preserves direction and energy information is conversion to negative ions on surfaces. We have examined a variety of surface materials and conversion geometries in order to identify the factors that determine conversion efficiency. For chemically and physically stable surfaces smoothness is of primary importance while properties such as work function have no obvious correlation to conversion efficiency. For the noble metals, tungsten, silicon, and graphite with comparable smoothness, conversion efficiency varies by a factor of two to three. We have also examined the way in which surface conversion efficiency varies with the angle of incidence of the neutral atom and have found that the highest efficiencies are obtained at angles of incidence greater then 80deg. The conversion efficiency of silicon, tungsten and graphite were examined most closely and the energy dependent variation of conversion efficiency measured over a range of incident angles. We have also developed methods for micromachining silicon in order to reduce the volume to surface area over that of a single flat surface and have been able to reduce volume to surface area ratios by up to a factor of 60. With smooth micro-machined surfaces of the optimum geometry, conversion efficiencies can be increased by an order of magnitude over instruments like LENA on the IMAGE spacecraft without increase the instruments mass or volume.
Electroviscous effect and electrokinetic energy conversion in time periodic pressure-driven flow through a parallel-plate nanochannel with surface charge-dependent slip

NASA Astrophysics Data System (ADS)

Buren, Mandula; Jian, Yongjun; Zhao, Yingchun; Chang, Long

2018-05-01

In this paper we analytically investigate the electroviscous effect and electrokinetic energy conversion in the time periodic pressure-driven flow of an incompressible viscous Newtonian liquid through a parallel-plate nanochannel with surface charge-dependent slip. Analytical and semi-analytical solutions for electric potential, velocity and streaming electric field are obtained and are utilized to compute electrokinetic energy conversion efficiency. The results show that velocity amplitude and energy conversion efficiency are reduced when the effect of surface charge on slip length is considered. The surface charge effect increases with zeta potential and ionic concentration. In addition, the energy conversion efficiency is large when the ratio of channel half-height to the electric double layer thickness is small. The boundary slip results in a large increase in energy conversion. Higher values of the frequency of pressure pulsation lead to higher values of the energy conversion efficiency. We also obtain the energy conversion efficiency in constant pressure-driven flow and find that the energy conversion efficiency in periodical pressure-driven flow becomes larger than that in constant pressure-driven flow when the frequency is large enough.
Method to monitor HC-SCR catalyst NOx reduction performance for lean exhaust applications

DOEpatents

Viola, Michael B [Macomb Township, MI; Schmieg, Steven J [Troy, MI; Sloane, Thompson M [Oxford, MI; Hilden, David L [Shelby Township, MI; Mulawa, Patricia A [Clinton Township, MI; Lee, Jong H [Rochester Hills, MI; Cheng, Shi-Wai S [Troy, MI

2012-05-29

A method for initiating a regeneration mode in selective catalytic reduction device utilizing hydrocarbons as a reductant includes monitoring a temperature within the aftertreatment system, monitoring a fuel dosing rate to the selective catalytic reduction device, monitoring an initial conversion efficiency, selecting a determined equation to estimate changes in a conversion efficiency of the selective catalytic reduction device based upon the monitored temperature and the monitored fuel dosing rate, estimating changes in the conversion efficiency based upon the determined equation and the initial conversion efficiency, and initiating a regeneration mode for the selective catalytic reduction device based upon the estimated changes in conversion efficiency.
Robust fault detection of wind energy conversion systems based on dynamic neural networks.

PubMed

Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad

2014-01-01

Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate.
Robust Fault Detection of Wind Energy Conversion Systems Based on Dynamic Neural Networks

PubMed Central

Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad

2014-01-01

Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate. PMID:24744774
Sex differences in neural efficiency: Are they due to the stereotype threat effect?☆

PubMed Central

Dunst, Beate; Benedek, Mathias; Bergner, Sabine; Athenstaedt, Ursula; Neubauer, Aljoscha C.

2013-01-01

The neural efficiency hypothesis postulates a more efficient use of brain resources in more intelligent people as compared to less intelligent ones. However, this relationship was found to be moderated by sex and task content. While the phenomenon of neural efficiency was previously supported for men when performing visuo-spatial tasks it occurred for women only when performing verbal tasks. One possible explanation for this finding could be provided by the well-studied phenomenon called stereotype threat. Stereotype threat arises when a negative stereotype of one’s own group is made salient and can result in behavior that confirms the stereotype. Overall, 32 boys and 31 girls of varying intellectual ability were tested with a mental rotation task, either under a stereotype exposure or a no-stereotype exposure condition while measuring their EEG. The behavioral results show that an activated negative stereotype not necessarily hampers the performance of girls. Physiologically, a confirmation of the neural efficiency phenomenon was only obtained for boys working under a no-stereotype exposure condition. This result pattern replicates previous findings without threat and thus suggests that sex differences in neural efficiency during visuo-spatial tasks may not be due to the stereotype threat effect. PMID:24092950
Efficiency turns the table on neural encoding, decoding and noise.

PubMed

Deneve, Sophie; Chalk, Matthew

2016-04-01

Sensory neurons are usually described with an encoding model, for example, a function that predicts their response from the sensory stimulus using a receptive field (RF) or a tuning curve. However, central to theories of sensory processing is the notion of 'efficient coding'. We argue here that efficient coding implies a completely different neural coding strategy. Instead of a fixed encoding model, neural populations would be described by a fixed decoding model (i.e. a model reconstructing the stimulus from the neural responses). Because the population solves a global optimization problem, individual neurons are variable, but not noisy, and have no truly invariant tuning curve or receptive field. We review recent experimental evidence and implications for neural noise correlations, robustness and adaptation. Copyright © 2016. Published by Elsevier Ltd.
Egg production forecasting: Determining efficient modeling approaches.

PubMed

Ahmad, H A

2011-12-01

Several mathematical or statistical and artificial intelligence models were developed to compare egg production forecasts in commercial layers. Initial data for these models were collected from a comparative layer trial on commercial strains conducted at the Poultry Research Farms, Auburn University. Simulated data were produced to represent new scenarios by using means and SD of egg production of the 22 commercial strains. From the simulated data, random examples were generated for neural network training and testing for the weekly egg production prediction from wk 22 to 36. Three neural network architectures-back-propagation-3, Ward-5, and the general regression neural network-were compared for their efficiency to forecast egg production, along with other traditional models. The general regression neural network gave the best-fitting line, which almost overlapped with the commercial egg production data, with an R(2) of 0.71. The general regression neural network-predicted curve was compared with original egg production data, the average curves of white-shelled and brown-shelled strains, linear regression predictions, and the Gompertz nonlinear model. The general regression neural network was superior in all these comparisons and may be the model of choice if the initial overprediction is managed efficiently. In general, neural network models are efficient, are easy to use, require fewer data, and are practical under farm management conditions to forecast egg production.
Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.

PubMed

Tabaton, Massimo; Odetti, Patrizio; Cammarata, Sergio; Borghi, Roberta; Monacelli, Fiammetta; Caltagirone, Carlo; Bossù, Paola; Buscema, Massimo; Grossi, Enzo

2010-01-01

The search for markers that are able to predict the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is crucial for early mechanistic therapies. Using artificial neural networks (ANNs), 22 variables that are known risk factors of AD were analyzed in 80 patients with aMCI, for a period spanning at least 2 years. The cases were chosen from 195 aMCI subjects recruited by four Italian Alzheimer's disease units. The parameters of glucose metabolism disorder, female gender, and apolipoprotein E epsilon3/epsilon4 genotype were found to be the biological variables with high relevance for predicting the conversion of aMCI. The scores of attention and short term memory tests also were predictors. Surprisingly, the plasma concentration of amyloid-beta (42) had a low predictive value. The results support the utility of ANN analysis as a new tool in the interpretation of data from heterogeneous and distinct sources.
Analyses of conversion efficiency in high-speed clock recovery based on Mach-Zehnder modulator

NASA Astrophysics Data System (ADS)

Dong, H.; Sun, H.; Zhu, G.; Dutta, N. K.

2006-09-01

In this paper, detailed analyses of the conversion efficiency in high-speed clock recovery based on Mach-Zehnder (MZ) modulator has been carried out. The theoretical results show the conversion efficiency changes with RF driving power and the mixing order. For high order clock recovery, the cascaded MZ modulator provides higher conversion efficiency. A study of clock recovery at 160 Gb/s using the cascaded MZ modulator has been carried out. The experimental results agree with the results of the analysis.
Energy-efficient neural information processing in individual neurons and neuronal networks.

PubMed

Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Using Neural Net Technology To Enhance the Efficiency of a Computer Adaptive Testing Application.

ERIC Educational Resources Information Center

Van Nelson, C.; Henriksen, Larry W.

The potential for computer adaptive testing (CAT) has been well documented. In order to improve the efficiency of this process, it may be possible to utilize a neural network, or more specifically, a back propagation neural network. The paper asserts that in order to accomplish this end, it must be shown that grouping examinees by ability as…
Single-hidden-layer feed-forward quantum neural network based on Grover learning.

PubMed

Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

2013-09-01

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.
Ag Nanoparticle-Functionalized Open-Ended Freestanding TiO₂ Nanotube Arrays with a Scattering Layer for Improved Energy Conversion Efficiency in Dye-Sensitized Solar Cells.

PubMed

Rho, Won-Yeop; Chun, Myeung-Hwan; Kim, Ho-Sub; Kim, Hyung-Mo; Suh, Jung Sang; Jun, Bong-Hyun

2016-06-15

Dye-sensitized solar cells (DSSCs) were fabricated using open-ended freestanding TiO₂ nanotube arrays functionalized with Ag nanoparticles (NPs) in the channel to create a plasmonic effect, and then coated with large TiO₂ NPs to create a scattering effect in order to improve energy conversion efficiency. Compared to closed-ended freestanding TiO₂ nanotube array-based DSSCs without Ag or large TiO₂ NPs, the energy conversion efficiency of closed-ended DSSCs improved by 9.21% (actual efficiency, from 5.86% to 6.40%) with Ag NPs, 6.48% (actual efficiency, from 5.86% to 6.24%) with TiO₂ NPs, and 14.50% (actual efficiency, from 5.86% to 6.71%) with both Ag NPs and TiO₂ NPs. By introducing Ag NPs and/or large TiO₂ NPs to open-ended freestanding TiO₂ nanotube array-based DSSCs, the energy conversion efficiency was improved by 9.15% (actual efficiency, from 6.12% to 6.68%) with Ag NPs and 8.17% (actual efficiency, from 6.12% to 6.62%) with TiO₂ NPs, and by 15.20% (actual efficiency, from 6.12% to 7.05%) with both Ag NPs and TiO₂ NPs. Moreover, compared to closed-ended freestanding TiO₂ nanotube arrays, the energy conversion efficiency of open-ended freestanding TiO₂ nanotube arrays increased from 6.71% to 7.05%. We demonstrate that each component-Ag NPs, TiO₂ NPs, and open-ended freestanding TiO₂ nanotube arrays-enhanced the energy conversion efficiency, and the use of a combination of all components in DSSCs resulted in the highest energy conversion efficiency.
Limits to solar power conversion efficiency with applications to quantum and thermal systems

NASA Technical Reports Server (NTRS)

Byvik, C. E.; Buoncristiani, A. M.; Smith, B. T.

1983-01-01

An analytical framework is presented that permits examination of the limit to the efficiency of various solar power conversion devices. Thermodynamic limits to solar power efficiency are determined for both quantum and thermal systems, and the results are applied to a variety of devices currently considered for use in space systems. The power conversion efficiency for single-threshold energy quantum systems receiving unconcentrated air mass zero solar radiation is limited to 31 percent. This limit applies to photovoltaic cells directly converting solar radiation, or indirectly, as in the case of a thermophotovoltaic system. Photoelectrochemical cells rely on an additional chemical reaction at the semiconductor-electrolyte interface, which introduces additional second-law demands and a reduction of the solar conversion efficiency. Photochemical systems exhibit even lower possible efficiencies because of their relatively narrow absorption bands. Solar-powered thermal engines in contact with an ambient reservoir at 300 K and operating at maximum power have a peak conversion efficiency of 64 percent, and this occurs for a thermal reservoir at a temperature of 2900 K. The power conversion efficiency of a solar-powered liquid metal magnetohydrodydnamic generator, a solar-powered steam turbine electric generator, and an alkali metal thermoelectric converter is discussed.
Modelling and optimization of Mn/activate carbon nanocatalysts for NO reduction: comparison of RSM and ANN techniques.

PubMed

Mousavi, Seyed Mahdi; Niaei, Aligholi; Salari, Dariush; Panahi, Parvaneh Nakhostin; Samandari, Masoud

2013-01-01

A response surface methodology (RSM) involving a central composite design was applied to the modelling and optimization of a preparation of Mn/active carbon nanocatalysts in NH3-SCR of NO at 250 degrees C and the results were compared with the artificial neural network (ANN) predicted values. The catalyst preparation parameters, including metal loading (wt%), calcination temperature and pre-oxidization degree (v/v% HNO3) were selected as influence factors on catalyst efficiency. In the RSM model, the predicted values of NO conversion were found to be in good agreement with the experimental values. Pareto graphic analysis showed that all the chosen parameters and some of the interactions were effective on response. The optimization results showed that maximum NO conversion was achieved at the optimum conditions: 10.2 v/v% HNO3, 6.1 wt% Mn loading and calcination at 480 degrees C. The ANN model was developed by a feed-forward back propagation network with the topology 3, 8 and 1 and a Levenberg-Marquardt training algorithm. The mean square error for the ANN and RSM models were 0.339 and 1.176, respectively, and the R2 values were 0.991 and 0.972, respectively, indicating the superiority of ANN in capturing the nonlinear behaviour of the system and being accurate in estimating the values of the NO conversion.
Morphological and genetical changes of endothelial progenitor cells after in-vitro conversion into photoreceptors.

PubMed

Qiang, Shi; Alsaeedi, Hiba Amer; Yuhong, Cheng; Yang, Hao; Tong, Li; Kumar, Suresh; Higuchi, Akon; Alarfaj, Abdullah A; Munisvaradass, Rusheni; Ling, Mok Pooi; Cheng, Pei

2018-06-01

Retinal degeneration is a condition ensued by various ocular disorders such as artery occlusion, diabetic retinopathy, retrolental fibroplasia and retinitis pigmentosa which cause abnormal loss of photoreceptor cells and lead to eventual vision impairment. No efficient treatment has yet been found, however, the use of stem cell therapy such as bone marrow and embryonic stem cells has opened a new treatment modality for retinal degenerative diseases. The major goal of this study is to analyze the potential of endothelial progenitor cells derived from bone marrow to differentiate into retinal neural cells for regenerative medicine purposes. In this study, endothelial progenitor cells were induced in-vitro with photoreceptor growth factor (taurine) for 21 days. Subsequently, the morphology and gene expression of CRX and RHO of the photoreceptors-induced EPCs were examined through immunostaining assay. The results indicated that the induced endothelial progenitor cells demonstrated positive gene expression of CRX and RHO. Our findings suggested that EPC cells may have a high advantage in cell replacement therapy for treating eye disease, in addition to other neural diseases, and may be a suitable cell source in regenerative medicine for eye disorders. Copyright © 2018 Elsevier B.V. All rights reserved.
Investigation for all polarization conversions of the guided-modes in a bending waveguide

NASA Astrophysics Data System (ADS)

Shi, Yunjie; Shang, Hongpeng; Sun, DeGui

2018-03-01

In this work, a new solution to the partial differential Maxwell equations is first derived to investigate all polarization conversions of the transverse and the longitudinal components of guided-modes in a bending waveguide. Then, for the silica-waveguides, the polarization conversion efficiencies are numerical calculated and a significant finding is that the transverse-longitudinal polarization conversion efficiency is much higher than that of transverse-transverse polarization conversion. Furthermore, the dependences of all the conversion efficiencies on waveguide parameters are found. The agreeable results between the numerical calculation and the finite difference time-domain (FDTD) simulation show that for two 100 μm long bending waveguides of 0.75 and 1.50% index contrasts, the amplitude conversion efficiencies from ∼10-3 to ∼10-2 can be realized for the transverse-transverse polarization components and that of ∼10-1 can be realized for the transverse-longitudinal polarization components.

Stretching morphogenesis of the roof plate and formation of the central canal.

PubMed

Kondrychyn, Igor; Teh, Cathleen; Sin, Melvin; Korzh, Vladimir

2013-01-01

Neurulation is driven by apical constriction of actomyosin cytoskeleton resulting in conversion of the primitive lumen into the central canal in a mechanism driven by F-actin constriction, cell overcrowding and buildup of axonal tracts. The roof plate of the neural tube acts as the dorsal morphogenetic center and boundary preventing midline crossing by neural cells and axons. The roof plate zebrafish transgenics expressing cytosolic GFP were used to study and describe development of this structure in vivo for a first time ever. The conversion of the primitive lumen into the central canal causes significant morphogenetic changes of neuroepithelial cells in the dorsal neural tube. We demonstrated that the roof plate cells stretch along the D-V axis in parallel with conversion of the primitive lumen into central canal and its ventral displacement. Importantly, the stretching of the roof plate is well-coordinated along the whole spinal cord and the roof plate cells extend 3× in length to cover 2/3 of the neural tube diameter. This process involves the visco-elastic extension of the roof place cytoskeleton and depends on activity of Zic6 and the Rho-associated kinase (Rock). In contrast, stretching of the floor plate is much less extensive. The extension of the roof plate requires its attachment to the apical complex of proteins at the surface of the central canal, which depends on activity of Zic6 and Rock. The D-V extension of the roof plate may change a range and distribution of morphogens it produces. The resistance of the roof plate cytoskeleton attenuates ventral displacement of the central canal in illustration of the novel mechanical role of the roof plate during development of the body axis.
Stretching Morphogenesis of the Roof Plate and Formation of the Central Canal

PubMed Central

Kondrychyn, Igor; Teh, Cathleen; Sin, Melvin; Korzh, Vladimir

2013-01-01

Background Neurulation is driven by apical constriction of actomyosin cytoskeleton resulting in conversion of the primitive lumen into the central canal in a mechanism driven by F-actin constriction, cell overcrowding and buildup of axonal tracts. The roof plate of the neural tube acts as the dorsal morphogenetic center and boundary preventing midline crossing by neural cells and axons. Methodology/Principal Findings The roof plate zebrafish transgenics expressing cytosolic GFP were used to study and describe development of this structure in vivo for a first time ever. The conversion of the primitive lumen into the central canal causes significant morphogenetic changes of neuroepithelial cells in the dorsal neural tube. We demonstrated that the roof plate cells stretch along the D–V axis in parallel with conversion of the primitive lumen into central canal and its ventral displacement. Importantly, the stretching of the roof plate is well-coordinated along the whole spinal cord and the roof plate cells extend 3× in length to cover 2/3 of the neural tube diameter. This process involves the visco-elastic extension of the roof place cytoskeleton and depends on activity of Zic6 and the Rho-associated kinase (Rock). In contrast, stretching of the floor plate is much less extensive. Conclusions/Significance The extension of the roof plate requires its attachment to the apical complex of proteins at the surface of the central canal, which depends on activity of Zic6 and Rock. The D–V extension of the roof plate may change a range and distribution of morphogens it produces. The resistance of the roof plate cytoskeleton attenuates ventral displacement of the central canal in illustration of the novel mechanical role of the roof plate during development of the body axis. PMID:23409159
Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.

2018-05-01

Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.
Vectorized algorithms for spiking neural network simulation.

PubMed

Brette, Romain; Goodman, Dan F M

2011-06-01

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.
Synaptic E-I Balance Underlies Efficient Neural Coding.

PubMed

Zhou, Shanglin; Yu, Yuguo

2018-01-01

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.
Synaptic E-I Balance Underlies Efficient Neural Coding

PubMed Central

Zhou, Shanglin; Yu, Yuguo

2018-01-01

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding. PMID:29456491
Direct adaptive control of wind energy conversion systems using Gaussian networks.

PubMed

Mayosky, M A; Cancelo, I E

1999-01-01

Grid connected wind energy conversion systems (WECS) present interesting control demands, due to the intrinsic nonlinear characteristics of windmills and electric generators. In this paper a direct adaptive control strategy for WECS control is proposed. It is based on the combination of two control actions: a radial basis zfunction network-based adaptive controller, which drives the tracking error to zero with user specified dynamics, and a supervisory controller, based on crude bounds of the system's nonlinearities. The supervisory controller fires when the finite neural-network approximation properties cannot be guaranteed. The form of the supervisor control and the adaptation law for the neural controller are derived from a Lyapunov analysis of stability. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution.
A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

PubMed

Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

2009-01-01

For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.
Changes in brain activity following intensive voice treatment in children with cerebral palsy.

PubMed

Bakhtiari, Reyhaneh; Cummine, Jacqueline; Reed, Alesha; Fox, Cynthia M; Chouinard, Brea; Cribben, Ivor; Boliek, Carol A

2017-09-01

Eight children (3 females; 8-16 years) with motor speech disorders secondary to cerebral palsy underwent 4 weeks of an intensive neuroplasticity-principled voice treatment protocol, LSVT LOUD ® , followed by a structured 12-week maintenance program. Children were asked to overtly produce phonation (ah) at conversational loudness, cued-phonation at perceived twice-conversational loudness, a series of single words, and a prosodic imitation task while being scanned using fMRI, immediately pre- and post-treatment and 12 weeks following a maintenance program. Eight age- and sex-matched controls were scanned at each of the same three time points. Based on the speech and language literature, 16 bilateral regions of interest were selected a priori to detect potential neural changes following treatment. Reduced neural activity in the motor areas (decreased motor system effort) before and immediately after treatment, and increased activity in the anterior cingulate gyrus after treatment (increased contribution of decision making processes) were observed in the group with cerebral palsy compared to the control group. Using graphical models, post-treatment changes in connectivity were observed between the left supramarginal gyrus and the right supramarginal gyrus and the left precentral gyrus for the children with cerebral palsy, suggesting LSVT LOUD enhanced contributions of the feedback system in the speech production network instead of high reliance on feedforward control system and the somatosensory target map for regulating vocal effort. Network pruning indicates greater processing efficiency and the recruitment of the auditory and somatosensory feedback control systems following intensive treatment. Hum Brain Mapp 38:4413-4429, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Silicon trench photodiodes on a wafer for efficient X-ray-to-current signal conversion using side-X-ray-irradiation mode

NASA Astrophysics Data System (ADS)

Ariyoshi, Tetsuya; Takane, Yuta; Iwasa, Jumpei; Sakamoto, Kenji; Baba, Akiyoshi; Arima, Yutaka

2018-04-01

In this paper, we report a direct-conversion-type X-ray sensor composed of trench-structured silicon photodiodes, which achieves a high X-ray-to-current conversion efficiency under side X-ray irradiation. The silicon X-ray sensor with a length of 22.6 mm and a trench depth of 300 µm was fabricated using a single-poly single-metal 0.35 µm process. X-rays with a tube voltage of 80 kV were irradiated along the trench photodiode from the side of the test chip. The theoretical limit of X-ray-to-current conversion efficiency of 83.8% was achieved at a low reverse bias voltage of 25 V. The X-ray-to-electrical signal conversion efficiency of conventional indirect-conversion-type X-ray sensors is about 10%. Therefore, the developed sensor has a conversion efficiency that is about eight times higher than that of conventional sensors. It is expected that the developed X-ray sensor will be able to markedly lower the radiation dose required for X-ray diagnoses.
[Case report: electroconvulsive therapy in a 33-year-old man with hysterical quadriplegia].

PubMed

Gaillard, A; Gaillard, R; Mouaffak, F; Radtchenko, A; Lôo, H

2012-02-01

Conversion disorder refers to the occurrence of neurological-like symptoms or deficits that are neither intentionally produced nor simulated. While it cannot be explained by an organic disease, it is often related to psychological events. We report the case of a 33-year-old patient with a fluctuating hysterical tetraplegia, which had started three years earlier. After the failure or the exhaustion of several biological (psychotropic medication, transcranial magnetic stimulation) and psychotherapeutic strategies, treatment with electroconvulsive therapy (ECT) was conducted. A total of thirty-five ECT sessions were performed. Whereas the patient's clinical state was initially characterized by a complete quadriplegia and an uncontrollable muscular hypertonia, we noted that the ECT sessions were associated with a slow, though remarkable, progress. At first, the sessions were followed by moments of altered consciousness during which the patient would be relaxed and could make simple movements. Secondarily, not only was our patient able to consciously move his four limbs, but he was also able to walk. However, those improvements remained partial and fluctuating, sometimes allowing the symptom to return temporarily secondary to frustrations or annoyances. Finally, our patient relapsed. Nevertheless, his clinical state presently remains better than that in which we first knew him. The treatment of conversion disorders has been the subject of few studies and predominantly remains symptomatic. Its main goals are: to lessen secondary gains impact by adopting a neutral behaviour towards the symptom and by encouraging physical rehabilitation; to lower the symptom by allowing the patient to understand the normal functioning of the diseased organ, and; to help the patient to deal with stressful situations. There is no evidence that hypnosis is superior to medical and other psychotherapeutic approaches. Pharmacological treatments may be helpful in the case of anxiety, impulsivity or depression, albeit delivered with caution. According to some case reports, transcranial magnetic stimulation has also been associated with clinical remission. Although the use of ECT in motor conversion disorders constitutes an uncommon procedure, and even if no clinical trial has evaluated its impact on such a pathological condition, several case reports suggest that electroconvulsive therapy can be efficient in the treatment of motor conversion disorders. This efficacy may rely on several hypotheses. ECT could induce neural modifications, and participate in the suppression of an active inhibition, which is responsible for hysterical symptoms. Indeed, conversion cerebral disorder correlates can be explored with the help of functional neuro-imaging techniques, which could therefore also identify ECT neural effects. ECT adverse effects on memory could lead to a new relationship with the symptom, and modulate the psychological conflict which has participated in its emergence. Narcoanalysis, ECT sessions could have an impact on consciousness by means of some dissolution and reorganization phenomenon. It could therefore participate in the ending of an emotional block, the psychic integration of traumatic events and the recovery of a voluntary motor control. Finally, ECT could be efficient thanks to its antidepressant properties, especially its ability to stimulate triaminergic, and particularly dopaminergic transmission. This case report reminds us how difficult it can be to deal with severe conversion disorders, and to navigate between two reefs, which are abstention, and therapeutic escalation. Copyright Â© 2011 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.
Estimating Hardwood Sawmill Conversion Efficiency Based on Sawing Machine and Log.

Treesearch

Michael W. Wade; Steven H. Bullard; Philip H. Steele; Philip A. Araman

1992-01-01

Increased problems of hardwood timber availability have caused many sawmillers, industry analysts, and planners to recognize the importance of sawmill conversion efficiency. Conversion efficiency not only affects sawmill profits, but is also important on a much broader level. Timber supply issues have caused resource planners and policy makers to consider the effects...
An Inductively-Powered Wireless Neural Recording System with a Charge Sampling Analog Front-End

PubMed Central

Lee, Seung Bae; Lee, Byunghun; Kiani, Mehdi; Mahmoudi, Babak; Gross, Robert; Ghovanloo, Maysam

2015-01-01

An inductively-powered wireless integrated neural recording system (WINeR-7) is presented for wireless and battery less neural recording from freely-behaving animal subjects inside a wirelessly-powered standard homecage. The WINeR-7 system employs a novel wide-swing dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which performs amplification, filtering, sampling, and analog-to-time conversion (ATC) with minimal interference and small amount of power. The output of the DSCS-AFE produces a pseudo-digital pulse width modulated (PWM) signal. A circular shift register (CSR) time division multiplexes (TDM) the PWM pulses to create a TDM-PWM signal, which is fed into an on-chip 915 MHz transmitter (Tx). The AFE and Tx are supplied at 1.8 V and 4.2 V, respectively, by a power management block, which includes a high efficiency active rectifier and automatic resonance tuning (ART), operating at 13.56 MHz. The 8-ch system-on-a-chip (SoC) was fabricated in a 0.35-μm CMOS process, occupying 5.0 × 2.5 mm2 and consumed 51.4 mW. For each channel, the sampling rate is 21.48 kHz and the power consumption is 19.3 μW. In vivo experiments were conducted on freely behaving rats in an energized homecage by continuously delivering 51.4 mW to the WINeR-7 system in a closed-loop fashion and recording local field potentials (LFP). PMID:27069422
An Inductively-Powered Wireless Neural Recording System with a Charge Sampling Analog Front-End.

PubMed

Lee, Seung Bae; Lee, Byunghun; Kiani, Mehdi; Mahmoudi, Babak; Gross, Robert; Ghovanloo, Maysam

2016-01-15

An inductively-powered wireless integrated neural recording system (WINeR-7) is presented for wireless and battery less neural recording from freely-behaving animal subjects inside a wirelessly-powered standard homecage. The WINeR-7 system employs a novel wide-swing dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which performs amplification, filtering, sampling, and analog-to-time conversion (ATC) with minimal interference and small amount of power. The output of the DSCS-AFE produces a pseudo-digital pulse width modulated (PWM) signal. A circular shift register (CSR) time division multiplexes (TDM) the PWM pulses to create a TDM-PWM signal, which is fed into an on-chip 915 MHz transmitter (Tx). The AFE and Tx are supplied at 1.8 V and 4.2 V, respectively, by a power management block, which includes a high efficiency active rectifier and automatic resonance tuning (ART), operating at 13.56 MHz. The 8-ch system-on-a-chip (SoC) was fabricated in a 0.35-μm CMOS process, occupying 5.0 × 2.5 mm 2 and consumed 51.4 mW. For each channel, the sampling rate is 21.48 kHz and the power consumption is 19.3 μW. In vivo experiments were conducted on freely behaving rats in an energized homecage by continuously delivering 51.4 mW to the WINeR-7 system in a closed-loop fashion and recording local field potentials (LFP).
Current matching using CdSe quantum dots to enhance the power conversion efficiency of InGaP/GaAs/Ge tandem solar cells.

PubMed

Lee, Ya-Ju; Yao, Yung-Chi; Tsai, Meng-Tsan; Liu, An-Fan; Yang, Min-De; Lai, Jiun-Tsuen

2013-11-04

A III-V multi-junction tandem solar cell is the most efficient photovoltaic structure that offers an extremely high power conversion efficiency. Current mismatching between each subcell of the device, however, is a significant challenge that causes the experimental value of the power conversion efficiency to deviate from the theoretical value. In this work, we explore a promising strategy using CdSe quantum dots (QDs) to enhance the photocurrent of the limited subcell to match with those of the other subcells and to enhance the power conversion efficiency of InGaP/GaAs/Ge tandem solar cells. The underlying mechanism of the enhancement can be attributed to the QD's unique capacity for photon conversion that tailors the incident spectrum of solar light; the enhanced efficiency of the device is therefore strongly dependent on the QD's dimensions. As a result, by appropriately selecting and spreading 7 mg/mL of CdSe QDs with diameters of 4.2 nm upon the InGaP/GaAs/Ge solar cell, the power conversion efficiency shows an enhancement of 10.39% compared to the cell's counterpart without integrating CdSe QDs.
Polarity-specific high-level information propagation in neural networks.

PubMed

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.
Polarity-specific high-level information propagation in neural networks

PubMed Central

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals. PMID:24672472
Conversation Effects on Neural Mechanisms Underlying Reaction Time to Visual Events while Viewing a Driving Scene using MEG

PubMed Central

Bowyer, Susan M.; Hsieh, Li; Moran, John E.; Young, Richard A.; Manoharan, Arun; Liao, Chia-cheng Jason; Malladi, Kiran; Yu, Ya-Ju; Chiang, Yow-Ren; Tepley, Norman

2009-01-01

Magnetoencephalography (MEG) imaging examined the neural mechanisms that modulate reaction times to visual events while viewing a driving video, with and without a conversation. Twenty-four subjects ages 18–65 were monitored by whole-head MEG. The primary tasks were to monitor a driving video and to depress a foot pedal in response to a small red light presented to the left or below the driving scene at unpredictable times. The behavioral reaction time (RT) to the lights was recorded. The secondary task was a hands-free conversation. The subject pressed a button to answer a ring tone, and then covertly answered pre-recorded non-emotional questions such as “What is your birth date?” RTs for the conversation task (1043ms, SE=65ms) were slightly longer than for the primary task (baseline no conversation (944ms, SE=48ms). During the primary task RTs were inversely related to the amount of brain activity detected by MEG in the right superior parietal lobe (Brodmann’s Area 7). Brain activity was seen in the 200 to 300 ms range after the onset of the red light and in the visual cortex (BA 19) about 85 ms after the red light. Conversation reduced the strengths of these regression relationships and increased mean RT. Conversation may contribute to increased reaction times by (1) damping brain activation in specific regions during specific time windows, or (2) reducing facilitation from attention inputs into those areas. These laboratory findings should not be interpreted as indicative of real-world driving, without on-road validation, and comparison to other in-vehicle tasks. PMID:18992728
Effect of the shell material and confinement type on the conversion efficiency of core/shell quantum dot nanocrystal solar cells

NASA Astrophysics Data System (ADS)

Sahin, Mehmet

2018-05-01

In this study, the effects of the shell material and confinement type on the conversion efficiency of core/shell quantum dot nanocrystal (QDNC) solar cells have been investigated in detail. For this purpose, the conventional, i.e. original, detailed balance model, developed by Shockley and Queisser to calculate an upper limit for the conversion efficiency of silicon p–n junction solar cells, is modified in a simple and effective way to calculate the conversion efficiency of core/shell QDNC solar cells. Since the existing model relies on the gap energy () of the solar cell, it does not make an estimation about the effect of QDNC materials on the efficiency of the solar cells, and gives the same efficiency values for several QDNC solar cells with the same . The proposed modification, however, estimates a conversion efficiency in relation to the material properties and also the confinement type of the QDNCs. The results of the modified model show that, in contrast to the original one, the conversion efficiencies of different QDNC solar cells, even if they have the same , become different depending upon the confinement type and shell material of the core/shell QDNCs, and this is crucial in the design and fabrication of the new generation solar cells to predict the confinement type and also appropriate QDNC materials for better efficiency.
SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2017-01-01

Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches. PMID:28771497

The Brain as a Distributed Intelligent Processing System: An EEG Study

PubMed Central

da Rocha, Armando Freitas; Rocha, Fábio Theoto; Massad, Eduardo

2011-01-01

Background Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion The present results support these claims and the neural efficiency hypothesis. PMID:21423657
Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe -decay searches

NASA Astrophysics Data System (ADS)

Caldwell, A.; Cossavella, F.; Majorovits, B.; Palioselitis, D.; Volynets, O.

2015-07-01

A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate variations of efficiencies as a function of used training set. It is verified that neural networks are well-suited to identify background pulses in true-coaxial high-purity germanium detectors. The systematic uncertainty on the signal recognition efficiency derived using signal-like evaluation samples from calibration measurements is estimated to be 5 %. This uncertainty is due to differences between signal and calibration samples.
Biphasic influence of Miz1 on neural crest development by regulating cell survival and apical adhesion complex formation in the developing neural tube

PubMed Central

Kerosuo, Laura; Bronner, Marianne E.

2014-01-01

Myc interacting zinc finger protein-1 (Miz1) is a transcription factor known to regulate cell cycle– and cell adhesion–related genes in cancer. Here we show that Miz1 also plays a critical role in neural crest development. In the chick, Miz1 is expressed throughout the neural plate and closing neural tube. Its morpholino-mediated knockdown affects neural crest precursor survival, leading to reduction of neural plate border and neural crest specifier genes Msx-1, Pax7, FoxD3, and Sox10. Of interest, Miz1 loss also causes marked reduction of adhesion molecules (N-cadherin, cadherin6B, and α1-catenin) with a concomitant increase of E-cadherin in the neural folds, likely leading to delayed and decreased neural crest emigration. Conversely, Miz1 overexpression results in up-regulation of cadherin6B and FoxD3 expression in the neural folds/neural tube, leading to premature neural crest emigration and increased number of migratory crest cells. Although Miz1 loss effects cell survival and proliferation throughout the neural plate, the neural progenitor marker Sox2 was unaffected, suggesting a neural crest–selective effect. The results suggest that Miz1 is important not only for survival of neural crest precursors, but also for maintenance of integrity of the neural folds and tube, via correct formation of the apical adhesion complex therein. PMID:24307680
Near-IR, blue, and UV generation by frequency conversion of a Tm:YAP laser

NASA Astrophysics Data System (ADS)

Cole, Brian; Goldberg, Lew; Chinn, Steve

2018-02-01

We describe generation of near-infrared (944nm, 970nm), blue (472nm, 485nm), and UV (236 nm) light by frequency up-conversion of 2 μm output of a compact and efficient passively Q-switched Tm:YAP laser. The Tm:YAP laser source was near diffraction limited with maximum Q-switched pulse peak power of 190 kW. For second harmonic generation (SHG) of NIR, both periodically poled lithium niobate (PPLN) and lithium tri-borate (LBO) were evaluated, with 58% conversion efficiency and 3.1 W of 970 nm power achieved with PPLN. The PPLN 970nm emission was frequency doubled in 20mm long type I LBO, generating 1.1 W at 485nm with a conversion efficiency of 34%. With LBO used for frequency doubling of 2.3 W of 1888 nm Tm:YAP output to 944nm, 860mW was generated, with 37% conversion efficiency. Using a second LBO crystal to generate the 4th harmonic, 545mW of 472nm power was generated, corresponding to 64% conversion efficiency. To generate the 8th harmonic of Tm:YAP laser emission, the 472nm output of the second LBO was frequency doubled in a 7mm long BBO crystal, generating 110 mW at 236nm, corresponding to 21% conversion efficiency.
Status of photoelectrochemical production of hydrogen and electrical energy

NASA Technical Reports Server (NTRS)

Byvik, C. E.; Walker, G. H.

1976-01-01

The efficiency for conversion of electromagnetic energy to chemical and electrical energy utilizing semiconductor single crystals as photoanodes in electrochemical cells was investigated. Efficiencies as high as 20 percent were achieved for the conversion of 330 nm radiation to chemical energy in the form of hydrogen by the photoelectrolysis of water in a SrTiO3 based cell. The SrTiO3 photoanodes were shown to be stable in 9.5 M NaOH solutions for periods up to 48 hours. Efficiencies of 9 percent were measured for the conversion of broadband visible radiation to hydrogen using n-type GaAs crystals as photoanodes. Crystals of GaAs coated with 500 nm of gold, silver, or tin for surface passivation show no significant change in efficiency. By suppressing the production of hydrogen in a CdSe-based photogalvanic cell, an efficiency of 9 percent was obtained in conversion of 633 nm light to electrical energy. A CdS-based photogalvanic cell produced a conversion efficiency of 5 percent for 500 nm radiation.
Hierarchical Graphene Foam for Efficient Omnidirectional Solar-Thermal Energy Conversion.

PubMed

Ren, Huaying; Tang, Miao; Guan, Baolu; Wang, Kexin; Yang, Jiawei; Wang, Feifan; Wang, Mingzhan; Shan, Jingyuan; Chen, Zhaolong; Wei, Di; Peng, Hailin; Liu, Zhongfan

2017-10-01

Efficient solar-thermal energy conversion is essential for the harvesting and transformation of abundant solar energy, leading to the exploration and design of efficient solar-thermal materials. Carbon-based materials, especially graphene, have the advantages of broadband absorption and excellent photothermal properties, and hold promise for solar-thermal energy conversion. However, to date, graphene-based solar-thermal materials with superior omnidirectional light harvesting performances remain elusive. Herein, hierarchical graphene foam (h-G foam) with continuous porosity grown via plasma-enhanced chemical vapor deposition is reported, showing dramatic enhancement of broadband and omnidirectional absorption of sunlight, which thereby can enable a considerable elevation of temperature. Used as a heating material, the external solar-thermal energy conversion efficiency of the h-G foam impressively reaches up to ≈93.4%, and the solar-vapor conversion efficiency exceeds 90% for seawater desalination with high endurance. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Efficiently modeling neural networks on massively parallel computers

NASA Technical Reports Server (NTRS)

Farber, Robert M.

1993-01-01

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.
Motor and somatosensory conversion disorder: a functional unawareness syndrome?

PubMed

Perez, David L; Barsky, Arthur J; Daffner, Kirk; Silbersweig, David A

2012-01-01

Although conversion disorder is closely connected to the origins of neurology and psychiatry, it remains poorly understood. In this article, the authors discuss neural and clinical parallels between lesional unawareness disorders and unilateral motor and somatosensory conversion disorder, emphasizing functional neuroimaging/disease correlates. Authors suggest that a functional-unawareness neurobiological framework, mediated by right hemisphere-lateralized, large-scale brain network dysfunction, may play a significant role in the neurobiology of conversion disorder. The perigenual anterior cingulate and the posterior parietal cortices are detailed as important in disease pathophysiology. Further investigations will refine the functional-unawareness concept, clarify the role of affective circuits, and delineate the process through which functional neurologic symptoms emerge.
The role of fluid intelligence and learning in analogical reasoning: How to become neurally efficient?

PubMed

Dix, Annika; Wartenburger, Isabell; van der Meer, Elke

2016-10-01

This study on analogical reasoning evaluates the impact of fluid intelligence on adaptive changes in neural efficiency over the course of an experiment and specifies the underlying cognitive processes. Grade 10 students (N=80) solved unfamiliar geometric analogy tasks of varying difficulty. Neural efficiency was measured by the event-related desynchronization (ERD) in the alpha band, an indicator of cortical activity. Neural efficiency was defined as a low amount of cortical activity accompanying high performance during problem-solving. Students solved the tasks faster and more accurately the higher their FI was. Moreover, while high FI led to greater cortical activity in the first half of the experiment, high FI was associated with a neurally more efficient processing (i.e., better performance but same amount of cortical activity) in the second half of the experiment. Performance in difficult tasks improved over the course of the experiment for all students while neural efficiency increased for students with higher but decreased for students with lower fluid intelligence. Based on analyses of the alpha sub-bands, we argue that high fluid intelligence was associated with a stronger investment of attentional resource in the integration of information and the encoding of relations in this unfamiliar task in the first half of the experiment (lower-2 alpha band). Students with lower fluid intelligence seem to adapt their applied strategies over the course of the experiment (i.e., focusing on task-relevant information; lower-1 alpha band). Thus, the initially lower cortical activity and its increase in students with lower fluid intelligence might reflect the overcoming of mental overload that was present in the first half of the experiment. Copyright © 2016 Elsevier Inc. All rights reserved.
Effect of the Molecular Nature of Mutation on the Efficiency of Intrachromosomal Gene Conversion in Mouse Cells

PubMed Central

Letsou, Anthea; Liskay, R. Michael

1987-01-01

With the intent of further exploring the nature of gene conversion in mammalian cells, we systematically addressed the effects of the molecular nature of mutation on the efficiency of intrachromosomal gene conversion in cultured mouse cells. Comparison of conversion rates revealed that all mutations studied were suitable substrates for gene conversion; however, we observed that the rates at which different mutations converted to wild-type could differ by two orders of magnitude. Differences in conversion rates were correlated with the molecular nature of the mutations. In general, rates of conversion decreased with increasing size of the molecular lesions. In comparisons of conversion rates for single base pair insertions and deletions we detected a genotype-directed path for conversion, by which an insertion was converted to wild-type three to four times more efficiently than was a deletion which maps to the same site. The data are discussed in relation to current theories of gene conversion, and are consistent with the idea that gene conversion in mammalian cells can result from repair of heteroduplex DNA (hDNA) intermediates. PMID:2828159
Estimating Seebeck Coefficient of a p-Type High Temperature Thermoelectric Material Using Bee Algorithm Multi-layer Perception

NASA Astrophysics Data System (ADS)

Uysal, Fatih; Kilinc, Enes; Kurt, Huseyin; Celik, Erdal; Dugenci, Muharrem; Sagiroglu, Selami

2017-08-01

Thermoelectric generators (TEGs) convert heat into electrical energy. These energy-conversion systems do not involve any moving parts and are made of thermoelectric (TE) elements connected electrically in a series and thermally in parallel; however, they are currently not suitable for use in regular operations due to their low efficiency levels. In order to produce high-efficiency TEGs, there is a need for highly heat-resistant thermoelectric materials (TEMs) with an improved figure of merit ( ZT). Production and test methods used for TEMs today are highly expensive. This study attempts to estimate the Seebeck coefficient of TEMs by using the values of existing materials in the literature. The estimation is made within an artificial neural network (ANN) based on the amount of doping and production methods. Results of the estimations show that the Seebeck coefficient can approximate the real values with an average accuracy of 94.4%. In addition, ANN has detected that any change in production methods is followed by a change in the Seebeck coefficient.
DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.
Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

PubMed

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.
Object-processing neural efficiency differentiates object from spatial visualizers.

PubMed

Motes, Michael A; Malach, Rafael; Kozhevnikov, Maria

2008-11-19

The visual system processes object properties and spatial properties in distinct subsystems, and we hypothesized that this distinction might extend to individual differences in visual processing. We conducted a functional MRI study investigating the neural underpinnings of individual differences in object versus spatial visual processing. Nine participants of high object-processing ability ('object' visualizers) and eight participants of high spatial-processing ability ('spatial' visualizers) were scanned, while they performed an object-processing task. Object visualizers showed lower bilateral neural activity in lateral occipital complex and lower right-lateralized neural activity in dorsolateral prefrontal cortex. The data indicate that high object-processing ability is associated with more efficient use of visual-object resources, resulting in less neural activity in the object-processing pathway.
Effect of the shell material and confinement type on the conversion efficiency of core/shell quantum dot nanocrystal solar cells.

PubMed

Sahin, Mehmet

2018-05-23

In this study, the effects of the shell material and confinement type on the conversion efficiency of core/shell quantum dot nanocrystal (QDNC) solar cells have been investigated in detail. For this purpose, the conventional, i.e. original, detailed balance model, developed by Shockley and Queisser to calculate an upper limit for the conversion efficiency of silicon p-n junction solar cells, is modified in a simple and effective way to calculate the conversion efficiency of core/shell QDNC solar cells. Since the existing model relies on the gap energy ([Formula: see text]) of the solar cell, it does not make an estimation about the effect of QDNC materials on the efficiency of the solar cells, and gives the same efficiency values for several QDNC solar cells with the same [Formula: see text]. The proposed modification, however, estimates a conversion efficiency in relation to the material properties and also the confinement type of the QDNCs. The results of the modified model show that, in contrast to the original one, the conversion efficiencies of different QDNC solar cells, even if they have the same [Formula: see text], become different depending upon the confinement type and shell material of the core/shell QDNCs, and this is crucial in the design and fabrication of the new generation solar cells to predict the confinement type and also appropriate QDNC materials for better efficiency.
Experimental evaluation of heat transfer efficiency of nanofluid in a double pipe heat exchanger and prediction of experimental results using artificial neural networks

NASA Astrophysics Data System (ADS)

Maddah, Heydar; Ghasemi, Nahid

2017-12-01

In this study, heat transfer efficiency of water and iron oxide nanofluid in a double pipe heat exchanger equipped with a typical twisted tape is experimentally investigated and impacts of the concentration of nanofluid and twisted tape on the heat transfer efficiency are also studied. Experiments were conducted under the laminar and turbulent flow for Reynolds numbers in the range of 1000 to 6000 and the concentration of nanofluid was 0.01, 0.02 and 0.03 wt%. In order to model and predict the heat transfer efficiency, an artificial neural network was used. The temperature of the hot fluid (nanofluid), the temperature of the cold fluid (water), mass flow rate of hot fluid (nanofluid), mass flow rate of cold fluid (water), the concentration of nanofluid and twist ratio are input data in artificial neural network and heat transfer is output or target. Heat transfer efficiency in the presence of 0.03 wt% nanofluid increases by 30% while using both the 0.03 wt% nanofluid and twisted tape with twist ratio 2 increases the heat transfer efficiency by 60%. Implementation of various structures of neural network with different number of neurons in the middle layer showed that 1-10-6 arrangement with the correlation coefficient 0.99181 and normal root mean square error 0.001621 is suggested as a desirable arrangement. The above structure has been successful in predicting 72% to 97%of variation in heat transfer efficiency characteristics based on the independent variables changes. In total, comparing the predicted results in this study with other studies and also the statistical measures shows the efficiency of artificial neural network.
miR-146b-5p promotes the neural conversion of pluripotent stem cells by targeting Smad4

PubMed Central

Zhang, Nianping; Lyu, Ying; Pan, Xuebing; Xu, Liping; Xuan, Aiguo; He, Xiaosong; Huang, Wandan; Long, Dahong

2017-01-01

Pluripotent stem cells (PSCs) are regarded as potential sources that provide specific neural cells for cell therapy in some nervous system diseases. However, the mechanisms underlying the neural differentiation of PSCs remain largely unknown. MicroRNAs (miRNAs or miRs) are a class of small non-protein-coding RNAs that act as critical regulatory molecules in many cellular processes. In this study, we found that miR-146b-5p expression was markedly increased following the neural induction of mouse embryonic stem cells (ESCs) or induced PSCs (iPSCs). In this study, to further identify the role of miR-146b-5p, we generated stable miR-146b-5p- overexpressing ESC and iPSC cell lines, and induced the differentiation of these cells by the adherent monolayer culture method. In the miR-146b-5p-overexpressing ESC- or iPSC- derived cultures, RT-qPCR analysis revealed that the mRNA expression levels of neuroectoderm markers, such as Sox1, Nestin and Pax6, were markedly increased, and flow cytometric analysis verified that the number of Nestin-positive cells was higher in the miR-146b-5p-overexpressing compared with the control cells. Mechanistically, the miR-146b-5p-overexpressing ESCs or iPSCs exhibited a significant reduction in Oct4 expression, which may be an explanation for these cells having a tendency to differentiate towards the neural lineage. Moreover, we confirmed that miR-146b-5p directly targeted Smad4 and negatively regulated the transforming growth factor (TGF)-β signaling pathway, which contributed to the neural commitment of PSCs. Collectively, our findings uncover the essential role of miR-146b-5p in the neural conversion of PSCs. PMID:28713933
Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

PubMed Central

Malik, Wasim Q.; Truccolo, Wilson; Brown, Emery N.; Hochberg, Leigh R.

2011-01-01

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. PMID:21078582
Enhancement of the efficiency of dye-sensitized solar cell with multi-wall carbon nanotubes/polypyrrole composite counter electrodes prepared by electrophoresis/electrochemical polymerization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Jun; Niu, Hai-jun; Wen, Hai-lin

2013-03-15

Graphical abstract: The overall energy conversion efficiency of the DSSC employing the MWCNT/PPy CE reached 3.78%. Compared with a reference DSSC using single MWCNT film CE with efficiency of 2.68%, the energy conversion efficiency was increased by 41.04%. Highlights: ► MWCNT/PPy composite film prepared by electrodeposition layer by layer was used as counter electrode in DSSC. ► The overall energy conversion efficiency of the DSSC was 3.78% by employing the composite film. ► The energy conversion efficiency increased by 41.04% compared with efficiency of 2.68% by using the single MWCNT film. ► We analyzed the mechanism and influence factor ofmore » electron transfer in the composite electrode by EIS. - Abstract: For the purpose of replacing the precious Pt counter electrode in dye-sensitized solar cells (DSSCs) with higher energy conversion efficiency, multi-wall carbon nanotube (MWCNT)/polypyrrole (PPy) double layers film counter electrode (CE) was fabricated by electrophoresis and cyclic voltammetry (CV) layer by layer. Atom force microscopy (AFM), scanning electron microscopy (SEM) and transmission electron microscope (TEM) demonstrated the morphologies of the composite electrode and Raman spectroscopy verified the PPy had come into being. The overall energy conversion efficiency of the DSSC employing the MWCNT/PPy CE reached 3.78%. Compared with a reference DSSC using single MWCNT film CE with efficiency of 2.68%, the energy conversion efficiency was increased by 41.04%. The result of impedance showed that the charge transfer resistance R{sub ct} of the MWCNT/PPy CE had the lowest value compared to that of MWCNT or PPy electrode. These results indicate that the composite film with high conductivity, high active surface area, and good catalytic properties for I{sub 3}{sup −} reduction can potentially be used as the CE in a high-performance DSSC.« less
Optimal Control of Induction Machines to Minimize Transient Energy Losses

NASA Astrophysics Data System (ADS)

Plathottam, Siby Jose

Induction machines are electromechanical energy conversion devices comprised of a stator and a rotor. Torque is generated due to the interaction between the rotating magnetic field from the stator, and the current induced in the rotor conductors. Their speed and torque output can be precisely controlled by manipulating the magnitude, frequency, and phase of the three input sinusoidal voltage waveforms. Their ruggedness, low cost, and high efficiency have made them ubiquitous component of nearly every industrial application. Thus, even a small improvement in their energy efficient tend to give a large amount of electrical energy savings over the lifetime of the machine. Hence, increasing energy efficiency (reducing energy losses) in induction machines is a constrained optimization problem that has attracted attention from researchers. The energy conversion efficiency of induction machines depends on both the speed-torque operating point, as well as the input voltage waveform. It also depends on whether the machine is in the transient or steady state. Maximizing energy efficiency during steady state is a Static Optimization problem, that has been extensively studied, with commercial solutions available. On the other hand, improving energy efficiency during transients is a Dynamic Optimization problem that is sparsely studied. This dissertation exclusively focuses on improving energy efficiency during transients. This dissertation treats the transient energy loss minimization problem as an optimal control problem which consists of a dynamic model of the machine, and a cost functional. The rotor field oriented current fed model of the induction machine is selected as the dynamic model. The rotor speed and rotor d-axis flux are the state variables in the dynamic model. The stator currents referred to as d-and q-axis currents are the control inputs. A cost functional is proposed that assigns a cost to both the energy losses in the induction machine, as well as the deviations from desired speed-torque-magnetic flux setpoints. Using Pontryagin's minimum principle, a set of necessary conditions that must be satisfied by the optimal control trajectories are derived. The conditions are in the form a two-point boundary value problem, that can be solved numerically. The conjugate gradient method that was modified using the Hestenes-Stiefel formula was used to obtain the numerical solution of both the control and state trajectories. Using the distinctive shape of the numerical trajectories as inspiration, analytical expressions were derived for the state, and control trajectories. It was shown that the trajectory could be fully described by finding the solution of a one-dimensional optimization problem. The sensitivity of both the optimal trajectory and the optimal energy efficiency to different induction machine parameters were analyzed. A non-iterative solution that can use feedback for generating optimal control trajectories in real time was explored. It was found that an artificial neural network could be trained using the numerical solutions and made to emulate the optimal control trajectories with a high degree of accuracy. Hence a neural network along with a supervisory logic was implemented and used in a real-time simulation to control the Finite Element Method model of the induction machine. The results were compared with three other control regimes and the optimal control system was found to have the highest energy efficiency for the same drive cycle.

Efficiency of Energy Harvesting in Ni-Mn-Ga Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Lindquist, Paul; Hobza, Tony; Patrick, Charles; Müllner, Peter

2018-03-01

Many researchers have reported on the voltage and power generated while energy harvesting using Ni-Mn-Ga shape memory alloys; few researchers report on the power conversion efficiency of energy harvesting. We measured the magneto-mechanical behavior and energy harvesting of Ni-Mn-Ga shape memory alloys to quantify the efficiency of energy harvesting using the inverse magneto-plastic effect. At low frequencies, less than 150 Hz, the power conversion efficiency is less than 0.1%. Power conversion efficiency increases with (i) increasing actuation frequency, (ii) increasing actuation stroke, and (iii) decreasing twinning stress. Extrapolating the results of low-frequency experiments to the kHz actuation regime yields a power conversion factor of about 20% for 3 kHz actuation frequency, 7% actuation strain, and 0.05 MPa twinning stress.
Experimental feasibility of the airborne measurement of absolute oil fluorescence spectral conversion efficiency

NASA Technical Reports Server (NTRS)

Hoge, F. E.; Swift, R. N.

1983-01-01

Airborne lidar oil spill experiments carried out to determine the practicability of the AOFSCE (absolute oil fluorescence spectral conversion efficiency) computational model are described. The results reveal that the model is suitable over a considerable range of oil film thicknesses provided the fluorescence efficiency of the oil does not approach the minimum detection sensitivity limitations of the lidar system. Separate airborne lidar experiments to demonstrate measurement of the water column Raman conversion efficiency are also conducted to ascertain the ultimate feasibility of converting such relative oil fluorescence to absolute values. Whereas the AOFSCE model is seen as highly promising, further airborne water column Raman conversion efficiency experiments with improved temporal or depth-resolved waveform calibration and software deconvolution techniques are thought necessary for a final determination of suitability.
Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers.

PubMed

Taheri, Mahboobeh; Mohebbi, Ali

2008-08-30

In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm (GA), has been used to predict collection efficiency in venturi scrubbers. The experimental input data, including particle diameter, throat gas velocity, liquid to gas flow rate ratio, throat hydraulic diameter, pressure drop across the venturi scrubber and collection efficiency as an output, have been used to create a GA-artificial neural network (ANN) model. The testing results from the model are in good agreement with the experimental data. Comparison of the results of the GA optimized ANN model with the results from the trial-and-error calibrated ANN model indicates that the GA-ANN model is more efficient. Finally, the effects of operating parameters such as liquid to gas flow rate ratio, throat gas velocity, and particle diameter on collection efficiency were determined.
Highly-efficient enzymatic conversion of crude algal oils into biodiesel.

PubMed

Wang, Yao; Liu, Jin; Gerken, Henri; Zhang, Chengwu; Hu, Qiang; Li, Yantao

2014-11-01

Energy-intensive chemical conversion of crude algal oils into biodiesel is a major barrier for cost-effective algal biofuel production. To overcome this problem, we developed an enzyme-based platform for conversion of crude algal oils into fatty acid methyl esters. Crude algal oils were extracted from the oleaginous microalga Nannochloropsis oceanica IMET1 and converted by an immobilized lipase from Candida antarctica. The effects of different acyl acceptors, t-butanol as a co-solvent, oil to t-butanol ratio, oil to methanol ratio, temperature and reaction time on biodiesel conversion efficiency were studied. The conversion efficiency reached 99.1% when the conversion conditions were optimized, i.e., an oil to t-butanol weight ratio of 1:1, an oil to methanol molar ratio of 1:12, and a reaction time of 4h at 25°C. The enzymatic conversion process developed in this study may hold a promise for low energy consumption, low wastewater-discharge biochemical conversion of algal feedstocks into biofuels. Published by Elsevier Ltd.
Discrete-time neural network for fast solving large linear L1 estimation problems and its application to image restoration.

PubMed

Xia, Youshen; Sun, Changyin; Zheng, Wei Xing

2012-05-01

There is growing interest in solving linear L1 estimation problems for sparsity of the solution and robustness against non-Gaussian noise. This paper proposes a discrete-time neural network which can calculate large linear L1 estimation problems fast. The proposed neural network has a fixed computational step length and is proved to be globally convergent to an optimal solution. Then, the proposed neural network is efficiently applied to image restoration. Numerical results show that the proposed neural network is not only efficient in solving degenerate problems resulting from the nonunique solutions of the linear L1 estimation problems but also needs much less computational time than the related algorithms in solving both linear L1 estimation and image restoration problems.
Character recognition from trajectory by recurrent spiking neural networks.

PubMed

Jiangrong Shen; Kang Lin; Yueming Wang; Gang Pan

2017-07-01

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.
Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.
Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

PubMed Central

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987
Monthly water quality forecasting and uncertainty assessment via bootstrapped wavelet neural networks under missing data for Harbin, China.

PubMed

Wang, Yi; Zheng, Tong; Zhao, Ying; Jiang, Jiping; Wang, Yuanyuan; Guo, Liang; Wang, Peng

2013-12-01

In this paper, bootstrapped wavelet neural network (BWNN) was developed for predicting monthly ammonia nitrogen (NH(4+)-N) and dissolved oxygen (DO) in Harbin region, northeast of China. The Morlet wavelet basis function (WBF) was employed as a nonlinear activation function of traditional three-layer artificial neural network (ANN) structure. Prediction intervals (PI) were constructed according to the calculated uncertainties from the model structure and data noise. Performance of BWNN model was also compared with four different models: traditional ANN, WNN, bootstrapped ANN, and autoregressive integrated moving average model. The results showed that BWNN could handle the severely fluctuating and non-seasonal time series data of water quality, and it produced better performance than the other four models. The uncertainty from data noise was smaller than that from the model structure for NH(4+)-N; conversely, the uncertainty from data noise was larger for DO series. Besides, total uncertainties in the low-flow period were the biggest due to complicated processes during the freeze-up period of the Songhua River. Further, a data missing-refilling scheme was designed, and better performances of BWNNs for structural data missing (SD) were observed than incidental data missing (ID). For both ID and SD, temporal method was satisfactory for filling NH(4+)-N series, whereas spatial imputation was fit for DO series. This filling BWNN forecasting method was applied to other areas suffering "real" data missing, and the results demonstrated its efficiency. Thus, the methods introduced here will help managers to obtain informed decisions.
The neural implementation of task rule activation in the task-cuing paradigm: an event-related fMRI study.

PubMed

Shi, Yiquan; Zhou, Xiaolin; Müller, Hermann J; Schubert, Torsten

2010-07-01

To isolate the neural correlates for task rule activation from those related to general task preparation, the effect of a cue explicitly specifying the S-R correspondences (rule-cue) was contrasted with the effects of a cue specifying only the task to performed (task-cue). While the task-cue provides merely information about the type of task, the rule-cue is explicit about both the task type and the task rule (i.e., the set of S-R correspondences). The rule-cue was expected to activate the task rule more efficiently in the preparation period (prior to target presentation); by contrast, in the task-cue condition, part of the task rule activation was expected to be postponed into the task execution period (following the presentation of the target). In an event-related fMRI experiment, we found the right anterior and middle parts of the middle frontal and superior frontal gyri, the right inferior frontal junction, the pre-SMA, as well as the right superior and inferior parietal lobes to show larger activation elicited by the rule-cue than by the task-cue prior to target presentation. Conversely, the results revealed larger activations in these regions in the task-cue than in the rule-cue condition during the task execution period. In summary, this study identified some of the neural correlates of task rule activation and showed that these are a subset of the general task preparation network. Copyright (c) 2010 Elsevier Inc. All rights reserved.
An evaluation of tannery industry wastewater treatment sludge gasification by artificial neural network modeling.

PubMed

Ongen, Atakan; Ozcan, H Kurtulus; Arayıcı, Semiha

2013-12-15

This paper reports on the calorific value of synthetic gas (syngas) produced by gasification of dewatered sludge derived from treatment of tannery wastewater. Proximate and ultimate analyses of samples were performed. Thermochemical conversion alters the chemical structure of the waste. Dried air was used as a gasification agent at varying flow rates, which allowed the feedstock to be quickly converted into gas by means of different heterogeneous reactions. A lab-scale updraft fixed-bed steel reactor was used for thermochemical conversion of sludge samples. Artificial neural network (ANN) modeling techniques were used to observe variations in the syngas related to operational conditions. Modeled outputs showed that temporal changes of model predictions were in close accordance with real values. Correlation coefficients (r) showed that the ANN used in this study gave results with high sensitivity. Copyright © 2013 Elsevier B.V. All rights reserved.
The Neural Network In Coordinate Transformation

NASA Astrophysics Data System (ADS)

Urusan, Ahmet Yucel

2011-12-01

In international literature, Coordinate operations is divided into two categories. They are coordinate conversion and coordinate transformation. Coordinates converted from coordinate system A to coordinate system B in the same datum (mean origine, scale and axis directions are same) by coordinate conversion. There are two different datum in coordinate transformation. The basis of each datum to a different coordinate reference system. In Coordinate transformation, coordinates are transformed from coordinate reference system A to coordinate referance system B. Geodetic studies based on physical measurements. Coordinate transformation needs identical points which were measured in each coordinate reference system (A and B). However it is difficult (and need a big reserved budget) to measure in some places like as top of mountain, boundry of countries and seaside. In this study, this sample problem solution was researched. The method of learning which is one of the neural network methods, was used for solution of this problem.
Maximum efficiency of state-space models of nanoscale energy conversion devices

NASA Astrophysics Data System (ADS)

Einax, Mario; Nitzan, Abraham

2016-07-01

The performance of nano-scale energy conversion devices is studied in the framework of state-space models where a device is described by a graph comprising states and transitions between them represented by nodes and links, respectively. Particular segments of this network represent input (driving) and output processes whose properly chosen flux ratio provides the energy conversion efficiency. Simple cyclical graphs yield Carnot efficiency for the maximum conversion yield. We give general proof that opening a link that separate between the two driving segments always leads to reduced efficiency. We illustrate these general result with simple models of a thermoelectric nanodevice and an organic photovoltaic cell. In the latter an intersecting link of the above type corresponds to non-radiative carriers recombination and the reduced maximum efficiency is manifested as a smaller open-circuit voltage.
Maximum efficiency of state-space models of nanoscale energy conversion devices.

PubMed

Einax, Mario; Nitzan, Abraham

2016-07-07

The performance of nano-scale energy conversion devices is studied in the framework of state-space models where a device is described by a graph comprising states and transitions between them represented by nodes and links, respectively. Particular segments of this network represent input (driving) and output processes whose properly chosen flux ratio provides the energy conversion efficiency. Simple cyclical graphs yield Carnot efficiency for the maximum conversion yield. We give general proof that opening a link that separate between the two driving segments always leads to reduced efficiency. We illustrate these general result with simple models of a thermoelectric nanodevice and an organic photovoltaic cell. In the latter an intersecting link of the above type corresponds to non-radiative carriers recombination and the reduced maximum efficiency is manifested as a smaller open-circuit voltage.
An efficient optical architecture for sparsely connected neural networks

NASA Technical Reports Server (NTRS)

Hine, Butler P., III; Downie, John D.; Reid, Max B.

1990-01-01

An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.
10.2% power conversion efficiency polymer tandem solar cells consisting of two identical sub-cells.

PubMed

You, Jingbi; Chen, Chun-Chao; Hong, Ziruo; Yoshimura, Ken; Ohya, Kenichiro; Xu, Run; Ye, Shenglin; Gao, Jing; Li, Gang; Yang, Yang

2013-08-07

Polymer tandem solar cells with 10.2% power conversion efficiency are demonstrated via stacking two PDTP-DFBT:PC₇₁ BM bulk heterojunctions, connected by MoO₃/PEDOT:PSS/ZnO as an interconnecting layer. The tandem solar cells increase the power conversion efficiency of the PDTP-DFBT:PC₇₁ BM system from 8.1% to 10.2%, successfully demonstrating polymer tandem solar cells with identical sub-cells of double-digit efficiency. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A method for determining the conversion efficiency of multiple-cell photovoltaic devices

NASA Astrophysics Data System (ADS)

Glatfelter, Troy; Burdick, Joseph

A method for accurately determining the conversion efficiency of any multiple-cell photovoltaic device under any arbitrary reference spectrum is presented. This method makes it possible to obtain not only the short-circuit current, but also the fill factor, the open-circuit voltage, and hence the conversion efficiency of a multiple-cell device under any reference spectrum. Results are presented which allow a comparison of the I-V parameters of two-terminal, two- and three-cell tandem devices measured under a multiple-source simulator with the same parameters measured under different reference spectra. It is determined that the uncertainty in the conversion efficiency of a multiple-cell photovoltaic device obtained with this method is less than +/-3 percent.
In-use catalyst surface area and its relation to HC conversion efficiency and FTP emissions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donahue, K.S.; Sabourin, M.A.; Larson, R.E.

1986-01-01

Surface area data, steady-state hydrocarbon conversion efficiency data, and hydrocarbon emissions results have been determined for catalysts collected by the U.S. Environmental Protection Agency from properly maintained 1981 and 1982 model year vehicles. Catalysts covered in this study were limited to those with three-way-plus-oxidation monolith technologies. Catalyst surface areas were measured using the BET method, conversion efficiencies were measured on an exhaust gas generator, and emissions results were determined using the Urban Driving Schedule of the Federal Test Procedure. Results indicate that correlation of catalyst surface area data with hydrocarbon conversion efficiency data and hydrocarbon emissions results is significant formore » the sample studied.« less
Computer-Aided Screening of Conjugated Polymers for Organic Solar Cell: Classification by Random Forest.

PubMed

Nagasawa, Shinji; Al-Naamani, Eman; Saeki, Akinori

2018-05-17

Owing to the diverse chemical structures, organic photovoltaic (OPV) applications with a bulk heterojunction framework have greatly evolved over the last two decades, which has produced numerous organic semiconductors exhibiting improved power conversion efficiencies (PCEs). Despite the recent fast progress in materials informatics and data science, data-driven molecular design of OPV materials remains challenging. We report a screening of conjugated molecules for polymer-fullerene OPV applications by supervised learning methods (artificial neural network (ANN) and random forest (RF)). Approximately 1000 experimental parameters including PCE, molecular weight, and electronic properties are manually collected from the literature and subjected to machine learning with digitized chemical structures. Contrary to the low correlation coefficient in ANN, RF yields an acceptable accuracy, which is twice that of random classification. We demonstrate the application of RF screening for the design, synthesis, and characterization of a conjugated polymer, which facilitates a rapid development of optoelectronic materials.
Evidence of significant down-conversion in a Si-based solar cell using CuInS2/ZnS core shell quantum dots

NASA Astrophysics Data System (ADS)

Gardelis, Spiros; Nassiopoulou, Androula G.

2014-05-01

We report on the increase of up to 37.5% in conversion efficiency of a Si-based solar cell after deposition of light-emitting Cd-free, CuInS2/ZnS core shell quantum dots on the active area of the cell due to the combined effect of down-conversion and the anti- reflecting property of the dots. We clearly distinguished the effect of down-conversion from anti-reflection and estimated an enhancement of up to 10.5% in the conversion efficiency due to down-conversion.

Neural networks: Application to medical imaging

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.

1994-01-01

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.
Alpha, delta and theta rhythms in a neural net model. Comparison with MEG data.

PubMed

Kotini, A; Anninos, P

2016-01-07

The aim of this study is to provide information regarding the comparison of a neural model to MEG measurements. Our study population consisted of 10 epileptic patients and 10 normal subjects. The epileptic patients had high MEG amplitudes characterized with θ (4-7 Hz) or δ (2-3 Hz) rhythms and absence of α-rhythm (8-13 Hz). The statistical analysis of such activities corresponded to Poisson distribution. Conversely, the MEG from normal subjects had low amplitudes, higher frequencies and presence of α-rhythm (8-13 Hz). Such activities were not synchronized and their distributions were Gauss. These findings were in agreement with our theoretical neural model. The comparison of the neural network with MEG data provides information about the status of brain function in epileptic and normal states. Copyright © 2015 Elsevier Ltd. All rights reserved.
Ion fluxes and neurotransmitters signaling in neural development.

PubMed

Andäng, Michael; Lendahl, Urban

2008-06-01

The brain develops and functions in a complex ionic milieu, which is a prerequisite for neurotransmitter function and neuronal signaling. Neurotransmitters and ion fluxes are, however, important not only in neuronal signaling, but also in the control of neural differentiation, and in this review, we highlight the recent advances in our understanding of how the gamma-amino butyric acid (GABA) neurotransmitter and ion fluxes are relevant for cell cycle control and neural differentiation. Conversely, proteins previously associated with ion transport across membranes have been endowed with novel ion-independent functions, and we discuss this in the context of gap junctions in cell adhesion and of the neuron-specific K(+)-Cl(-) cotransporter KCC2 in dendritic spine development. Collectively, these findings provide a richer and more complex picture of when ion fluxes are needed in neural development and when they are not.
Neural nets on the MPP

NASA Technical Reports Server (NTRS)

Hastings, Harold M.; Waner, Stefan

1987-01-01

The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.
High-Efficiency Photovoltaic System Using Partially-Connected DC-DC Converter

NASA Astrophysics Data System (ADS)

Uno, Masatoshi; Kukita, Akio; Tanaka, Koji

Power conversion electronics for photovoltaic (PV) systems are desired to operate as efficiently as possible to exploit the power generated by PV modules. This paper proposes a novel PV system in which a dc-dc converter is partially connected to series-connected PV modules. The proposed system achieves high power-conversion efficiency by reducing the passing power and input/output voltages of the converter. The theoretical operating principle was experimentally validated. Resultant efficiency performances of the proposed and conventional systems demonstrated that the proposed system was more efficient in terms of power conversion though the identical converter was used for the both systems.
Human adenovirus serotypes 4p and 11p are efficiently expressed in cell lines of neural tumour origin.

PubMed

Skog, Johan; Mei, Ya-Fang; Wadell, Göran

2002-06-01

Most currently used adenovirus vectors are based upon adenovirus serotypes 2 and 5 (Ad2 and Ad5), which have limited efficiencies for gene transfer to human neural cells. Both serotypes bind to the known adenovirus receptor, CAR (coxsackievirus and adenovirus receptor), and have restricted cell tropism. The purpose of this study was to find vector candidates that are superior to Ad5 in infecting human neural tumours. Using flow cytometry, the vector candidates Ad4p, Ad11p and Ad17p were compared to the commonly used adenovirus vector Ad5v for their binding capacity to neural cell lines derived from glioblastoma, medulloblastoma and neuroblastoma cell lines. The production of viral structural proteins and the CAR-binding properties of the different serotypes were also assessed in these cells. Computer-based models of the fibre knobs of Ad4p and Ad17 were created based upon the crystallized fibre knob structure of adenoviruses and analysed for putative receptor-interacting regions that differed from the fibre knob of Ad5. The non CAR-binding vector candidate Ad11p showed clearly the best binding capacity to all of the neural cell lines, binding more than 90% of cells of all of the neural cell lines tested, in contrast to 20% or less for the commonly used vector Ad5v. Ad4p and Ad11p were also internalized and produced viral proteins more successfully than Ad5. Ad4p showed a low binding ability but a very efficient capacity for infection in cell culture. Ad17p virions neither bound or efficiently infected any of the neural cell lines studied.
Neural network fusion capabilities for efficient implementation of tracking algorithms

NASA Astrophysics Data System (ADS)

Sundareshan, Malur K.; Amoozegar, Farid

1997-03-01

The ability to efficiently fuse information of different forms to facilitate intelligent decision making is one of the major capabilities of trained multilayer neural networks that is now being recognized. While development of innovative adaptive control algorithms for nonlinear dynamical plants that attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. We describe the capabilities and functionality of neural network algorithms for data fusion and implementation of tracking filters. To discuss details and to serve as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target- tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The innovation lies in the way the fusion of multisensor data is accomplished to facilitate improved estimation without increasing the computational complexity of the dynamical state estimator itself.
Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

NASA Astrophysics Data System (ADS)

Wu, Wei; Cui, Bao-Tong

2007-07-01

In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.
Exceeding the solar cell Shockley-Queisser limit via thermal up-conversion of low-energy photons

NASA Astrophysics Data System (ADS)

Boriskina, Svetlana V.; Chen, Gang

2014-03-01

Maximum efficiency of ideal single-junction photovoltaic (PV) cells is limited to 33% (for 1 sun illumination) by intrinsic losses such as band edge thermalization, radiative recombination, and inability to absorb below-bandgap photons. This intrinsic thermodynamic limit, named after Shockley and Queisser (S-Q), can be exceeded by utilizing low-energy photons either via their electronic up-conversion or via the thermophotovoltaic (TPV) conversion process. However, electronic up-conversion systems have extremely low efficiencies, and practical temperature considerations limit the operation of TPV converters to the narrow-gap PV cells. Here we develop a conceptual design of a hybrid TPV platform, which exploits thermal up-conversion of low-energy photons and is compatible with conventional silicon PV cells by using spectral and directional selectivity of the up-converter. The hybrid platform offers sunlight-to-electricity conversion efficiency exceeding that imposed by the S-Q limit on the corresponding PV cells across a broad range of bandgap energies, under low optical concentration (1-300 suns), operating temperatures in the range 900-1700 K, and in simple flat panel designs. We demonstrate maximum conversion efficiency of 73% under illumination by non-concentrated sunlight. A detailed analysis of non-ideal hybrid platforms that allows for up to 15% of absorption/re-emission losses yields limiting efficiency value of 45% for Si PV cells.
Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.
Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616
Development of a high efficiency thin silicon solar cell

NASA Technical Reports Server (NTRS)

Storti, G.; Culik, J.; Wrigley, C.

1980-01-01

Significant improvements in open-circuit voltage and conversion efficiency, even on relatively high bulk resistivity silicon, were achieved by using a screen-printed aluminum paste back surface field. A 4 sq cm 50 micron m thick cell was fabricated from textured 10 omega-cm silicon which had an open-circuit voltage of 595 mV and AMO conversion efficiency at 25 C of 14.3%. The best 4 sq cm 50 micron thick cell (2 omega-cm silicon) produced had an open-circuit voltage of 607 mV and an AMO conversion efficiency of 15%. Processing modifications are described which resulted in better front contact integrity and reduced breakage. These modifications were utilized in the thin cell pilot line to fabricate 4 sq cm cells with an average AMO conversion efficiency at 25 C of better than 12.5% and with lot yields as great as 51% of starts; a production rate of 10,000 cells per month was demonstrated. A pilot line was operated which produced large area (25 cm) ultra-thin cells with an average AMO conversion efficiency at 25 deg of better than 11.5% and a lot yield as high as 17%.
Identification of bioconversion quantitative trait loci in the interspecific cross Sorghum bicolor × Sorghum propinquum.

PubMed

Vandenbrink, Joshua P; Goff, Valorie; Jin, Huizhe; Kong, Wenqian; Paterson, Andrew H; Feltus, F Alex

2013-09-01

For lignocellulosic bioenergy to be economically viable, genetic improvements must be made in feedstock quality including both biomass total yield and conversion efficiency. Toward this goal, multiple studies have considered candidate genes and discovered quantitative trait loci (QTL) associated with total biomass accumulation and/or grain production in bioenergy grass species including maize and sorghum. However, very little research has been focused on genes associated with increased biomass conversion efficiency. In this study, Trichoderma viride fungal cellulase hydrolysis activity was measured for lignocellulosic biomass (leaf and stem tissue) obtained from individuals in a F5 recombinant inbred Sorghum bicolor × Sorghum propinquum mapping population. A total of 49 QTLs (20 leaf, 29 stem) were associated with enzymatic conversion efficiency. Interestingly, six high-density QTL regions were identified in which four or more QTLs overlapped. In addition to enzymatic conversion efficiency QTLs, two QTLs were identified for biomass crystallinity index, a trait which has been shown to be inversely correlated with conversion efficiency in bioenergy grasses. The identification of these QTLs provides an important step toward identifying specific genes relevant to increasing conversion efficiency of bioenergy feedstocks. DNA markers linked to these QTLs could be useful in marker-assisted breeding programs aimed at increasing overall bioenergy yields concomitant with selection of high total biomass genotypes.
Down-conversion emission of Ce3+-Tb3+ co-doped CaF2 hollow spheres and application for solar cells

NASA Astrophysics Data System (ADS)

Cheng, Yufei; Wang, Yongbo; Teng, Feng; Dong, Hua; Chen, Lida; Mu, Jianglong; Sun, Qian; Fan, Jun; Hu, Xiaoyun; Miao, Hui

2018-03-01

Luminescent downconversion is a promising way to harvest ultraviolet sunlight and transform it into visible light that can be absorbed by solar cells, and has potential to improve their photoelectric conversion efficiency. In this work, the uniform hollow spheres and well dispersed CaF2 phosphors doped with rare-earth Ce3+ and Tb3+ ions are prepared by a one-step hydrothermal synthesis method. Benefiting from the stronger ability of absorption and emission and excellent transparency property, we demonstrate that the application of the doped nanocrystals can efficiently improve visible light transmittance. The chosen phosphors are added in the SiO2 sols so as to get the anti-reflection coatings with wavelength conversion bi-functional films, promoting the optical transmittance in the visible and near-infrared range which matches with the range of the band gap energy of silicon semiconductor. Optimized photoelectric conversion efficiency of 14.35% and the external quantum efficiency over 70% from 450 to 950 nm are obtained through the silicon solar cells with 0.10 g phosphors coating. Compared with the pure glass devices, the photoelectric conversion efficiency is enhanced by 0.69%. This work indicates that fluorescent downconversion not only can serve as proof of principles for improving photoelectric conversion efficiency of solar cells but also may be helpful to practical application in the future.
Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

NASA Technical Reports Server (NTRS)

Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.

1993-01-01

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.
75 FR 31461 - Notice of Submission of Proposed Information Collection to OMB; Emergency Comment Request...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-03

... Proposed Information Collection to OMB; Emergency Comment Request; Conversion of Efficiencies Units to One... via Housing Notice and attached forms to permit the conversion of efficiencies to one-bedrooms provided it can be demonstrated that the conversion is warranted by local demands and results in the long...
Potential use and the energy conversion efficiency analysis of fermentation effluents from photo and dark fermentative bio-hydrogen production.

PubMed

Zhang, Zhiping; Li, Yameng; Zhang, Huan; He, Chao; Zhang, Quanguo

2017-12-01

Effluent of bio-hydrogen production system also can be adopted to produce methane for further fermentation, cogeneration of hydrogen and methane will significantly improve the energy conversion efficiency. Platanus Orientalis leaves were taken as the raw material for photo- and dark-fermentation bio-hydrogen production. The resulting concentrations of acetic, butyric, and propionic acids and ethanol in the photo- and dark-fermentation effluents were 2966mg/L and 624mg/L, 422mg/L and 1624mg/L, 1365mg/L and 558mg/L, and 866mg/L and 1352mg/L, respectively. Subsequently, we calculated the energy conversion efficiency according to the organic contents of the effluents and their energy output when used as raw material for methane production. The overall energy conversion efficiencies increased by 15.17% and 22.28%, respectively, when using the effluents of photo and dark fermentation. This two-step bio-hydrogen and methane production system can significantly improve the energy conversion efficiency of anaerobic biological treatment plants. Copyright © 2017. Published by Elsevier Ltd.
Improving Si solar cell performance using Mn:ZnSe quantum dot-doped PLMA thin film

PubMed Central

2013-01-01

Poly(lauryl methacrylate) (PLMA) thin film doped with Mn:ZnSe quantum dots (QDs) was spin-deposited on the front surface of Si solar cell for enhancing the solar cell efficiency via photoluminescence (PL) conversion. Significant solar cell efficiency enhancements (approximately 5% to 10%) under all-solar-spectrum (AM0) condition were observed after QD-doped PLMA coatings. Furthermore, the real contribution of the PL conversion was precisely assessed by investigating the photovoltaic responses of the QD-doped PLMA to monochromatic and AM0 light sources as functions of QD concentration, combined with reflectance and external quantum efficiency measurements. At a QD concentration of 1.6 mg/ml for example, among the efficiency enhancement of 5.96%, about 1.04% was due to the PL conversion, and the rest came from antireflection. Our work indicates that for the practical use of PL conversion in solar cell performance improvement, cautions are to be taken, as the achieved efficiency enhancement might not be wholly due to the PL conversion. PMID:23787125
Thermionic/AMTEC cascade converter concept for high-efficiency space power

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagan, T.H. van; Smith, J.N. Jr.; Schuller, M.

1996-12-31

This paper presents trade studies that address the use of the thermionic/AMTEC cell--a cascaded, high-efficiency, static power conversion concept that appears well-suited to space power applications. Both the thermionic and AMTEC power conversion approaches have been shown to be promising candidates for space power. Thermionics offers system compactness via modest efficiency at high heat rejection temperatures, and AMTEC offers high efficiency at modest heat rejection temperature. From a thermal viewpoint the two are ideally suited for cascaded power conversion: thermionic heat rejection and AMTEC heat source temperatures are essentially the same. In addition to realizing conversion efficiencies potentially as highmore » as 35--40%, such a cascade offers the following perceived benefits: survivability; simplicity; technology readiness; and technology growth. Mechanical approaches and thermal/electric matching criteria for integrating thermionics and AMTEC into a single conversion device are described. Focusing primarily on solar thermal space power applications, parametric trends are presented to show the performance and cost potential that should be achievable with present-day technology in cascaded thermionic/AMTEC systems.« less
Radiated microwave power transmission system efficiency measurements

NASA Technical Reports Server (NTRS)

Dickinson, R. M.; Brown, W. C.

1975-01-01

The measured and calculated results from determining the operating efficiencies of a laboratory version of a system for transporting electric power from one point to another via a wireless free space radiated microwave beam are reported. The system's overall end-to-end efficiency as well as intermediated conversion efficiencies were measured. The maximum achieved end-to-end dc-to-ac system efficiency was 54.18% with a probable error of + or - 0.94%. The dc-to-RF conversion efficiency was measured to be 68.87% + or - 1.0% and the RF-to-dc conversion efficiency was 78.67 + or - 1.1%. Under these conditions a dc power of 495.62 + or - 3.57 W was received with a free space transmitter antenna receiver antenna separation of 170.2 cm (67 in).

Enhanced Conversion Efficiency of III–V Triple-junction Solar Cells with Graphene Quantum Dots

PubMed Central

Lin, Tzu-Neng; Santiago, Svette Reina Merden S.; Zheng, Jie-An; Chao, Yu-Chiang; Yuan, Chi-Tsu; Shen, Ji-Lin; Wu, Chih-Hung; Lin, Cheng- An J.; Liu, Wei-Ren; Cheng, Ming-Chiang; Chou, Wu-Ching

2016-01-01

Graphene has been used to synthesize graphene quantum dots (GQDs) via pulsed laser ablation. By depositing the synthesized GQDs on the surface of InGaP/InGaAs/Ge triple-junction solar cells, the short-circuit current, fill factor, and conversion efficiency were enhanced remarkably. As the GQD concentration is increased, the conversion efficiency in the solar cell increases accordingly. A conversion efficiency of 33.2% for InGaP/InGaAs/Ge triple-junction solar cells has been achieved at the GQD concentration of 1.2 mg/ml, corresponding to a 35% enhancement compared to the cell without GQDs. On the basis of time-resolved photoluminescence, external quantum efficiency, and work-function measurements, we suggest that the efficiency enhancement in the InGaP/InGaAs/Ge triple-junction solar cells is primarily caused by the carrier injection from GQDs to the InGaP top subcell. PMID:27982073
A theoretical analysis of the current-voltage characteristics of solar cells. [and their energy conversion efficiency

NASA Technical Reports Server (NTRS)

Dunbar, P. M.; Hauser, J. R.

1976-01-01

Various mechanisms which limit the conversion efficiency of silicon solar cells were studied. The effects of changes in solar cell geometry such as layer thickness on performance were examined. The effects of various antireflecting layers were also examined. It was found that any single film antireflecting layer results in a significant surface loss of photons. The use of surface texturing techniques or low loss antireflecting layers can enhance by several percentage points the conversion efficiency of silicon cells. The basic differences between n(+)-p-p(+) and p(+)-n-n(+) cells are treated. A significant part of the study was devoted to the importance of surface region lifetime and heavy doping effects on efficiency. Heavy doping bandgap reduction effects are enhanced by low surface layer lifetimes, and conversely, the reduction in solar cell efficiency due to low surface layer lifetime is further enhanced by heavy doping effects. A series of computer studies is reported which seeks to determine the best cell structure and doping levels for maximum efficiency.
Efficient second-harmonic conversion of CW single-frequency Nd:YAG laser light by frequency locking to a monolithic ring frequency doubler

NASA Technical Reports Server (NTRS)

Gerstenberger, D. C.; Tye, G. E.; Wallace, R. W.

1991-01-01

Efficient second-harmonic conversion of the 1064-nm output of a diode-pumped CW single-frequency Nd:YAG laser to 532 nm was obtained by frequency locking the laser to a monolithic ring resonator constructed of magnesium-oxide-doped lithium niobate. The conversion efficiency from the fundamental to the second harmonic was 65 percent. Two hundred milliwatts of CW single-frequency 532-nm light were produced from 310 mW of power of 1064-nm light. This represents a conversion efficiency of 20 percent from the 1-W diode laser used to pump the Nd:YAG laser to single-frequency 532-nm output. No signs of degradation were observed for over 500 h of operation.
Ethanol production from renewable resources.

PubMed

Gong, C S; Cao, N J; Du, J; Tsao, G T

1999-01-01

Vast amounts of renewable biomass are available for conversion to liquid fuel, ethanol. In order to convert biomass to ethanol, the efficient utilization of both cellulose-derived and hemicellulose-derived carbohydrates is essential. Six-carbon sugars are readily utilized for this purpose. Pentoses, on the other hand, are more difficult to convert. Several metabolic factors limit the efficient utilization of pentoses (xylose and arabinose). Recent developments in the improvement of microbial cultures provide the versatility of conversion of both hexoses and pentoses to ethanol more efficiently. In addition, novel bioprocess technologies offer a promising prospective for the efficient conversion of biomass and recovery of ethanol.
Seismic signal auto-detecing from different features by using Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Huang, Y.; Zhou, Y.; Yue, H.; Zhou, S.

2017-12-01

We try Convolutional Neural Network to detect some features of seismic data and compare their efficience. The features include whether a signal is seismic signal or noise and the arrival time of P and S phase and each feature correspond to a Convolutional Neural Network. We first use traditional STA/LTA to recongnize some events and then use templete matching to find more events as training set for the Neural Network. To make the training set more various, we add some noise to the seismic data and make some synthetic seismic data and noise. The 3-component raw signal and time-frequancy ananlyze are used as the input data for our neural network. Our Training is performed on GPUs to achieve efficient convergence. Our method improved the precision in comparison with STA/LTA and template matching. We will move to recurrent neural network to see if this kind network is better in detect P and S phase.
Training Data Requirement for a Neural Network to Predict Aerodynamic Coefficients

NASA Technical Reports Server (NTRS)

Korsmeyer, David (Technical Monitor); Rajkumar, T.; Bardina, Jorge

2003-01-01

Basic aerodynamic coefficients are modeled as functions of angle of attack, speed brake deflection angle, Mach number, and side slip angle. Most of the aerodynamic parameters can be well-fitted using polynomial functions. We previously demonstrated that a neural network is a fast, reliable way of predicting aerodynamic coefficients. We encountered few under fitted and/or over fitted results during prediction. The training data for the neural network are derived from wind tunnel test measurements and numerical simulations. The basic questions that arise are: how many training data points are required to produce an efficient neural network prediction, and which type of transfer functions should be used between the input-hidden layer and hidden-output layer. In this paper, a comparative study of the efficiency of neural network prediction based on different transfer functions and training dataset sizes is presented. The results of the neural network prediction reflect the sensitivity of the architecture, transfer functions, and training dataset size.
ANNarchy: a code generation approach to neural simulations on parallel hardware

PubMed Central

Vitay, Julien; Dinkelbach, Helge Ü.; Hamker, Fred H.

2015-01-01

Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect) neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit). Several numerical methods are available to transform ordinary differential equations into an efficient C++code. We compare the parallel performance of the simulator to existing solutions. PMID:26283957
Bi2S3microspheres grown on graphene sheets as low-cost counter-electrode materials for dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Li, Guang; Chen, Xiaoshuang; Gao, Guandao

2014-02-01

In this work, we synthesized 3D Bi2S3 microspheres comprised of nanorods grown along the (211) facet on graphene sheets by a solvothermal route, and investigated its catalytic activities through I-V curves and conversion efficiency tests as the CE in DSSCs. Although the (211) facet has a large band gap for a Bi2S3 semiconductor, owing to the introduction of graphene into the system, its short-circuit current density, open-circuit voltage, fill factor, and efficiency were Jsc = 12.2 mA cm-2, Voc = 0.75 V, FF = 0.60, and η = 5.5%, respectively. By integrating it with graphene sheets, our material achieved the conversion efficiency of 5.5%, which is almost triple the best conversion efficiency value of the DSSCs with (211)-faceted 3D Bi2S3 without graphene (1.9%) reported in the latest literature. Since this conversion-efficient 3D material grown on the graphene sheets significantly improves its catalytic properties, it paves the way for designing and applying low-cost Pt-free CE materials in DSSC from inorganic nanostructures.In this work, we synthesized 3D Bi2S3 microspheres comprised of nanorods grown along the (211) facet on graphene sheets by a solvothermal route, and investigated its catalytic activities through I-V curves and conversion efficiency tests as the CE in DSSCs. Although the (211) facet has a large band gap for a Bi2S3 semiconductor, owing to the introduction of graphene into the system, its short-circuit current density, open-circuit voltage, fill factor, and efficiency were Jsc = 12.2 mA cm-2, Voc = 0.75 V, FF = 0.60, and η = 5.5%, respectively. By integrating it with graphene sheets, our material achieved the conversion efficiency of 5.5%, which is almost triple the best conversion efficiency value of the DSSCs with (211)-faceted 3D Bi2S3 without graphene (1.9%) reported in the latest literature. Since this conversion-efficient 3D material grown on the graphene sheets significantly improves its catalytic properties, it paves the way for designing and applying low-cost Pt-free CE materials in DSSC from inorganic nanostructures. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr06093d
Enhanced energy conversion efficiency from high strength synthetic organic wastewater by sequential dark fermentative hydrogen production and algal lipid accumulation.

PubMed

Ren, Hong-Yu; Liu, Bing-Feng; Kong, Fanying; Zhao, Lei; Xing, Defeng; Ren, Nan-Qi

2014-04-01

A two-stage process of sequential dark fermentative hydrogen production and microalgal cultivation was applied to enhance the energy conversion efficiency from high strength synthetic organic wastewater. Ethanol fermentation bacterium Ethanoligenens harbinense B49 was used as hydrogen producer, and the energy conversion efficiency and chemical oxygen demand (COD) removal efficiency reached 18.6% and 28.3% in dark fermentation. Acetate was the main soluble product in dark fermentative effluent, which was further utilized by microalga Scenedesmus sp. R-16. The final algal biomass concentration reached 1.98gL(-1), and the algal biomass was rich in lipid (40.9%) and low in protein (23.3%) and carbohydrate (11.9%). Compared with single dark fermentation stage, the energy conversion efficiency and COD removal efficiency of two-stage system remarkably increased 101% and 131%, respectively. This research provides a new approach for efficient energy production and wastewater treatment using a two-stage process combining dark fermentation and algal cultivation. Copyright © 2014 Elsevier Ltd. All rights reserved.
Supported black phosphorus nanosheets as hydrogen-evolving photocatalyst achieving 5.4% energy conversion efficiency at 353 K.

PubMed

Tian, Bin; Tian, Bining; Smith, Bethany; Scott, M C; Hua, Ruinian; Lei, Qin; Tian, Yue

2018-04-11

Solar-driven water splitting using powdered catalysts is considered as the most economical means for hydrogen generation. However, four-electron-driven oxidation half-reaction showing slow kinetics, accompanying with insufficient light absorption and rapid carrier combination in photocatalysts leads to low solar-to-hydrogen energy conversion efficiency. Here, we report amorphous cobalt phosphide (Co-P)-supported black phosphorus nanosheets employed as photocatalysts can simultaneously address these issues. The nanosheets exhibit robust hydrogen evolution from pure water (pH = 6.8) without bias and hole scavengers, achieving an apparent quantum efficiency of 42.55% at 430 nm and energy conversion efficiency of over 5.4% at 353 K. This photocatalytic activity is attributed to extremely efficient utilization of solar energy (~75% of solar energy) by black phosphorus nanosheets and high-carrier separation efficiency by amorphous Co-P. The hybrid material design realizes efficient solar-to-chemical energy conversion in suspension, demonstrating the potential of black phosphorus-based materials as catalysts for solar hydrogen production.
Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

PubMed

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

2013-11-01

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

PubMed

Contestabile, G; Yoshida, Y; Maruta, A; Kitayama, K

2012-12-03

We report broadband, all-optical wavelength conversion over 100 nm span, in full S- and C-band, with positive conversion efficiency with low optical input power exploiting dual pump Four-Wave-Mixing in a Quantum Dot Semiconductor Optical Amplifier (QD-SOA). We also demonstrate by Error Vector Magnitude analysis the full transparency of the conversion scheme for coherent modulation formats (QPSK, 8-PSK, 16-QAM, OFDM-16QAM) in the whole C-band.
Efficient Digital Implementation of The Sigmoidal Function For Artificial Neural Network

NASA Astrophysics Data System (ADS)

Pratap, Rana; Subadra, M.

2011-10-01

An efficient piecewise linear approximation of a nonlinear function (PLAN) is proposed. This uses simulink environment design to perform a direct transformation from X to Y, where X is the input and Y is the approximated sigmoidal output. This PLAN is then used within the outputs of an artificial neural network to perform the nonlinear approximation. In This paper, is proposed a method to implement in FPGA (Field Programmable Gate Array) circuits different approximation of the sigmoid function.. The major benefit of the proposed method resides in the possibility to design neural networks by means of predefined block systems created in System Generator environment and the possibility to create a higher level design tools used to implement neural networks in logical circuits.
Gliding Arc Plasmatron: Providing an Alternative Method for Carbon Dioxide Conversion.

PubMed

Ramakers, Marleen; Trenchev, Georgi; Heijkers, Stijn; Wang, Weizong; Bogaerts, Annemie

2017-06-22

Low-temperature plasmas are gaining a lot of interest for environmental and energy applications. A large research field in these applications is the conversion of CO 2 into chemicals and fuels. Since CO 2 is a very stable molecule, a key performance indicator for the research on plasma-based CO 2 conversion is the energy efficiency. Until now, the energy efficiency in atmospheric plasma reactors is quite low, and therefore we employ here a novel type of plasma reactor, the gliding arc plasmatron (GAP). This paper provides a detailed experimental and computational study of the CO 2 conversion, as well as the energy cost and efficiency in a GAP. A comparison with thermal conversion, other plasma types and other novel CO 2 conversion technologies is made to find out whether this novel plasma reactor can provide a significant contribution to the much-needed efficient conversion of CO 2 . From these comparisons it becomes evident that our results are less than a factor of two away from being cost competitive and already outperform several other new technologies. Furthermore, we indicate how the performance of the GAP can still be improved by further exploiting its non-equilibrium character. Hence, it is clear that the GAP is very promising for CO 2 conversion. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Free-space microwave-to-optical conversion via six-wave mixing in Rydberg atoms

NASA Astrophysics Data System (ADS)

Han, Jingshan; Vogt, Thibault; Gross, Christian; Jaksch, Dieter; Kiffner, Martin; Li, Wenhui

2017-04-01

The interconversion of millimeter waves and optical fields is an important and highly topical subject for classical and quantum technologies. In this talk, we report an experimental demonstration of coherent and efficient microwave-to-optical conversion in free space via six-wave mixing in Rydberg atoms. Our scheme utilizes the strong coupling of millimeter waves to Rydberg atoms as well as the frequency mixing based on electromagnetically induced transparency (EIT) that greatly enhances the nonlinearity for the conversion process. We achieve a free-space conversion efficiency of 0.25% with a bandwidth of about 4 MHz in our experiment. Optimized geometry and energy level configurations should enable the broadband interconversion of microwave and optical fields with near-unity efficiency. These results indicate the tremendous potential of Rydberg atoms for the efficient conversion between microwave and optical fields, and thus paves the way to many applications. This work is supported by Singapore Ministry of Education Academic Research Fund Tier 2 (Grant No. MOE2015-T2-1-085).
Apparatus and method for enabling quantum-defect-limited conversion efficiency in cladding-pumped Raman fiber lasers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heebner, John E.; Sridharan, Arun K.; Dawson, Jay Walter

Cladding-pumped Raman fiber lasers and amplifiers provide high-efficiency conversion efficiency at high brightness enhancement. Differential loss is applied to both single-pass configurations appropriate for pulsed amplification and laser oscillator configurations applied to high average power cw source generation.
Design of multi-energy Helds coupling testing system of vertical axis wind power system

NASA Astrophysics Data System (ADS)

Chen, Q.; Yang, Z. X.; Li, G. S.; Song, L.; Ma, C.

2016-08-01

The conversion efficiency of wind energy is the focus of researches and concerns as one of the renewable energy. The present methods of enhancing the conversion efficiency are mostly improving the wind rotor structure, optimizing the generator parameters and energy storage controller and so on. Because the conversion process involves in energy conversion of multi-energy fields such as wind energy, mechanical energy and electrical energy, the coupling effect between them will influence the overall conversion efficiency. In this paper, using system integration analysis technology, a testing system based on multi-energy field coupling (MEFC) of vertical axis wind power system is proposed. When the maximum efficiency of wind rotor is satisfied, it can match to the generator function parameters according to the output performance of wind rotor. The voltage controller can transform the unstable electric power to the battery on the basis of optimizing the parameters such as charging times, charging voltage. Through the communication connection and regulation of the upper computer system (UCS), it can make the coupling parameters configure to an optimal state, and it improves the overall conversion efficiency. This method can test the whole wind turbine (WT) performance systematically and evaluate the design parameters effectively. It not only provides a testing method for system structure design and parameter optimization of wind rotor, generator and voltage controller, but also provides a new testing method for the whole performance optimization of vertical axis wind energy conversion system (WECS).
Neural network fusion capabilities for efficient implementation of tracking algorithms

NASA Astrophysics Data System (ADS)

Sundareshan, Malur K.; Amoozegar, Farid

1996-05-01

The ability to efficiently fuse information of different forms for facilitating intelligent decision-making is one of the major capabilities of trained multilayer neural networks that is being recognized int eh recent times. While development of innovative adaptive control algorithms for nonlinear dynamical plants which attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. In this paper we describe the capabilities and functionality of neural network algorithms for data fusion and implementation of nonlinear tracking filters. For a discussion of details and for serving as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes form the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. Such an approach results in an overall nonlinear tracking filter which has several advantages over the popular efforts at designing nonlinear estimation algorithms for tracking applications, the principle one being the reduction of mathematical and computational complexities. A system architecture that efficiently integrates the processing capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described in this paper.
Performance analysis of hybrid vibrational energy harvesters with experimental verification

NASA Astrophysics Data System (ADS)

Sriramdas, Rammohan; Pratap, Rudra

2018-07-01

In the present work, performance indices for a hybrid energy harvester (HEH) that is composed of piezoelectric and electrodynamic or electromagnetic mechanisms of energy conversion are analyzed. Performance of a HEH is defined in terms of Q-normalized power factor and efficiency of conversion. They are observed to acutely depend on coupling strength or figures of merit in both piezoelectric and electrodynamic domains. The influence of figures of merit on the Q-normalized power factor, and the limits of conversion efficiency are explored. Based on the studies, a suitable range for figures of merit that would maximize both Q-normalized power factor and conversion efficiency in hybrid harvesters is proposed. The proposed idea is verified experimentally for the appropriate values of figures of merit and efficiencies by fabricating and testing four experimental models of the HEHs.
Betavoltaic Battery Conversion Efficiency Improvement Based on Interlayer Structures

NASA Astrophysics Data System (ADS)

Li, Da-Rang; Jiang, Lan; Yin, Jian-Hua; Tan, Yuan-Yuan; Lin, Nai

2012-07-01

Significant differences among the doping densities of PN junctions in semiconductors cause lattice mismatch and lattice defects that increase the recombination current of betavoltaic batteries. This extensively decreases the open circuit voltage and the short current, which results in low conversion efficiency. This study proposes P+PINN+-structure based betavoltaic batteries by adding an interlayer to typical PIN structures to improve conversion efficiency. Numerical simulations are conducted for the energy deposition of beta particles along the thickness direction in semiconductors. Based on this, 63Ni-radiation GaAs batteries with PIN and P+PINN+ structures are designed and fabricated to experimentally verify the proposed design. It turns out that the conversion efficiency of the betavoltaic battery with the proposed P+PINN+ structure is about 1.45 times higher than that with the traditional PIN structure.

Performance of conversion efficiency of a crystalline silicon solar cell with base doping density

NASA Astrophysics Data System (ADS)

Sahin, Gokhan; Kerimli, Genber; Barro, Fabe Idrissa; Sane, Moustapha; Alma, Mehmet Hakkı

In this study, we investigate theoretically the electrical parameters of a crystalline silicon solar cell in steady state. Based on a one-dimensional modeling of the cell, the short circuit current density, the open circuit voltage, the shunt and series resistances and the conversion efficiency are calculated, taking into account the base doping density. Either the I-V characteristic, series resistance, shunt resistance and conversion efficiency are determined and studied versus base doping density. The effects applied of base doping density on these parameters have been studied. The aim of this work is to show how short circuit current density, open circuit voltage and parasitic resistances are related to the base doping density and to exhibit the role played by those parasitic resistances on the conversion efficiency of the crystalline silicon solar.
High-efficiency frequency doubling of continuous-wave laser light.

PubMed

Ast, Stefan; Nia, Ramon Moghadas; Schönbeck, Axel; Lastzka, Nico; Steinlechner, Jessica; Eberle, Tobias; Mehmet, Moritz; Steinlechner, Sebastian; Schnabel, Roman

2011-09-01

We report on the observation of high-efficiency frequency doubling of 1550 nm continuous-wave laser light in a nonlinear cavity containing a periodically poled potassium titanyl phosphate crystal (PPKTP). The fundamental field had a power of 1.10 W and was converted into 1.05 W at 775 nm, yielding a total external conversion efficiency of 95±1%. The latter value is based on the measured depletion of the fundamental field being consistent with the absolute values derived from numerical simulations. According to our model, the conversion efficiency achieved was limited by the nonperfect mode matching into the nonlinear cavity and by the nonperfect impedance matching for the maximum input power available. Our result shows that cavity-assisted frequency conversion based on PPKTP is well suited for low-decoherence frequency conversion of quantum states of light.
Seeking to Improve Low Energy Neutral Atom Detection in Space

NASA Technical Reports Server (NTRS)

Shappirio, M.; Coplan, M.; Chornay, D.; Collier, M.; Herrero, F.; Ogilvie, K.; Williams, E.

2007-01-01

The detection of energetic neutral atoms allows for the remote examination of the interactions between plasmas and neutral populations in space. Before these neutral atoms can be measured, they must first be converted to ions. For the low energy end of this spectrum, interaction with a conversion surface is often the most efficient method to convert neutrals into ions. It is generally thought that the most efficient surfaces are low work functions materials. However, by their very nature, these surfaces are highly reactive and unstable, and therefore are not suitable for space missions where conditions cannot be controlled as they are in a laboratory. We therefore are looking to optimize a stable surface for conversion efficiency. Conversion efficiency can be increased either by changing the incident angle of the neutral particles to be grazing incidence and using stable surfaces with high conversion efficiencies. We have examined how to increase the angle of incidence from -80 degrees to -89 degrees, while maintaining or improving the total active conversion surface area without increasing the overall volume of the instrument. We are developing a method to micro-machine silicon, which will reduce the volume to surface area ratio by a factor of 60. We have also examined the material properties that affect the conversion efficiency of the surface for stable surfaces. Some of the parameters we have examined are work function, smoothness, and bond structure. We find that for stable surfaces, the most important property is the smoothness of the surface.
Enhancement of Energy Conversion Efficiency for Dye Sensitized Solar Cell Using Zinc Oxide Photoanode

NASA Astrophysics Data System (ADS)

Jamalullail, N.; Smohamad, I.; Nnorizan, M.; Mahmed, N.

2018-06-01

Dye sensitized solar cell (DSSC) is a third generation solar cell that is well known for its low cost, simple fabrication process and promised reasonable energy conversion efficiency. Basic structure of DSSC is composed of photoanode, dye sensitizer, electrolyte that is sandwiched together in between two transparent conductive oxide (TCO) glasses. Each of the components in the DSSC contributes important role that affect the energy conversion efficiency. In this research, the commonly used titanium dioxide (TiO2) photoanode has previously reported to have high recombination rate and low electron mobility which caused efficiency loss had been compared with the zinc oxide (ZnO) photoanode with high electron mobility (155 cm2V-1s-1). Both of these photoanodes had been deposited through doctor blade technique. The electrical performance of the laboratory based DSSCs were tested using solar cell simulator and demonstrated that ZnO is a better photoanode compared to TiO2 with the energy conversion efficiency of 0.34% and 0.29% respectively. Nanorods shape morphology was observed in ZnO photoanode with average particle size of 41.60 nm and average crystallite size of 19.13 nm. This research proved that the energy conversion efficiency of conventional TiO2 based photoanode can be improved using ZnO material.
Mid-infrared Raman amplification and wavelength conversion in dispersion engineered silicon-on-sapphire waveguides

NASA Astrophysics Data System (ADS)

Wang, Zhaolu; Liu, Hongjun; Huang, Nan; Sun, Qibing; Li, Xuefeng

2014-01-01

Raman amplification based on stimulated Stokes Raman scattering (SSRS) and wavelength conversion based on coherent anti-Stokes Raman scattering (CARS) are theoretically investigated in silicon-on-sapphire (SOS) waveguides in the mid-infrared (IR) region. When the linear phase mismatch Δk is close to zero, the Stokes gain and conversion efficiency drop down quickly due to the effect of parametric gain suppression when the Stokes-pump input ratio is sufficiently large. The Stokes gain increases with the increase of Δk, whereas efficient wavelength conversion needs appropriate Δk under different pump intensities. The conversion efficiency at exact linear phase matching (Δk = 0) is smaller than that at optimal linear phase mismatch by a factor of about 28 dB when the pump intensity is 2 GW cm-2.
Calorimetric Measurement for Internal Conversion Efficiency of Photovoltaic Cells/Modules Based on Electrical Substitution Method

NASA Astrophysics Data System (ADS)

Saito, Terubumi; Tatsuta, Muneaki; Abe, Yamato; Takesawa, Minato

2018-02-01

We have succeeded in the direct measurement for solar cell/module internal conversion efficiency based on a calorimetric method or electrical substitution method by which the absorbed radiant power is determined by replacing the heat absorbed in the cell/module with the electrical power. The technique is advantageous in that the reflectance and transmittance measurements, which are required in the conventional methods, are not necessary. Also, the internal quantum efficiency can be derived from conversion efficiencies by using the average photon energy. Agreements of the measured data with the values estimated from the nominal values support the validity of this technique.
Spatial walk-off compensated beta-barium borate stack for efficient deep-UV generation

NASA Astrophysics Data System (ADS)

Li, Da; Lee, Huai-Chuan; Meissner, Stephanie K.; Meissner, Helmuth E.

2018-02-01

Beta-Barium Borate (β-BBO) crystal is commonly used in nonlinear frequency conversion from visible to deep ultraviolet (DUV). However, in a single crystal BBO, its large spatial walk-off effect will reduce spatial overlap of ordinary and extraordinary beam, and thus degrade the conversion efficiency. To overcome the restrictions in current DUV conversion systems, Onyx applies adhesive-free bonding technique to replace the single crystal BBO with a spatial Walk-off Compensated (WOC) BBO stack, which is capable of correcting the spatial walk-off while retaining a constant nonlinear coefficient in the adjacent bonding layers. As a result, the β-BBO stack will provide good beam quality, high conversion efficiency, and broader acceptance angle and spectral linewidth, when compared with a single crystal of BBO. In this work, we report on performance of a spatial walk-off compensated β-BBO stack with adhesive-free bonding technique, for efficiently converting from the visible to DUV range. The physics behind the WOC BBO stack are demonstrated, followed by simulation of DUV conversion efficiency in an external resonance cavity. We also demonstrate experimentally the beam quality improvement in a 4-layer WOC BBO stack over a single BBO crystal.
Effect of end reflections on conversion efficiency of coaxial relativistic backward wave oscillator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teng, Yan; Chen, Changhua; Sun, Jun

2015-11-07

This paper theoretically investigates the effect of end reflections on the operation of the coaxial relativistic backward wave oscillator (CRBWO). It is found that the considerable enhancement of the end reflection at one end increases the conversion efficiency, but excessively large end reflections at both ends weaken the asynchronous wave-beam interaction and thus reduce the conversion efficiency. Perfect reflection at the post end significantly improves the interaction between the electron beam and the asynchronous harmonic so that the conversion efficiency is notably increased. Based on the theoretical research, the diffraction-CRBWO with the generated microwave diffracted and output through the frontmore » end of the coaxial slow wave structure cavity is proposed. The post end is conductively closed to provide the perfect reflection. This promotes the amplitude and uniformity of the longitudinal electric field on the beam transmission line and improves the asynchronous wave-beam interaction. In numerical simulations under the diode voltage and current of 450 kV and 5.84 kA, microwave generation with the power of 1.45 GW and the conversion efficiency of 55% are obtained at the frequency of 7.45 GHz.« less
DNA-mediated excitonic upconversion FRET switching

DOE PAGES

Kellis, Donald L.; Rehn, Sarah M.; Cannon, Brittany L.; ...

2015-11-17

Excitonics is a rapidly expanding field of nanophotonics in which the harvesting of photons, ensuing creation and transport of excitons via Förster resonant energy transfer (FRET), and subsequent charge separation or photon emission has led to the demonstration of excitonic wires, switches, Boolean logic and light harvesting antennas for many applications. FRET funnels excitons down an energy gradient resulting in energy loss with each step along the pathway. Conversely, excitonic energy up conversion via up conversion nanoparticles (UCNPs), although currently inefficient, serves as an energy ratchet to boost the exciton energy. Although FRET-based up conversion has been demonstrated, it suffersmore » from low FRET efficiency and lacks the ability to modulate the FRET. We have engineered an up conversion FRET-based switch by combining lanthanide-doped UCNPs and fluorophores that demonstrates excitonic energy up conversion by nearly a factor of 2, an excited state donor to acceptor FRET efficiency of nearly 25%, and an acceptor fluorophore quantum efficiency that is close to unity. These findings offer a promising path for energy up conversion in nanophotonic applications including artificial light harvesting, excitonic circuits, photovoltaics, nanomedicine, and optoelectronics.« less
Synthetic Glycopolymers for Highly Efficient Differentiation of Embryonic Stem Cells into Neurons: Lipo- or Not?

PubMed

Liu, Qi; Lyu, Zhonglin; Yu, You; Zhao, Zhen-Ao; Hu, Shijun; Yuan, Lin; Chen, Gaojian; Chen, Hong

2017-04-05

To realize the potential application of embryonic stem cells (ESCs) for the treatment of neurodegenerative diseases, it is a prerequisite to develop an effective strategy for the neural differentiation of ESCs so as to obtain adequate amount of neurons. Considering the efficacy of glycosaminoglycans (GAG) and their disadvantages (e.g., structure heterogeneity and impurity), GAG-mimicking glycopolymers (designed polymers containing functional units similar to natural GAG) with or without phospholipid groups were synthesized in the present work and their ability to promote neural differentiation of mouse ESCs (mESCs) was investigated. It was found that the lipid-anchored GAG-mimicking glycopolymers (lipo-pSGF) retained on the membrane of mESCs rather than being internalized by cells after 1 h of incubation. Besides, lipo-pSGF showed better activity in promoting neural differentiation. The expression of the neural-specific maker β3-tubulin in lipo-pSGF-treated cells was ∼3.8- and ∼1.9-fold higher compared to natural heparin- and pSGF-treated cells at day 14. The likely mechanism involved in lipo-pSGF-mediated neural differentiation was further investigated by analyzing its effect on fibroblast growth factor 2 (FGF2)-mediated extracellular signal-regulated kinases 1 and 2 (ERK1/2) signaling pathway which is important for neural differentiation of ESCs. Lipo-pSGF was found to efficiently bind FGF2 and enhance the phosphorylation of ERK1/2, thus promoting neural differentiation. These findings demonstrated that engineering of cell surface glycan using our synthetic lipo-glycopolymer is a highly efficient approach for neural differentiation of ESCs and this strategy can be applied for the regulation of other cellular activities mediated by cell membrane receptors.
Neural-Network Quantum States, String-Bond States, and Chiral Topological States

NASA Astrophysics Data System (ADS)

Glasser, Ivan; Pancotti, Nicola; August, Moritz; Rodriguez, Ivan D.; Cirac, J. Ignacio

2018-01-01

Neural-network quantum states have recently been introduced as an Ansatz for describing the wave function of quantum many-body systems. We show that there are strong connections between neural-network quantum states in the form of restricted Boltzmann machines and some classes of tensor-network states in arbitrary dimensions. In particular, we demonstrate that short-range restricted Boltzmann machines are entangled plaquette states, while fully connected restricted Boltzmann machines are string-bond states with a nonlocal geometry and low bond dimension. These results shed light on the underlying architecture of restricted Boltzmann machines and their efficiency at representing many-body quantum states. String-bond states also provide a generic way of enhancing the power of neural-network quantum states and a natural generalization to systems with larger local Hilbert space. We compare the advantages and drawbacks of these different classes of states and present a method to combine them together. This allows us to benefit from both the entanglement structure of tensor networks and the efficiency of neural-network quantum states into a single Ansatz capable of targeting the wave function of strongly correlated systems. While it remains a challenge to describe states with chiral topological order using traditional tensor networks, we show that, because of their nonlocal geometry, neural-network quantum states and their string-bond-state extension can describe a lattice fractional quantum Hall state exactly. In addition, we provide numerical evidence that neural-network quantum states can approximate a chiral spin liquid with better accuracy than entangled plaquette states and local string-bond states. Our results demonstrate the efficiency of neural networks to describe complex quantum wave functions and pave the way towards the use of string-bond states as a tool in more traditional machine-learning applications.
Impacts of kafirin allelic diversity, starch content, and protein digestibility on ethanol conversion efficiency in grain sorghum

USDA-ARS?s Scientific Manuscript database

Seed protein and starch composition determines the efficiency of ethanol conversion in the production of grain-based biofuels. Sorghum, highly water- and nutrient-efficient, has the potential to replace fuel crops with greater irrigation and fertiliser requirements, such as maize. However, sorghum g...
DOE Office of Scientific and Technical Information (OSTI.GOV)

Todt, Michael A.; Isenberg, Allan E.; Nanayakkara, Sanjini U.

Semiconducting transition-metal dichalcogenide (TMD) nanoflake thin films are promising large-area electrodes for photo-electrochemical solar energy conversion applications. However, their energy conversion efficiencies are typically much lower than those of bulk electrodes. It is unclear to what extent this efficiency gap stems from differences among nanoflakes (e.g., area, thickness, and surface structural features). It is also unclear whether individual exfoliated nanoflakes can achieve energy conversion efficiencies similar to those of bulk crystals. Here, we use a single-nanoflake photo-electrochemical approach to show that there are both highly active and completely inactive nanoflakes within a film. For the exfoliated MoSe 2 samples studiedmore » herein, 7% of nanoflakes are highly active champions, whose photocurrent efficiency exceeds that of the bulk crystal. However, 66% of nanoflakes are inactive spectators, which are mostly responsible for the overall lower photocurrent efficiency compared to the bulk crystal. The photocurrent collection efficiency increases with nanoflake area and decreases more at perimeter edges than at interior step edges. These observations, which are hidden in ensemble-level measurements, reveal the underlying performance issues of exfoliated TMD electrodes for photo-electrochemical energy conversion applications.« less
Mode conversion efficiency to Laguerre-Gaussian OAM modes using spiral phase optics.

PubMed

Longman, Andrew; Fedosejevs, Robert

2017-07-24

An analytical model for the conversion efficiency from a TEM 00 mode to an arbitrary Laguerre-Gaussian (LG) mode with null radial index spiral phase optics is presented. We extend this model to include the effects of stepped spiral phase optics, spiral phase optics of non-integer topological charge, and the reduction in conversion efficiency due to broad laser bandwidth. We find that through optimization, an optimal beam waist ratio of the input and output modes exists and is dependent upon the output azimuthal mode number.
Efficient Training of Supervised Spiking Neural Network via Accurate Synaptic-Efficiency Adjustment Method.

PubMed

Xie, Xiurui; Qu, Hong; Yi, Zhang; Kurths, Jurgen

2017-06-01

The spiking neural network (SNN) is the third generation of neural networks and performs remarkably well in cognitive tasks, such as pattern recognition. The temporal neural encode mechanism found in biological hippocampus enables SNN to possess more powerful computation capability than networks with other encoding schemes. However, this temporal encoding approach requires neurons to process information serially on time, which reduces learning efficiency significantly. To keep the powerful computation capability of the temporal encoding mechanism and to overcome its low efficiency in the training of SNNs, a new training algorithm, the accurate synaptic-efficiency adjustment method is proposed in this paper. Inspired by the selective attention mechanism of the primate visual system, our algorithm selects only the target spike time as attention areas, and ignores voltage states of the untarget ones, resulting in a significant reduction of training time. Besides, our algorithm employs a cost function based on the voltage difference between the potential of the output neuron and the firing threshold of the SNN, instead of the traditional precise firing time distance. A normalized spike-timing-dependent-plasticity learning window is applied to assigning this error to different synapses for instructing their training. Comprehensive simulations are conducted to investigate the learning properties of our algorithm, with input neurons emitting both single spike and multiple spikes. Simulation results indicate that our algorithm possesses higher learning performance than the existing other methods and achieves the state-of-the-art efficiency in the training of SNN.
Efficient differentiation of mouse embryonic stem cells into motor neurons.

PubMed

Wu, Chia-Yen; Whye, Dosh; Mason, Robert W; Wang, Wenlan

2012-06-09

Direct differentiation of embryonic stem (ES) cells into functional motor neurons represents a promising resource to study disease mechanisms, to screen new drug compounds, and to develop new therapies for motor neuron diseases such as spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS). Many current protocols use a combination of retinoic acid (RA) and sonic hedgehog (Shh) to differentiate mouse embryonic stem (mES) cells into motor neurons. However, the differentiation efficiency of mES cells into motor neurons has only met with moderate success. We have developed a two-step differentiation protocol that significantly improves the differentiation efficiency compared with currently established protocols. The first step is to enhance the neuralization process by adding Noggin and fibroblast growth factors (FGFs). Noggin is a bone morphogenetic protein (BMP) antagonist and is implicated in neural induction according to the default model of neurogenesis and results in the formation of anterior neural patterning. FGF signaling acts synergistically with Noggin in inducing neural tissue formation by promoting a posterior neural identity. In this step, mES cells were primed with Noggin, bFGF, and FGF-8 for two days to promote differentiation towards neural lineages. The second step is to induce motor neuron specification. Noggin/FGFs exposed mES cells were incubated with RA and a Shh agonist, Smoothened agonist (SAG), for another 5 days to facilitate motor neuron generation. To monitor the differentiation of mESs into motor neurons, we used an ES cell line derived from a transgenic mouse expressing eGFP under the control of the motor neuron specific promoter Hb9. Using this robust protocol, we achieved 51 ± 0.8% of differentiation efficiency (n = 3; p < 0.01, Student's t-test). Results from immunofluorescent staining showed that GFP+ cells express the motor neuron specific markers, Islet-1 and choline acetyltransferase (ChAT). Our two-step differentiation protocol provides an efficient way to differentiate mES cells into spinal motor neurons.
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks.

PubMed

Li, Can; Belkin, Daniel; Li, Yunning; Yan, Peng; Hu, Miao; Ge, Ning; Jiang, Hao; Montgomery, Eric; Lin, Peng; Wang, Zhongrui; Song, Wenhao; Strachan, John Paul; Barnell, Mark; Wu, Qing; Williams, R Stanley; Yang, J Joshua; Xia, Qiangfei

2018-06-19

Memristors with tunable resistance states are emerging building blocks of artificial neural networks. However, in situ learning on a large-scale multiple-layer memristor network has yet to be demonstrated because of challenges in device property engineering and circuit integration. Here we monolithically integrate hafnium oxide-based memristors with a foundry-made transistor array into a multiple-layer neural network. We experimentally demonstrate in situ learning capability and achieve competitive classification accuracy on a standard machine learning dataset, which further confirms that the training algorithm allows the network to adapt to hardware imperfections. Our simulation using the experimental parameters suggests that a larger network would further increase the classification accuracy. The memristor neural network is a promising hardware platform for artificial intelligence with high speed-energy efficiency.
Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

PubMed

Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang

2017-09-21

The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.
The brain’s conversation with itself: neural substrates of dialogic inner speech

PubMed Central

Weis, Susanne; McCarthy-Jones, Simon; Moseley, Peter; Smailes, David; Fernyhough, Charles

2016-01-01

Inner speech has been implicated in important aspects of normal and atypical cognition, including the development of auditory hallucinations. Studies to date have focused on covert speech elicited by simple word or sentence repetition, while ignoring richer and arguably more psychologically significant varieties of inner speech. This study compared neural activation for inner speech involving conversations (‘dialogic inner speech’) with single-speaker scenarios (‘monologic inner speech’). Inner speech-related activation differences were then compared with activations relating to Theory-of-Mind (ToM) reasoning and visual perspective-taking in a conjunction design. Generation of dialogic (compared with monologic) scenarios was associated with a widespread bilateral network including left and right superior temporal gyri, precuneus, posterior cingulate and left inferior and medial frontal gyri. Activation associated with dialogic scenarios and ToM reasoning overlapped in areas of right posterior temporal cortex previously linked to mental state representation. Implications for understanding verbal cognition in typical and atypical populations are discussed. PMID:26197805
Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images.

PubMed

Lu, Donghuan; Popuri, Karteek; Ding, Gavin Weiguang; Balachandar, Rakesh; Beg, Mirza Faisal

2018-04-09

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1-3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature.

Indium oxide/n-silicon heterojunction solar cells

DOEpatents

Feng, Tom; Ghosh, Amal K.

1982-12-28

A high photo-conversion efficiency indium oxide/n-silicon heterojunction solar cell is spray deposited from a solution containing indium trichloride. The solar cell exhibits an Air Mass One solar conversion efficiency in excess of about 10%.
Comparison of Predicted Thermoelectric Energy Conversion Efficiency by Cumulative Properties and Reduced Variables Approaches

NASA Astrophysics Data System (ADS)

Linker, Thomas M.; Lee, Glenn S.; Beekman, Matt

2018-06-01

The semi-analytical methods of thermoelectric energy conversion efficiency calculation based on the cumulative properties approach and reduced variables approach are compared for 21 high performance thermoelectric materials. Both approaches account for the temperature dependence of the material properties as well as the Thomson effect, thus the predicted conversion efficiencies are generally lower than that based on the conventional thermoelectric figure of merit ZT for nearly all of the materials evaluated. The two methods also predict material energy conversion efficiencies that are in very good agreement which each other, even for large temperature differences (average percent difference of 4% with maximum observed deviation of 11%). The tradeoff between obtaining a reliable assessment of a material's potential for thermoelectric applications and the complexity of implementation of the three models, as well as the advantages of using more accurate modeling approaches in evaluating new thermoelectric materials, are highlighted.
Fully Controllable Pancharatnam-Berry Metasurface Array with High Conversion Efficiency and Broad Bandwidth

PubMed Central

Liu, Chuanbao; Bai, Yang; Zhao, Qian; Yang, Yihao; Chen, Hongsheng; Zhou, Ji; Qiao, Lijie

2016-01-01

Metasurfaces have powerful abilities to manipulate the properties of electromagnetic waves flexibly, especially the modulation of polarization state for both linearly polarized (LP) and circularly polarized (CP) waves. However, the transmission efficiency of cross-polarization conversion by a single-layer metasurface has a low theoretical upper limit of 25% and the bandwidth is usually narrow, which cannot be resolved by their simple additions. Here, we efficiently manipulate polarization coupling in multilayer metasurface to promote the transmission of cross-polarization by Fabry-Perot resonance, so that a high conversion coefficient of 80–90% of CP wave is achieved within a broad bandwidth in the metasurface with C-shaped scatters by theoretical calculation, numerical simulation and experiments. Further, fully controlling Pancharatnam-Berry phase enables to realize polarized beam splitter, which is demonstrated to produce abnormal transmission with high conversion efficiency and broad bandwidth. PMID:27703254
Full 3D modelling of pulse propagation enables efficient nonlinear frequency conversion with low energy laser pulses in a single-element tripler.

PubMed

Kardaś, Tomasz M; Nejbauer, Michał; Wnuk, Paweł; Resan, Bojan; Radzewicz, Czesław; Wasylczyk, Piotr

2017-02-22

Although new optical materials continue to open up access to more and more wavelength bands where femtosecond laser pulses can be generated, light frequency conversion techniques are still indispensable in filling the gaps on the ultrafast spectral scale. With high repetition rate, low pulse energy laser sources (oscillators) tight focusing is necessary for a robust wave mixing and the efficiency of broadband nonlinear conversion is limited by diffraction as well as spatial and temporal walk-off. Here we demonstrate a miniature third harmonic generator (tripler) with conversion efficiency exceeding 30%, producing 246 fs UV pulses via cascaded second order processes within a single laser beam focus. Designing this highly efficient and ultra compact frequency converter was made possible by full 3-dimentional modelling of propagation of tightly focused, broadband light fields in nonlinear and birefringent media.
Full 3D modelling of pulse propagation enables efficient nonlinear frequency conversion with low energy laser pulses in a single-element tripler

NASA Astrophysics Data System (ADS)

Kardaś, Tomasz M.; Nejbauer, Michał; Wnuk, Paweł; Resan, Bojan; Radzewicz, Czesław; Wasylczyk, Piotr

2017-02-01

Although new optical materials continue to open up access to more and more wavelength bands where femtosecond laser pulses can be generated, light frequency conversion techniques are still indispensable in filling the gaps on the ultrafast spectral scale. With high repetition rate, low pulse energy laser sources (oscillators) tight focusing is necessary for a robust wave mixing and the efficiency of broadband nonlinear conversion is limited by diffraction as well as spatial and temporal walk-off. Here we demonstrate a miniature third harmonic generator (tripler) with conversion efficiency exceeding 30%, producing 246 fs UV pulses via cascaded second order processes within a single laser beam focus. Designing this highly efficient and ultra compact frequency converter was made possible by full 3-dimentional modelling of propagation of tightly focused, broadband light fields in nonlinear and birefringent media.
Using an artificial neural network to predict the optimal conditions for enzymatic hydrolysis of apple pomace.

PubMed

Gama, Repson; Van Dyk, J Susan; Burton, Mike H; Pletschke, Brett I

2017-06-01

The enzymatic degradation of lignocellulosic biomass such as apple pomace is a complex process influenced by a number of hydrolysis conditions. Predicting optimal conditions, including enzyme and substrate concentration, temperature and pH can improve conversion efficiency. In this study, the production of sugar monomers from apple pomace using commercial enzyme preparations, Celluclast 1.5L, Viscozyme L and Novozyme 188 was investigated. A limited number of experiments were carried out and then analysed using an artificial neural network (ANN) to model the enzymatic hydrolysis process. The ANN was used to simulate the enzymatic hydrolysis process for a range of input variables and the optimal conditions were successfully selected as was indicated by the R 2 value of 0.99 and a small MSE value. The inputs for the ANN were substrate loading, enzyme loading, temperature, initial pH and a combination of these parameters, while release profiles of glucose and reducing sugars were the outputs. Enzyme loadings of 0.5 and 0.2 mg/g substrate and a substrate loading of 30% were optimal for glucose and reducing sugar release from apple pomace, respectively, resulting in concentrations of 6.5 g/L glucose and 28.9 g/L reducing sugars. Apple pomace hydrolysis can be successfully carried out based on the predicted optimal conditions from the ANN.
Plasma Accelerator and Energy Conversion Research

DTIC Science & Technology

1982-10-29

performance tests have been accomplished. A self-contained recirculating AMTEC device with a thermal to electric conversion efficiency of 19% has been...combined efficiency . These two match up particularly well, because thermionic conversion is a high temperature technique, whereas AMTEC is limited to...EXPERIENTAL: Samples: The samples were prepared with a high rate DC magnetron sputtering apparatus ( SFI model 1 ). The sample set consisted of four
Comparative efficiency of technologies for conversion and transportation of energy resources of Russia's eastern regions to NEA countries

NASA Astrophysics Data System (ADS)

Kler, Aleksandr; Tyurina, Elina; Mednikov, Aleksandr

2018-01-01

The paper presents perspective technologies for combined conversion of fossil fuels into synthetic liquid fuels and electricity. The comparative efficiency of various process flows of conversion and transportation of energy resources of Russia's east that are aimed at supplying electricity to remote consumers is presented. These also include process flows based on production of synthetic liquid fuel.
Everyday conversation requires cognitive inference: neural bases of comprehending implicated meanings in conversations.

PubMed

Jang, Gijeong; Yoon, Shin-ae; Lee, Sung-Eun; Park, Haeil; Kim, Joohan; Ko, Jeong Hoon; Park, Hae-Jeong

2013-11-01

In ordinary conversations, literal meanings of an utterance are often quite different from implicated meanings and the inference about implicated meanings is essentially required for successful comprehension of the speaker's utterances. Inference of finding implicated meanings is based on the listener's assumption that the conversational partner says only relevant matters according to the maxim of relevance in Grice's theory of conversational implicature. To investigate the neural correlates of comprehending implicated meanings under the maxim of relevance, a total of 23 participants underwent an fMRI task with a series of conversational pairs, each consisting of a question and an answer. The experimental paradigm was composed of three conditions: explicit answers, moderately implicit answers, and highly implicit answers. Participants were asked to decide whether the answer to the Yes/No question meant 'Yes' or 'No'. Longer reaction time was required for the highly implicit answers than for the moderately implicit answers without affecting the accuracy. The fMRI results show that the left anterior temporal lobe, left angular gyrus, and left posterior middle temporal gyrus had stronger activation in both moderately and highly implicit conditions than in the explicit condition. Comprehension of highly implicit answers had increased activations in additional regions including the left inferior frontal gyrus, left medial prefrontal cortex, left posterior cingulate cortex and right anterior temporal lobe. The activation results indicate involvement of these regions in the inference process to build coherence between literally irrelevant but pragmatically associated utterances under the maxim of relevance. Especially, the left anterior temporal lobe showed high sensitivity to the level of implicitness and showed increased activation for highly versus moderately implicit conditions, which imply its central role in inference such as semantic integration. The right hemisphere activation, uniquely found in the anterior temporal lobe for highly implicit utterances, suggests its competence for integrating distant concepts in implied utterances under the relevance principle. Copyright © 2013 Elsevier Inc. All rights reserved.
Investigation of Saturation Effects in Ceramic Phosphors for Laser Lighting

PubMed Central

Krasnoshchoka, Anastasiia; Dam-Hansen, Carsten; Corell, Dennis Dan; Petersen, Paul Michael

2017-01-01

We report observations of saturation effects in a Ce:LuAG and Eu-doped nitride ceramic phosphor for conversion of blue laser light for white light generation. The luminous flux from the phosphors material increases linearly with the input power until saturation effects limit the conversion. It is shown that the temperature of the phosphor layer influences the saturation power level and the conversion efficiency. It is also shown that the correlated color temperature (CCT), phosphor conversion efficiency and color rendering index (CRI) are dependent both on the incident power and spot size diameter of the illumination. A phosphor conversion efficiency up to 140.8 lm/W with CRI of 89.4 was achieved. The saturation in a ceramic phosphor, when illuminated by high intensity laser diodes, is estimated to play the main role in limiting the available luminance from laser-based lighting systems. PMID:29292770
Efficiency enhancement of organic solar cells using transparent plasmonic Ag nanowire electrodes.

PubMed

Kang, Myung-Gyu; Xu, Ting; Park, Hui Joon; Luo, Xiangang; Guo, L Jay

2010-10-15

Surface plasmon enhanced photo-current and power conversion efficiency of organic solar cells using periodic Ag nanowires as transparent electrodes are reported, as compared to the device with conventional ITO electrodes. External quantum efficiencies are enhanced about 2.5 fold around the peak solar spectrum wavelength of 560 nm, resulting in 35% overall increase in power conversion efficiency than the ITO control device under normal unpolarized light.
Prototype-Incorporated Emotional Neural Network.

PubMed

Oyedotun, Oyebade K; Khashman, Adnan

2017-08-15

Artificial neural networks (ANNs) aim to simulate the biological neural activities. Interestingly, many ''engineering'' prospects in ANN have relied on motivations from cognition and psychology studies. So far, two important learning theories that have been subject of active research are the prototype and adaptive learning theories. The learning rules employed for ANNs can be related to adaptive learning theory, where several examples of the different classes in a task are supplied to the network for adjusting internal parameters. Conversely, the prototype-learning theory uses prototypes (representative examples); usually, one prototype per class of the different classes contained in the task. These prototypes are supplied for systematic matching with new examples so that class association can be achieved. In this paper, we propose and implement a novel neural network algorithm based on modifying the emotional neural network (EmNN) model to unify the prototype- and adaptive-learning theories. We refer to our new model as ``prototype-incorporated EmNN''. Furthermore, we apply the proposed model to two real-life challenging tasks, namely, static hand-gesture recognition and face recognition, and compare the result to those obtained using the popular back-propagation neural network (BPNN), emotional BPNN (EmNN), deep networks, an exemplar classification model, and k-nearest neighbor.
Functional Neuroanatomy and Neurophysiology of Functional Neurological Disorders (Conversion Disorder).

PubMed

Voon, Valerie; Cavanna, Andrea E; Coburn, Kerry; Sampson, Shirlene; Reeve, Alya; LaFrance, W Curt

2016-01-01

Much is known regarding the physical characteristics, comorbid symptoms, psychological makeup, and neuropsychological performance of patients with functional neurological disorders (FNDs)/conversion disorders. Gross neurostructural deficits do not account for the patients' deficits or symptoms. This review describes the literature focusing on potential neurobiological (i.e. functional neuroanatomic/neurophysiological) findings among individuals with FND, examining neuroimaging and neurophysiological studies of patients with the various forms of motor and sensory FND. In summary, neural networks and neurophysiologic mechanisms may mediate "functional" symptoms, reflecting neurobiological and intrapsychic processes.
All‐optical functional synaptic connectivity mapping in acute brain slices using the calcium integrator CaMPARI

PubMed Central

Sha, Fern; Johenning, Friedrich W.; Schreiter, Eric R.; Looger, Loren L.; Larkum, Matthew E.

2016-01-01

Key points The genetically encoded fluorescent calcium integrator calcium‐modulated photoactivatable ratiobetric integrator (CaMPARI) reports calcium influx induced by synaptic and neural activity. Its fluorescence is converted from green to red in the presence of violet light and calcium.The rate of conversion – the sensitivity to activity – is tunable and depends on the intensity of violet light.Synaptic activity and action potentials can independently initiate significant CaMPARI conversion.The level of conversion by subthreshold synaptic inputs is correlated to the strength of input, enabling optical readout of relative synaptic strength.When combined with optogenetic activation of defined presynaptic neurons, CaMPARI provides an all‐optical method to map synaptic connectivity. Abstract The calcium‐modulated photoactivatable ratiometric integrator (CaMPARI) is a genetically encoded calcium integrator that facilitates the study of neural circuits by permanently marking cells active during user‐specified temporal windows. Permanent marking enables measurement of signals from large swathes of tissue and easy correlation of activity with other structural or functional labels. One potential application of CaMPARI is labelling neurons postsynaptic to specific populations targeted for optogenetic stimulation, giving rise to all‐optical functional connectivity mapping. Here, we characterized the response of CaMPARI to several common types of neuronal calcium signals in mouse acute cortical brain slices. Our experiments show that CaMPARI is effectively converted by both action potentials and subthreshold synaptic inputs, and that conversion level is correlated to synaptic strength. Importantly, we found that conversion rate can be tuned: it is linearly related to light intensity. At low photoconversion light levels CaMPARI offers a wide dynamic range due to slower conversion rate; at high light levels conversion is more rapid and more sensitive to activity. Finally, we employed CaMPARI and optogenetics for functional circuit mapping in ex vivo acute brain slices, which preserve in vivo‐like connectivity of axon terminals. With a single light source, we stimulated channelrhodopsin‐2‐expressing long‐range posteromedial (POm) thalamic axon terminals in cortex and induced CaMPARI conversion in recipient cortical neurons. We found that POm stimulation triggers robust photoconversion of layer 5 cortical neurons and weaker conversion of layer 2/3 neurons. Thus, CaMPARI enables network‐wide, tunable, all‐optical functional circuit mapping that captures supra‐ and subthreshold depolarization. PMID:27861906
Method for forming indium oxide/n-silicon heterojunction solar cells

DOEpatents

Feng, Tom; Ghosh, Amal K.

1984-03-13

A high photo-conversion efficiency indium oxide/n-silicon heterojunction solar cell is spray deposited from a solution containing indium trichloride. The solar cell exhibits an Air Mass One solar conversion efficiency in excess of about 10%.
Red laser based on intra-cavity Nd:YAG/CH4 frequency doubled Raman lasers

NASA Astrophysics Data System (ADS)

Wang, Yanchao; Wang, Pengyuan; Liu, Jinbo; Liu, Wanfa; Guo, Jingwei

2017-01-01

Stimulated Raman scattering (SRS) is a powerful tool for the extension of the spectral range of lasers. To obtain efficient Raman conversion in SRS, many researchers have studied different types of Raman laser configurations. Among these configurations, the intra-cavity type is particularly attractive. Intra-cavity SRS has the advantages of high intra-cavity laser intensity, low-SRS threshold, and high Raman conversion efficiency. In this paper, An Q-switched intra-cavity Nd: YAG/CH4 frequency-doubled Raman lasers is reported. A negative branch confocal resonator with M= 1.25 is used for the frequency-doubling of Nd: YAG laser. The consequent 532nm light is confined in intra- cavity SRS with travelling wave resonator, and the focal of one mirror of cavity is overlap with the center of the other mirror of the cavity. We found this design is especially efficient to reduce the threshold of SRS, and increase conversion efficiency. The threshold is measured to be 0.62 MW, and at the pump energy of 16.1 mJ, the conversion efficiency is 34%. With the smaller magnification M, the threshold could further decrease, and the conversion efficiency could be improved further. This is a successful try to extend the spectral range of a laser to the shorter wavelength by SRS, and this design may play an important role in the fulfillment of high power red lasers.
Theoretical limits of the multistacked 1D and 2D microstructured inorganic solar cells

NASA Astrophysics Data System (ADS)

Yengel, Emre; Karaagac, Hakan; VJ, Logeeswaran; Islam, M. Saif

2015-09-01

Recent studies in monocrystalline semiconductor solar cells are focused on mechanically stacking multiple cells from different materials to increase the power conversion efficiency. Although, the results show promising increase in the device performance, the cost remains as the main drawback. In this study, we calculated the theoretical limits of multistacked 1D and 2D microstructered inorganic monocrstalline solar cells. This system is studied for Si and Ge material pair. The results show promising improvements in the surface reflection due to enhanced light trapping caused by photon-microstructures interactions. The theoretical results are also supported with surface reflection and angular dependent power conversion efficiency measurements of 2D axial microwall solar cells. We address the challenge of cost reduction by proposing to use our recently reported mass-manufacturable fracture-transfer- printing method which enables the use of a monocrystalline substrate wafer for repeated fabrication of devices by consuming only few microns of materials in each layer of devices. We calculated thickness dependent power conversion efficiencies of multistacked Si/Ge microstructured solar cells and found the power conversion efficiency to saturate at 26% with a combined device thickness of 30 μm. Besides having benefits of fabricating low-cost, light weight, flexible, semi-transparent, and highly efficient devices, the proposed fabrication method is applicable for other III-V materials and compounds to further increase the power conversion efficiency above 35% range.
GH Mediates Exercise-Dependent Activation of SVZ Neural Precursor Cells in Aged Mice

PubMed Central

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

2012-01-01

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

NASA Astrophysics Data System (ADS)

Goldt, Sebastian; Seifert, Udo

2017-11-01

Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.
Large Deviations for Nonlocal Stochastic Neural Fields

PubMed Central

2014-01-01

We study the effect of additive noise on integro-differential neural field equations. In particular, we analyze an Amari-type model driven by a Q-Wiener process, and focus on noise-induced transitions and escape. We argue that proving a sharp Kramers’ law for neural fields poses substantial difficulties, but that one may transfer techniques from stochastic partial differential equations to establish a large deviation principle (LDP). Then we demonstrate that an efficient finite-dimensional approximation of the stochastic neural field equation can be achieved using a Galerkin method and that the resulting finite-dimensional rate function for the LDP can have a multiscale structure in certain cases. These results form the starting point for an efficient practical computation of the LDP. Our approach also provides the technical basis for further rigorous study of noise-induced transitions in neural fields based on Galerkin approximations. Mathematics Subject Classification (2000): 60F10, 60H15, 65M60, 92C20. PMID:24742297

A program for the calculation of paraboloidal-dish solar thermal power plant performance

NASA Technical Reports Server (NTRS)

Bowyer, J. M., Jr.

1985-01-01

A program capable of calculating the design-point and quasi-steady-state annual performance of a paraboloidal-concentrator solar thermal power plant without energy storage was written for a programmable calculator equipped with suitable printer. The power plant may be located at any site for which a histogram of annual direct normal insolation is available. Inputs required by the program are aperture area and the design and annual efficiencies of the concentrator; the intercept factor and apparent efficiency of the power conversion subsystem and a polynomial representation of its normalized part-load efficiency; the efficiency of the electrical generator or alternator; the efficiency of the electric power conditioning and transport subsystem; and the fractional parasitic loses for the plant. Losses to auxiliaries associated with each individual module are to be deducted when the power conversion subsystem efficiencies are calculated. Outputs provided by the program are the system design efficiency, the annualized receiver efficiency, the annualized power conversion subsystem efficiency, total annual direct normal insolation received per unit area of concentrator aperture, and the system annual efficiency.
Infrared Signal Detection by Upconversion Technique

NASA Technical Reports Server (NTRS)

Wong, Teh-Hwa; Yu, Jirong; Bai, Yingxin; Johnson, William E.

2014-01-01

We demonstrated up-conversion assisted detection of a 2.05-micron signal by using a bulk periodically poled Lithium niobate crystal. The 94% intrinsic up-conversion efficiency and 22.58% overall detection efficiency at pW level of 2.05-micron was achieved.
TECHNICAL NOTE: The development of a PZT-based microdrive for neural signal recording

NASA Astrophysics Data System (ADS)

Park, Sangkyu; Yoon, Euisung; Lee, Sukchan; Shin, Hee-sup; Park, Hyunjun; Kim, Byungkyu; Kim, Daesoo; Park, Jongoh; Park, Sukho

2008-04-01

A hand-controlled microdrive has been used to obtain neural signals from rodents such as rats and mice. However, it places severe physical stress on the rodents during its manipulation, and this stress leads to alertness in the mice and low efficiency in obtaining neural signals from the mice. To overcome this issue, we developed a novel microdrive, which allows one to adjust the electrodes by a piezoelectric device (PZT) with high precision. Its mass is light enough to install on the mouse's head. The proposed microdrive has three H-type PZT actuators and their guiding structure. The operation principle of the microdrive is based on the well known inchworm mechanism. When the three PZT actuators are synchronized, linear motion of the electrode is produced along the guiding structure. The electrodes used for the recording of the neural signals from neuron cells were fixed at one of the PZT actuators. Our proposed microdrive has an accuracy of about 400 nm and a long stroke of about 5 mm. In response to formalin-induced pain, single unit activities are robustly measured at the thalamus with electrodes whose vertical depth is adjusted by the microdrive under urethane anesthesia. In addition, the microdrive was efficient in detecting neural signals from mice that were moving freely. Thus, the present study suggests that the PZT-based microdrive could be an alternative for the efficient detection of neural signals from mice during behavioral states without any stress to the mice.
In vitro generation of three-dimensional substrate-adherent embryonic stem cell-derived neural aggregates for application in animal models of neurological disorders.

PubMed

Hargus, Gunnar; Cui, Yi-Fang; Dihné, Marcel; Bernreuther, Christian; Schachner, Melitta

2012-05-01

In vitro-differentiated embryonic stem (ES) cells comprise a useful source for cell replacement therapy, but the efficiency and safety of a translational approach are highly dependent on optimized protocols for directed differentiation of ES cells into the desired cell types in vitro. Furthermore, the transplantation of three-dimensional ES cell-derived structures instead of a single-cell suspension may improve graft survival and function by providing a beneficial microenvironment for implanted cells. To this end, we have developed a new method to efficiently differentiate mouse ES cells into neural aggregates that consist predominantly (>90%) of postmitotic neurons, neural progenitor cells, and radial glia-like cells. When transplanted into the excitotoxically lesioned striatum of adult mice, these substrate-adherent embryonic stem cell-derived neural aggregates (SENAs) showed significant advantages over transplanted single-cell suspensions of ES cell-derived neural cells, including improved survival of GABAergic neurons, increased cell migration, and significantly decreased risk of teratoma formation. Furthermore, SENAs mediated functional improvement after transplantation into animal models of Parkinson's disease and spinal cord injury. This unit describes in detail how SENAs are efficiently derived from mouse ES cells in vitro and how SENAs are isolated for transplantation. Furthermore, methods are presented for successful implantation of SENAs into animal models of Huntington's disease, Parkinson's disease, and spinal cord injury to study the effects of stem cell-derived neural aggregates in a disease context in vivo.
Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.
Sustainable and efficient pathways for bioenergy recovery from low-value process streams via bioelectrochemical systems in biorefineries

DOE PAGES

Borole, Abhijeet P.

2015-08-25

Conversion of biomass into bioenergy is possible via multiple pathways resulting in production of biofuels, bioproducts and biopower. Efficient and sustainable conversion of biomass, however, requires consideration of many environmental and societal parameters in order to minimize negative impacts. Integration of multiple conversion technologies and inclusion of upcoming alternatives such as bioelectrochemical systems can minimize these impacts and improve conservation of resources such as hydrogen, water and nutrients via recycle and reuse. This report outlines alternate pathways integrating microbial electrolysis in biorefinery schemes to improve energy efficiency while evaluating environmental sustainability parameters.
Cascaded-cladding-pumped cascaded Raman fiber amplifier.

PubMed

Jiang, Huawei; Zhang, Lei; Feng, Yan

2015-06-01

The conversion efficiency of double-clad Raman fiber laser is limited by the cladding-to-core area ratio. To get high conversion efficiency, the inner-cladding-to-core area ratio has to be less than about 8, which limits the brightness enhancement. To overcome the problem, a cascaded-cladding-pumped cascaded Raman fiber laser with multiple-clad fiber as the Raman gain medium is proposed. A theoretical model of Raman fiber amplifier with multiple-clad fiber is developed, and numerical simulation proves that the proposed scheme can improve the conversion efficiency and brightness enhancement of cladding pumped Raman fiber laser.
Efficient 525 nm laser generation in single or double resonant cavity

NASA Astrophysics Data System (ADS)

Liu, Shilong; Han, Zhenhai; Liu, Shikai; Li, Yinhai; Zhou, Zhiyuan; Shi, Baosen

2018-03-01

This paper reports the results of a study into highly efficient sum frequency generation from 792 and 1556 nm wavelength light to 525 nm wavelength light using either a single or double resonant ring cavity based on a periodically poled potassium titanyl phosphate crystal (PPKTP). By optimizing the cavity's parameters, the maximum power achieved for the resultant 525 nm laser was 263 and 373 mW for the single and double resonant cavity, respectively. The corresponding quantum conversion efficiencies were 8 and 77% for converting 1556 nm photons to 525 nm photons with the single and double resonant cavity, respectively. The measured intra-cavity single pass conversion efficiency for both configurations was about 5%. The performances of the sum frequency generation in these two configurations was studied and compared in detail. This work will provide guidelines for optimizing the generation of sum frequency generated laser light for a variety of configurations. The high conversion efficiency achieved in this work will help pave the way for frequency up-conversion of non-classical quantum states, such as the squeezed vacuum and single photon states. The proposed green laser source will be used in our future experiments, which includes a plan to generate two-color entangled photon pairs and achieve the frequency down-conversion of single photons carrying orbital angular momentum.
Potential natural sensitizers extracted from the skin of Canarium odontophyllum fruits for dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Lim, Andery; Kumara, N. T. R. N.; Tan, Ai Ling; Mirza, Aminul Huq; Chandrakanthi, R. L. N.; Petra, Mohammad Iskandar; Ming, Lim Chee; Senadeera, G. K. R.; Ekanayake, Piyasiri

2015-03-01

Possibility of use of dye extract from skin samples of a seasonal, indigenous fruit from Borneo, namely Canarium odontophyllum, in dye sensitized solar cells (DSSCs) are explored. Three main groups of flavonoid pigments are detected and these pigments exhibit different UV-vis absorption properties, and hence showing different light harvesting capabilities. When applied in DSSCs. The detected pigment constituents of the extract consist of aurone (maritimein), anthocyanidin (pelargonidin) and anthocyanidin (cyanidin derivatives). When tested in DSSC, the highest conversion efficiency of 1.43% is exhibited by cyanidin derivatives, and this is followed by conversion efficiencies of 0.51% and 0.79% for aurone and pelargonidin, respectively. It is shown that individual pigments, like cyanidin derivatives and pelargonidin, exhibit higher power conversion efficiency when compared to that of C.odontophyllum skin pigment mixture (with a conversion efficiency of only 0.68%). The results indicate a possibility of masking effects of the pigments when used as a mixture. The acidification of C.odontophyllum skin pigments with concentrated hydrochloric acid improves the conversion efficiency of the mixture from 0.68% to 0.99%. The discussion in this paper will draw data and observations from the variation in absorption and adsorption properties, the HOMO-LUMO levels, the energy band gaps and the functional group compositions of the detected flavonoids.
Bioinspired model of mechanical energy harvesting based on flexoelectric membranes.

PubMed

Rey, Alejandro D; Servio, P; Herrera-Valencia, E E

2013-02-01

Membrane flexoelectricity is an electromechanical coupling process that describes membrane electrical polarization due to bending and membrane bending under electric fields. In this paper we propose, formulate, and characterize a mechanical energy harvesting system consisting of a deformable soft flexoelectric thin membrane subjected to harmonic forcing from contacting bulk fluids. The key elements of the energy harvester are formulated and characterized, including (i) the mechanical-to-electrical energy conversion efficiency, (ii) the electromechanical shape equation connecting fluid forces with membrane curvature and electric displacement, and (iii) the electric power generation and efficiency. The energy conversion efficiency is cast as the ratio of flexoelectric coupling to the product of electric and bending elasticity. The device is described by a second-order curvature dynamics coupled to the electric displacement equation and as such results in mechanical power absorption with a resonant peak whose amplitude decreases with bending viscosity. The electric power generation is proportional to the conversion factor and the power efficiency decreases with frequency. Under high bending viscosity, the power efficiency increases with the conversion factor and under low viscosities it decreases with the conversion factor. The theoretical results presented contribute to the ongoing experimental efforts to develop mechanical energy harvesting from fluid flow energy through solid-fluid interactions and electromechanical transduction.
Experimental investigation on the hydrodynamic performance of a wave energy converter

NASA Astrophysics Data System (ADS)

Zheng, Xiong-bo; Ma, Yong; Zhang, Liang; Jiang, Jin; Liu, Heng-xu

2017-06-01

Wave energy is an important type of marine renewable energy. A wave energy converter (WEC) moored with two floating bodies was developed in the present study. To analyze the dynamic performance of the WEC, an experimental device was designed and tested in a tank. The experiment focused on the factors which impact the motion and energy conversion performance of the WEC. Dynamic performance was evaluated by the relative displacements and velocities of the oscillator and carrier which served as the floating bodies of WEC. Four factors were tested, i.e. wave height, wave period, power take-off (PTO) damping, and mass ratio ( R M) of the oscillator and carrier. Experimental results show that these factors greatly affect the energy conversion performance, especially when the wave period matches R M and PTO damping. According to the results, we conclude that: (a) the maximization of the relative displacements and velocities leads to the maximization of the energy conversion efficiency; (b) the larger the wave height, the higher the energy conversion efficiency will be; (c) the relationships of energy conversion efficiency with wave period, PTO damping, and R M are nonlinear, but the maximum efficiency is obtained when these three factors are optimally matched. Experimental results demonstrated that the energy conversion efficiency reached the peak at 28.62% when the wave height was 120 mm, wave period was 1.0 s, R M was 0.21, and the PTO damping was corresponding to the resistance of 100 Ω.
Biomass and Nitrogen Budgets During Larval Development of Lymantria dispar and Choristoneura fumiferana: Allometric Relationships

Treesearch

Michael E. Montgomery

1983-01-01

Spruce budworm larvae grew faster than gypsy moth larvae both in a temporal and relative sense. The budworm larvae had a higher relative growth rate (RGR), biomass conversion efficiency (EGI), and nitrogen utilization efficiency (NOE) than the gypsy moth larvae. As both species matured, relative growth rates, rates of consumption, and conversion efficiencies declined....
Thin film solar cells grown by organic vapor phase deposition

NASA Astrophysics Data System (ADS)

Yang, Fan

Organic solar cells have the potential to provide low-cost photovoltaic devices as a clean and renewable energy resource. In this thesis, we focus on understanding the energy conversion process in organic solar cells, and improving the power conversion efficiencies via controlled growth of organic nanostructures. First, we explain the unique optical and electrical properties of organic materials used for photovoltaics, and the excitonic energy conversion process in donor-acceptor heterojunction solar cells that place several limiting factors of their power conversion efficiency. Then, strategies for improving exciton diffusion and carrier collection are analyzed using dynamical Monte Carlo models for several nanostructure morphologies. Organic vapor phase deposition is used for controlling materials crystallization and film morphology. We improve the exciton diffusion efficiency while maintaining good carrier conduction in a bulk heterojunction solar cell. Further efficiency improvement is obtained in a novel nanocrystalline network structure with a thick absorbing layer, leading to the demonstration of an organic solar cell with 4.6% efficiency. In addition, solar cells using simultaneously active heterojunctions with broad spectral response are presented. We also analyze the efficiency limits of single and multiple junction organic solar cells, and discuss the challenges facing their practical implementations.
Single-Nanoflake Photo-Electrochemistry Reveals Champion and Spectator Flakes in Exfoliated MoSe 2 Films

DOE PAGES

Todt, Michael A.; Isenberg, Allan E.; Nanayakkara, Sanjini U.; ...

2018-03-06

Semiconducting transition-metal dichalcogenide (TMD) nanoflake thin films are promising large-area electrodes for photo-electrochemical solar energy conversion applications. However, their energy conversion efficiencies are typically much lower than those of bulk electrodes. It is unclear to what extent this efficiency gap stems from differences among nanoflakes (e.g., area, thickness, and surface structural features). It is also unclear whether individual exfoliated nanoflakes can achieve energy conversion efficiencies similar to those of bulk crystals. Here, we use a single-nanoflake photo-electrochemical approach to show that there are both highly active and completely inactive nanoflakes within a film. For the exfoliated MoSe 2 samples studiedmore » herein, 7% of nanoflakes are highly active champions, whose photocurrent efficiency exceeds that of the bulk crystal. However, 66% of nanoflakes are inactive spectators, which are mostly responsible for the overall lower photocurrent efficiency compared to the bulk crystal. The photocurrent collection efficiency increases with nanoflake area and decreases more at perimeter edges than at interior step edges. These observations, which are hidden in ensemble-level measurements, reveal the underlying performance issues of exfoliated TMD electrodes for photo-electrochemical energy conversion applications.« less
Conversion of visible light to electrical energy - Stable cadmium selenide photoelectrodes in aqueous electrolytes

NASA Technical Reports Server (NTRS)

Wrighton, M. S.; Ellis, A. B.; Kaiser, S. W.

1977-01-01

Stabilization of n-type CdSe to photoanodic dissolution is reported. The stabilization is accomplished by the competitive oxidation of S(--) or S(n)(--) at the CdSe photoanode in an electrochemical cell. Such stabilized cells are shown to sustain the conversion of low energy (not less than 1.7 eV) visible light to electricity with good efficiency and no deterioration of the CdSe photoelectrode or of the electrolyte. The electrolyte undergoes no net chemical change because the oxidation occurring at the photoelectrode is reversed at the cathode. Conversion of monochromatic light at 633 nm to electricity is shown to be up to approximately 9% efficient with output potentials of approximately 0.4 V. Conversion of solar energy to electricity is estimated to be approximately 2% efficient.
Platinum-Free Counter Electrode Comprised of Metal-Organic-Framework (MOF)-Derived Cobalt Sulfide Nanoparticles for Efficient Dye-Sensitized Solar Cells (DSSCs)

PubMed Central

Hsu, Shao-Hui; Li, Chun-Ting; Chien, Heng-Ta; Salunkhe, Rahul R.; Suzuki, Norihiro; Yamauchi, Yusuke; Ho, Kuo-Chuan; Wu, Kevin C.-W.

2014-01-01

We fabricated a highly efficient (with a solar-to-electricity conversion efficiency (η) of 8.1%) Pt-free dye-sensitized solar cell (DSSC). The counter electrode was made of cobalt sulfide (CoS) nanoparticles synthesized via surfactant-assisted preparation of a metal organic framework, ZIF-67, with controllable particle sizes (50 to 320 nm) and subsequent oxidation and sulfide conversion. In contrast to conventional Pt counter electrodes, the synthesized CoS nanoparticles exhibited higher external surface areas and roughness factors, as evidenced by X-ray diffraction (XRD), scanning electron microscopy (SEM) element mapping, and electrochemical analysis. Incident photon-to-current conversion efficiency (IPCE) results showed an increase in the open circuit voltage (VOC) and a decrease in the short-circuit photocurrent density (Jsc) for CoS-based DSSCs compared to Pt-based DSSCs, resulting in a similar power conversion efficiency. The CoS-based DSSC fabricated in the study show great potential for economically friendly production of Pt-free DSSCs. PMID:25382139
Two-step photon up-conversion solar cells

PubMed Central

Asahi, Shigeo; Teranishi, Haruyuki; Kusaki, Kazuki; Kaizu, Toshiyuki; Kita, Takashi

2017-01-01

Reducing the transmission loss for below-gap photons is a straightforward way to break the limit of the energy-conversion efficiency of solar cells (SCs). The up-conversion of below-gap photons is very promising for generating additional photocurrent. Here we propose a two-step photon up-conversion SC with a hetero-interface comprising different bandgaps of Al0.3Ga0.7As and GaAs. The below-gap photons for Al0.3Ga0.7As excite GaAs and generate electrons at the hetero-interface. The accumulated electrons at the hetero-interface are pumped upwards into the Al0.3Ga0.7As barrier by below-gap photons for GaAs. Efficient two-step photon up-conversion is achieved by introducing InAs quantum dots at the hetero-interface. We observe not only a dramatic increase in the additional photocurrent, which exceeds the reported values by approximately two orders of magnitude, but also an increase in the photovoltage. These results suggest that the two-step photon up-conversion SC has a high potential for implementation in the next-generation high-efficiency SCs. PMID:28382945
Structural and functional correlates for language efficiency in auditory word processing.

PubMed

Jung, JeYoung; Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally.
Structural and functional correlates for language efficiency in auditory word processing

PubMed Central

Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally. PMID:28892503
Highly Efficient Protein Misfolding Cyclic Amplification

PubMed Central

Ostapchenko, Valeriy G.; Savtchenk, Regina; Alexeeva, Irina; Rohwer, Robert G.; Baskakov, Ilia V.

2011-01-01

Protein misfolding cyclic amplification (PMCA) provides faithful replication of mammalian prions in vitro and has numerous applications in prion research. However, the low efficiency of conversion of PrPC into PrPSc in PMCA limits the applicability of PMCA for many uses including structural studies of infectious prions. It also implies that only a small sub-fraction of PrPC may be available for conversion. Here we show that the yield, rate, and robustness of prion conversion and the sensitivity of prion detection are significantly improved by a simple modification of the PMCA format. Conducting PMCA reactions in the presence of Teflon beads (PMCAb) increased the conversion of PrPC into PrPSc from ∼10% to up to 100%. In PMCAb, a single 24-hour round consistently amplified PrPSc by 600-700-fold. Furthermore, the sensitivity of prion detection in one round (24 hours) increased by 2-3 orders of magnitude. Using serial PMCAb, a 1012-fold dilution of scrapie brain material could be amplified to the level detectible by Western blotting in 3 rounds (72 hours). The improvements in amplification efficiency were observed for the commonly used hamster 263K strain and for the synthetic strain SSLOW that otherwise amplifies poorly in PMCA. The increase in the amplification efficiency did not come at the expense of prion replication specificity. The current study demonstrates that poor conversion efficiencies observed previously have not been due to the scarcity of a sub-fraction of PrPC susceptible to conversion nor due to limited concentrations of essential cellular cofactors required for conversion. The new PMCAb format offers immediate practical benefits and opens new avenues for developing fast ultrasensitive assays and for producing abundant quantities of PrPSc in vitro. PMID:21347353

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

PubMed

Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

2015-11-01

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.
Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Hui; Song, Yongduan; Xue, Fangzheng

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than themore » SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.« less
Isolation and characterization of two chlorophyll-deficient genes in soybean

USDA-ARS?s Scientific Manuscript database

We have identified a viable-yellow and a lethal-yellow mutant in soybean. The three phenotypes green, lethal- and viable-yellow were easily distinguished based on their light reflectance indices, chlorophyll abundance and photochemical conversion efficiency. Photochemical conversion efficiency was r...
Electrochemistry of the Zinc-Silver Oxide System. Part 2: Practical Measurements of Energy Conversion Using Commercial Miniature Cells.

ERIC Educational Resources Information Center

Smith, Michael J.; Vincent, Colin A.

1989-01-01

Summarizes the quantitative relationships pertaining to the operation of electrochemical cells. Energy conversion efficiency, cycle efficiency, battery power, and energy/power density of two types of zinc-silver oxide cells are discussed. (YP)
Neural Development of Networks for Audiovisual Speech Comprehension

ERIC Educational Resources Information Center

Dick, Anthony Steven; Solodkin, Ana; Small, Steven L.

2010-01-01

Everyday conversation is both an auditory and a visual phenomenon. While visual speech information enhances comprehension for the listener, evidence suggests that the ability to benefit from this information improves with development. A number of brain regions have been implicated in audiovisual speech comprehension, but the extent to which the…
[Research on the photoelectric conversion efficiency of grating antireflective layer solar cells].

PubMed

Zhong, Hui; Gao, Yong-Yi; Zhou, Ren-Long; Zhou, Bing-ju; Tang, Li-qiang; Wu, Ling-xi; Li, Hong-jian

2011-07-01

A numerical investigation of the effect of grating antireflective layer structure on the photoelectric conversion efficiency of solar cells was carried out by the finite-difference time-domain method. The influence of grating shape, height and the metal film thickness coated on grating surface on energy storage was analyzed in detail. It was found that the comparison between unoptimized and optimized surface grating structure on solar cells shows that the optimization of surface by grating significantly increases the energy storage capability and greatly improves the efficiency, especially of the photoelectric conversion efficiency and energy storage of the triangle grating. As the film thickness increases, energy storage effect increases, while as the film thickness is too thick, energy storage effect becomes lower and lower.
Associations between motor unit action potential parameters and surface EMG features.

PubMed

Del Vecchio, Alessandro; Negro, Francesco; Felici, Francesco; Farina, Dario

2017-10-01

The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDF MU ), and amplitude (RMS MU ) of action potentials of 587 motor units from 13 individuals were assessed and associated with features of the interference EMG. MUCV was positively associated with RT ( R 2 = 0.64 ± 0.14), whereas MDF MU and RMS MU showed a weaker relation with RT ( R 2 = 0.11 ± 0.11 and 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV ( R 2 = 0.71), with a strong association to ankle dorsiflexion force ( R 2 = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated with motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies. NEW & NOTEWORTHY The surface EMG provides information on the neural drive to muscles. However, the associations between EMG features and neural drive have been long debated due to unavailability of motor unit population data. Here, by using novel highly accurate decomposition of the EMG, we related motor unit population behavior to a wide range of voluntary forces. The results fully clarify the potential and limitation of the surface EMG to provide estimates of the neural drive to muscles. Copyright © 2017 the American Physiological Society.
Nonlinear frequency conversion of radiation from a copper-vapor laser

NASA Astrophysics Data System (ADS)

Polunin, Iu. P.; Troitskii, V. O.

1987-11-01

The nonlinear frequency conversion of copper-vapor laser radiation in a KDP crystal was studied experimentally. Output powers of 600 mW and 120 mW were obtained at wavelengths of 271 nm (the sum frequency) and 289 nm (the second harmonic of the yellow line), respectively. The conversion efficiency in both cases was about 3 percent; when selector losses were taken into accounted, the efficiency amounted to 5 percent.
Design of hybrid nanoheterostructure systems for enhanced quantum and solar conversion efficiencies in dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Kılıç, Bayram; Telli, Hakan; Tüzemen, Sebahattin; Başaran, Ali; Pirge, Gursev

2015-04-01

Dye sensitized solar cells (DSSCs) with an innovative design involving controlled-morphology vertically aligned (VA) ZnO nanowires within mesoporous TiO2 structures with ultrahigh surface area for implementation as photoanodes are herein reported. Although TiO2 nanostructures exhibit excellent power conversion efficiency, the electron transport rate is low owing to low electron mobility. To overcome this, ZnO nanowires with high electron mobility have been investigated as potential candidates for photoanodes. However, the power conversion efficiency of ZnO nanowires is still lower than that of TiO2 owing to their low internal surface area. Consequently, in this work, vertical growth of ZnO nanowires within mesoporous TiO2 structures is carried out to increase their solar power conversion efficiency. The photovoltaic performance of solar cells using ZnO nanowires, mesoporous TiO2, and TiO2/ZnO hybrid structures are compared. The VA TiO2/ZnO hybrid structures are found to provide direct electron transfer compared with the tortuous pathway of zero-dimensional nanostructures, resulting in an increased conversion efficiency. It is demonstrated that the light scattering of the photoanode film is increased and electron recombination is decreased when an appropriate amount of mesoporous TiO2 is used as a substrate for ZnO nanowires. The DSSC fabricated with the TiO2/ZnO hybrid photoanode prepared with 15.8 wt. % TiO2 showed the highest conversion efficiency of 7.30%, approximately 5%, 18%, and 40% higher than that of DSSCs fabricated with 3.99 wt. % TiO2, pure TiO2, and pure ZnO photoanodes, respectively.
Neural substrates of sublexical processing for spelling.

PubMed

DeMarco, Andrew T; Wilson, Stephen M; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

2017-01-01

We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. Copyright © 2016 Elsevier Inc. All rights reserved.
Kannada character recognition system using neural network

NASA Astrophysics Data System (ADS)

Kumar, Suresh D. S.; Kamalapuram, Srinivasa K.; Kumar, Ajay B. R.

2013-03-01

Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. As there is no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India. In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten Kannada character is resized into 20x30 Pixel. The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different Kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.
Neural correlates of saccadic inhibition in healthy elderly and patients with amnestic mild cognitive impairment

PubMed Central

Alichniewicz, K. K.; Brunner, F.; Klünemann, H. H.; Greenlee, M. W.

2013-01-01

Performance on tasks that require saccadic inhibition declines with age and altered inhibitory functioning has also been reported in patients with Alzheimer's disease. Although mild cognitive impairment (MCI) is assumed to be a high-risk factor for conversion to AD, little is known about changes in saccadic inhibition and its neural correlates in this condition. Our study determined whether the neural activation associated with saccadic inhibition is altered in persons with amnestic mild cognitive impairment (aMCI). Functional magnetic resonance imaging (fMRI) revealed decreased activation in parietal lobe in healthy elderly persons compared to young persons and decreased activation in frontal eye fields in aMCI patients compared to healthy elderly persons during the execution of anti-saccades. These results illustrate that the decline in inhibitory functions is associated with impaired frontal activation in aMCI. This alteration in function might reflect early manifestations of AD and provide new insights in the neural activation changes that occur in pathological ageing. PMID:23898312
Neural Substrates of Sublexical Processing for Spelling

PubMed Central

Wilson, Stephen M.; Rising, Kindle; Rapcsak, Steven Z.; Beeson, Pélagie M.

2016-01-01

We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. PMID:27838547
Tauroursodeoxycholic acid increases neural stem cell pool and neuronal conversion by regulating mitochondria-cell cycle retrograde signaling

PubMed Central

Xavier, Joana M; Morgado, Ana L; Rodrigues, Cecília MP; Solá, Susana

2014-01-01

The low survival and differentiation rates of stem cells after either transplantation or neural injury have been a major concern of stem cell-based therapy. Thus, further understanding long-term survival and differentiation of stem cells may uncover new targets for discovery and development of novel therapeutic approaches. We have previously described the impact of mitochondrial apoptosis-related events in modulating neural stem cell (NSC) fate. In addition, the endogenous bile acid, tauroursodeoxycholic acid (TUDCA) was shown to be neuroprotective in several animal models of neurodegenerative disorders by acting as an anti-apoptotic and anti-oxidant molecule at the mitochondrial level. Here, we hypothesize that TUDCA might also play a role on NSC fate decision. We found that TUDCA prevents mitochondrial apoptotic events typical of early-stage mouse NSC differentiation, preserves mitochondrial integrity and function, while enhancing self-renewal potential and accelerating cell cycle exit of NSCs. Interestingly, TUDCA prevention of mitochondrial alterations interfered with NSC differentiation potential by favoring neuronal rather than astroglial conversion. Finally, inhibition of mitochondrial reactive oxygen species (mtROS) scavenger and adenosine triphosphate (ATP) synthase revealed that the effect of TUDCA is dependent on mtROS and ATP regulation levels. Collectively, these data underline the importance of mitochondrial stress control of NSC fate decision and support a new role for TUDCA in this process. PMID:25483094
An ERP investigation of the co-development of hemispheric lateralization of face and word recognition

PubMed Central

Dundas, Eva M.; Plaut, David C.; Behrmann, Marlene

2014-01-01

The adult human brain would appear to have specialized and independent neural systems for the visual processing of words and faces. Extensive evidence has demonstrated greater selectivity for written words in the left over right hemisphere, and, conversely, greater selectivity for faces in the right over left hemisphere. This study examines the emergence of these complementary neural profiles, as well as the possible relationship between them. Using behavioral and neurophysiological measures, in adults, we observed the standard finding of greater accuracy and a larger N170 ERP component in the left over right hemisphere for words, and conversely, greater accuracy and a larger N170 in the right over the left hemisphere for faces. We also found that, although children aged 7-12 years revealed the adult hemispheric pattern for words, they showed neither a behavioral nor a neural hemispheric superiority for faces. Of particular interest, the magnitude of their N170 for faces in the right hemisphere was related to that of the N170 for words in their left hemisphere. These findings suggest that the hemispheric organization of face recognition and of word recognition do not develop independently, and that word lateralization may precede and drive later face lateralization. A theoretical account for the findings, in which competition for visual representations unfolds over the course of development, is discussed. PMID:24933662
An ERP investigation of the co-development of hemispheric lateralization of face and word recognition.

PubMed

Dundas, Eva M; Plaut, David C; Behrmann, Marlene

2014-08-01

The adult human brain would appear to have specialized and independent neural systems for the visual processing of words and faces. Extensive evidence has demonstrated greater selectivity for written words in the left over right hemisphere, and, conversely, greater selectivity for faces in the right over left hemisphere. This study examines the emergence of these complementary neural profiles, as well as the possible relationship between them. Using behavioral and neurophysiological measures, in adults, we observed the standard finding of greater accuracy and a larger N170 ERP component in the left over right hemisphere for words, and conversely, greater accuracy and a larger N170 in the right over the left hemisphere for faces. We also found that although children aged 7-12 years revealed the adult hemispheric pattern for words, they showed neither a behavioral nor a neural hemispheric superiority for faces. Of particular interest, the magnitude of their N170 for faces in the right hemisphere was related to that of the N170 for words in their left hemisphere. These findings suggest that the hemispheric organization of face recognition and of word recognition does not develop independently, and that word lateralization may precede and drive later face lateralization. A theoretical account for the findings, in which competition for visual representations unfolds over the course of development, is discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
On-Chip Strong Coupling and Efficient Frequency Conversion between Telecom and Visible Optical Modes.

PubMed

Guo, Xiang; Zou, Chang-Ling; Jung, Hojoong; Tang, Hong X

2016-09-16

While the frequency conversion of photons has been realized with various approaches, the realization of strong coupling between optical modes of different colors has never been reported. Here, we present an experimental demonstration of strong coupling between telecom (1550 nm) and visible (775 nm) optical modes on an aluminum nitride photonic chip. The nonreciprocal normal-mode splitting is demonstrated as a result of the coherent interference between photons with different colors. Furthermore, a wideband, bidirectional frequency conversion with 0.14 on-chip conversion efficiency and a bandwidth up to 1.2 GHz is demonstrated.
Functionalization of graphene for efficient energy conversion and storage.

PubMed

Dai, Liming

2013-01-15

As global energy consumption accelerates at an alarming rate, the development of clean and renewable energy conversion and storage systems has become more important than ever. Although the efficiency of energy conversion and storage devices depends on a variety of factors, their overall performance strongly relies on the structure and properties of the component materials. Nanotechnology has opened up new frontiers in materials science and engineering to meet this challenge by creating new materials, particularly carbon nanomaterials, for efficient energy conversion and storage. As a building block for carbon materials of all other dimensionalities (such as 0D buckyball, 1D nanotube, 3D graphite), the two-dimensional (2D) single atomic carbon sheet of graphene has emerged as an attractive candidate for energy applications due to its unique structure and properties. Like other materials, however, a graphene-based material that possesses desirable bulk properties rarely features the surface characteristics required for certain specific applications. Therefore, surface functionalization is essential, and researchers have devised various covalent and noncovalent chemistries for making graphene materials with the bulk and surface properties needed for efficient energy conversion and storage. In this Account, I summarize some of our new ideas and strategies for the controlled functionalization of graphene for the development of efficient energy conversion and storage devices, such as solar cells, fuel cells, supercapacitors, and batteries. The dangling bonds at the edge of graphene can be used for the covalent attachment of various chemical moieties while the graphene basal plane can be modified via either covalent or noncovalent functionalization. The asymmetric functionalization of the two opposite surfaces of individual graphene sheets with different moieties can lead to the self-assembly of graphene sheets into hierarchically structured materials. Judicious application of these site-selective reactions to graphene sheets has opened up a rich field of graphene-based energy materials with enhanced performance in energy conversion and storage. These results reveal the versatility of surface functionalization for making sophisticated graphene materials for energy applications. Even though many covalent and noncovalent functionalization methods have already been reported, vast opportunities remain for developing novel graphene materials for highly efficient energy conversion and storage systems.
Building on prior knowledge without building it in.

PubMed

Hansen, Steven S; Lampinen, Andrew K; Suri, Gaurav; McClelland, James L

2017-01-01

Lake et al. propose that people rely on "start-up software," "causal models," and "intuitive theories" built using compositional representations to learn new tasks more efficiently than some deep neural network models. We highlight the many drawbacks of a commitment to compositional representations and describe our continuing effort to explore how the ability to build on prior knowledge and to learn new tasks efficiently could arise through learning in deep neural networks.
Dynamic illumination of spatially restricted or large brain volumes via a single tapered optical fiber

PubMed Central

Pisanello, Marco; Oldenburg, Ian A.; Sileo, Leonardo; Markowitz, Jeffrey E.; Peterson, Ralph E.; Della Patria, Andrea; Haynes, Trevor M.; Emara, Mohamed S.; Spagnolo, Barbara; Datta, Sandeep Robert; De Vittorio, Massimo; Sabatini, Bernardo L.

2017-01-01

Optogenetics promises spatiotemporal precise control of neural processes using light. However, the spatial extent of illumination within the brain is difficult to control and cannot be adjusted using standard fiber optics. We demonstrate that optical fibers with tapered tips can be used to illuminate either spatially restricted or large brain volumes. Remotely adjusting the light input angle to the fiber varies the light-emitting portion of the taper over several millimeters without movement of the implant. We use this mode to activate dorsal versus ventral striatum of individual mice and reveal different effects of each manipulation on motor behavior. Conversely, injecting light over the full numerical aperture of the fiber results in light emission from the entire taper surface, achieving broader and more efficient optogenetic activation of neurons when compared to the standard flat-faced fiber stimulation. Thus, tapered fibers permit focal or broad illumination that can be precisely and dynamically matched to experimental needs. PMID:28628101

Dynamic illumination of spatially restricted or large brain volumes via a single tapered optical fiber.

PubMed

Pisanello, Ferruccio; Mandelbaum, Gil; Pisanello, Marco; Oldenburg, Ian A; Sileo, Leonardo; Markowitz, Jeffrey E; Peterson, Ralph E; Della Patria, Andrea; Haynes, Trevor M; Emara, Mohamed S; Spagnolo, Barbara; Datta, Sandeep Robert; De Vittorio, Massimo; Sabatini, Bernardo L

2017-08-01

Optogenetics promises precise spatiotemporal control of neural processes using light. However, the spatial extent of illumination within the brain is difficult to control and cannot be adjusted using standard fiber optics. We demonstrate that optical fibers with tapered tips can be used to illuminate either spatially restricted or large brain volumes. Remotely adjusting the light input angle to the fiber varies the light-emitting portion of the taper over several millimeters without movement of the implant. We use this mode to activate dorsal versus ventral striatum of individual mice and reveal different effects of each manipulation on motor behavior. Conversely, injecting light over the full numerical aperture of the fiber results in light emission from the entire taper surface, achieving broader and more efficient optogenetic activation of neurons, compared to standard flat-faced fiber stimulation. Thus, tapered fibers permit focal or broad illumination that can be precisely and dynamically matched to experimental needs.
Investigation of operating parameters on CO2 splitting by dielectric barrier discharge plasma

NASA Astrophysics Data System (ADS)

Pan, CHEN; Jun, SHEN; Tangchun, RAN; Tao, YANG; Yongxiang, YIN

2017-12-01

Experiments of CO2 splitting by dielectric barrier discharge (DBD) plasma were carried out, and the influence of CO2 flow rate, plasma power, discharge voltage, discharge frequency on CO2 conversion and process energy efficiency were investigated. It was shown that the absolute quantity of CO2 decomposed was only proportional to the amount of conductive electrons across the discharge gap, and the electron amount was proportional to the discharge power; the energy efficiency of CO2 conversion was almost a constant at a lower level, which was limited by CO2 inherent discharge character that determined a constant gap electric field strength. This was the main reason why CO2 conversion rate decreased as the CO2 flow rate increase and process energy efficiency was decreased a little as applied frequency increased. Therefore, one can improve the CO2 conversion by less feed flow rate or larger discharge power in DBD plasma, but the energy efficiency is difficult to improve.
Ultra-wideband high-efficiency reflective linear-to-circular polarization converter based on metasurface at terahertz frequencies.

PubMed

Jiang, Yannan; Wang, Lei; Wang, Jiao; Akwuruoha, Charles Nwakanma; Cao, Weiping

2017-10-30

The polarization conversion of electromagnetic (EM) waves, especially linear-to-circular (LTC) polarization conversion, is of great significance in practical applications. In this study, we propose an ultra-wideband high-efficiency reflective LTC polarization converter based on a metasurface in the terahertz regime. It consists of periodic unit cells, each cell of which is formed by a double split resonant square ring, dielectric layer, and fully reflective gold mirror. In the frequency range of 0.60 - 1.41 THz, the magnitudes of the reflection coefficients reach approximately 0.7, and the phase difference between the two orthogonal electric field components of the reflected wave is close to 90° or -270°. The results indicate that the relative bandwidth reaches 80% and the efficiency is greater than 88%, thus, ultra-wideband high-efficiency LTC polarization conversion has been realized. Finally, the physical mechanism of the polarization conversion is revealed. This converter has potential applications in antenna design, EM measurement, and stealth technology.
Solar energy conversion with photon-enhanced thermionic emission

NASA Astrophysics Data System (ADS)

Kribus, Abraham; Segev, Gideon

2016-07-01

Photon-enhanced thermionic emission (PETE) converts sunlight to electricity with the combined photonic and thermal excitation of charge carriers in a semiconductor, leading to electron emission over a vacuum gap. Theoretical analyses predict conversion efficiency that can match, or even exceed, the efficiency of traditional solar thermal and photovoltaic converters. Several materials have been examined as candidates for radiation absorbers and electron emitters, with no conclusion yet on the best set of materials to achieve high efficiency. Analyses have shown the complexity of the energy conversion and transport processes, and the significance of several loss mechanisms, requiring careful control of material properties and optimization of the device structure. Here we survey current research on PETE modeling, materials, and device configurations, outline the advances made, and stress the open issues and future research needed. Based on the substantial progress already made in this young topic, and the potential of high conversion efficiency based on theoretical performance limits, continued research in this direction is very promising and may yield a competitive technology for solar electricity generation.
Study of solid-conversion gaseous detector based on GEM for high energy X-ray industrial CT.

PubMed

Zhou, Rifeng; Zhou, Yaling

2014-01-01

The general gaseous ionization detectors are not suitable for high energy X-ray industrial computed tomography (HEICT) because of their inherent limitations, especially low detective efficiency and large volume. The goal of this study was to investigate a new type of gaseous detector to solve these problems. The novel detector was made by a metal foil as X-ray convertor to improve the conversion efficiency, and the Gas Electron Multiplier (hereinafter "GEM") was used as electron amplifier to lessen its volume. The detective mechanism and signal formation of the detector was discussed in detail. The conversion efficiency was calculated by using EGSnrc Monte Carlo code, and the transport course of photon and secondary electron avalanche in the detector was simulated with the Maxwell and Garfield codes. The result indicated that this detector has higher conversion efficiency as well as less volume. Theoretically this kind of detector could be a perfect candidate for replacing the conventional detector in HEICT.
Energy conversion in isothermal nonlinear irreversible processes - struggling for higher efficiency

NASA Astrophysics Data System (ADS)

Ebeling, W.; Feistel, R.

2017-06-01

First we discuss some early work of Ulrike Feudel on structure formation in nonlinear reactions including ions and the efficiency of the conversion of chemical into electrical energy. Then we give some survey about isothermal energy conversion from chemical to higher forms of energy like mechanical, electrical and ecological energy. Isothermal means here that there are no temperature gradients within the model systems. We consider examples of energy conversion in several natural processes and in some devices like fuel cells. Further, as an example, we study analytically the dynamics and efficiency of a simple "active circuit" converting chemical into electrical energy and driving currents which is roughly modeling fuel cells. Finally we investigate an analogous ecological system of Lotka-Volterra type consisting of an "active species" consuming some passive "chemical food". We show analytically for both these models that the efficiency increases with the load, reaches values higher then 50 percent in a narrow regime of optimal load and goes beyond some maximal load abruptly to zero.
Reversible thermodynamic cycle for AMTEC power conversion. [Alkali Metal Thermal-to-Electric Converter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vining, C.B.; Williams, R.M.; Underwood, M.L.

1993-10-01

An AMTEC cell, may be described as performing two distinct energy conversion processes: (i) conversion of heat to mechanical energy via a sodium-based heat engine and (ii) conversion of mechanical energy to electrical energy by utilizing the special properties of the electrolyte material. The thermodynamic cycle appropriate to an alkali metal thermal-to-electric converter cell is discussed for both liquid- and vapor-fed modes of operation, under the assumption that all processes can be performed reversibly. In the liquid-fed mode, the reversible efficiency is greater than 89.6% of Carnot efficiency for heat input and rejection temperatures (900--1,300 and 400--800 K, respectively) typicalmore » of practical devices. Vapor-fed cells can approach the efficiency of liquid-fed cells. Quantitative estimates confirm that the efficiency is insensitive to either the work required to pressurize the sodium liquid or the details of the state changes associated with cooling the low pressure sodium gas to the heat rejection temperature.« less
Glucose buffer is suitable for blood group conversion with α-N acetylgalactosaminidase and α-galactosidase.

PubMed

Gao, Hong-Wei; Li, Su-Bo; Bao, Guo-Qiang; Zhang, Xue; Li, Hui; Wang, Ying-Li; Tan, Ying-Xia; Ji, Shou-Ping; Gong, Feng

2014-01-01

It is well known that the buffer plays a key role in the enzymatic reaction involved in blood group conversion. In previous study, we showed that a glycine buffer is suitable for A to O or B to O blood group conversion. In this study, we investigated the use of 5% glucose and other buffers for A to O or B to O blood group conversion by α-N-acetylgalactosaminidase or α-galactosidase. We compared the binding ability of α-N-acetylgalactosaminidase/α-galactosidase with red blood cells (RBC) in different reaction buffers, such as normal saline, phosphate-buffered saline (PBS), a disodium hydrogen phosphate-based buffer (PCS), and 5% commercial glucose solution. The doses of enzymes necessary for the A/B to O conversion in different reaction buffers were determined and compared. The enzymes' ability to bind to RBC was evaluated by western blotting, and routine blood typing and fluorescence activated cell sorting was used to evaluate B/A to O conversion efficiency. The A to O conversion efficiency in glucose buffer was similar to that in glycine buffer with the same dose (>0.06 mg/mL pRBC). B to O conversion efficiency in glucose buffer was also similar to that in glycine buffer with the same dose (>0.005 mg/mL pRBC). Most enzymes could bind with RBC in glycine or glucose buffer, but few enzymes could bind with RBC in PBS, PCS, or normal saline. These results indicate that 5% glucose solution provides a suitable condition for enzymolysis, especially for enzymes combining with RBC. Meanwhile, the conversion efficiency of A/B to O was similar in glucose buffer and glycine buffer. Moreover, 5% glucose solution has been used for years in venous transfusion, it is safe for humans and its cost is lower. Our results do, therefore, suggest that 5% glucose solution could become a novel suitable buffer for A/B to O blood group conversion.
Potential active materials for photo-supercapacitor: A review

NASA Astrophysics Data System (ADS)

Ng, C. H.; Lim, H. N.; Hayase, S.; Harrison, I.; Pandikumar, A.; Huang, N. M.

2015-11-01

The need for an endless renewable energy supply, typically through the utilization of solar energy in most applications and systems, has driven the expansion, versatility, and diversification of marketed energy storage devices. Energy storage devices such as hybridized dye-sensitized solar cell (DSSC)-capacitors and DSSC-supercapacitors have been invented for energy reservation. The evolution and vast improvement of these devices in terms of their efficiencies and flexibilities have further sparked the invention of the photo-supercapacitor. The idea of coupling a DSSC and supercapacitor as a complete energy conversion and storage device arose because the solar energy absorbed by dye molecules can be efficiently transferred and converted to electrical energy by adopting a supercapacitor as the energy delivery system. The conversion efficiency of a photo-supercapacitor is mainly dependent on the use of active materials during its fabrication. The performances of the dye, photoactive metal oxide, counter electrode, redox electrolyte, and conducting polymer are the primary factors contributing to high-energy-efficient conversion, which enhances the performance and shelf-life of a photo-supercapacitor. Moreover, the introduction of compact layer as a primary adherent film has been earmarked as an effort in enhancing power conversion efficiency of solar cell. Additionally, the development of electrolyte-free solar cell such as the invention of hole-conductor or perovskite solar cell is currently being explored extensively. This paper reviews and analyzes the potential active materials for a photo-supercapacitor to enhance the conversion and storage efficiencies.
Localised and delocalised optically induced conversion of composite glow peak 5 in LiF:Mg,Ti (TLD-100) to glow peak 4 as a function of postirradiation annealing temperature.

PubMed

Horowitz, Y S; Einav, Y; Biderman, S; Oster, L

2002-01-01

The composite structure of glow peak 5 in LiF:Mg,Ti (TLD-100) has been investigated using optical bleaching by 310 nm (4 eV) light. The glow peak conversion efficiency of peak 5a (Tm = 187 degrees C) to peak 4 traps is very high at a value of 3+/-0.5 (1 SD) whereas the glow peak conversion efficiency of peak 5 (Tm = 205 degrees C) to peak 4 traps is 0.0026+/-0.0012 (1 SD). The high conversion efficiency of peak 5a to peak 4 arises from direct optical ionisation of the electron in the electron-hole pair. leaving behind a singly-trapped hole (peak 4), a direct mechanism, relatively free of competitive mechanisms. Optical ionisation of the 'singly-trapped' electron (peak 5), however, can lead to peak 4 only via multi-stage mechanisms involving charge carrier transport in the valence and conduction bands, a mechanism subject to competitive processes. The conduction/valence band competitive processes lead to the factor of one thousand decrease in the conversion efficiency of peak 5 compared to peak 5a.
Learning and diagnosing faults using neural networks

NASA Technical Reports Server (NTRS)

Whitehead, Bruce A.; Kiech, Earl L.; Ali, Moonis

1990-01-01

Neural networks have been employed for learning fault behavior from rocket engine simulator parameters and for diagnosing faults on the basis of the learned behavior. Two problems in applying neural networks to learning and diagnosing faults are (1) the complexity of the sensor data to fault mapping to be modeled by the neural network, which implies difficult and lengthy training procedures; and (2) the lack of sufficient training data to adequately represent the very large number of different types of faults which might occur. Methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Secondly, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented during training. These methods were tested on a task of fault diagnosis by employing rocket engine simulator data. Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.
An improved protocol that induces human embryonic stem cells to differentiate into neural cells in vitro.

PubMed

Zhou, Jun-Mei; Chu, Jian-Xin; Chen, Xue-Jin

2008-01-01

Human embryonic stem (ES) cells have the capacity for self-renewal and are able to differentiate into any cell type. However, obtaining high-efficient neural differentiation from human ES cells remains a challenge. This study describes an improved 4-stage protocol to induce a human ES cell line derived from a Chinese population to differentiate into neural cells. At the first stage, embryonic bodies (EBs) were formed in a chemically-defined neural inducing medium rather than in traditional serum or serum-replacement medium. At the second stage, rosette-like structures were formed. At the third stage, the rosette-like structures were manually selected rather than enzymatically digested to form floating neurospheres. At the fourth stage, the neurospheres were further differentiated into neurons. The results show that, at the second stage, the rate of the formation of rosette-like structures from EBs induced by noggin was 88+/-6.32%, higher than that of retinoic acid 55+/-5.27%. Immunocytochemistry staining was used to confirm the neural identity of the cells. These results show a major improvement in obtaining efficient neural differentiation of human ES cells.
Fuzzy wavelet plus a quantum neural network as a design base for power system stability enhancement.

PubMed

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.
Nutrigenetic screening strains of the mulberry silkworm, Bombyx mori, for nutritional efficiency.

PubMed

Ramesha, Chinnaswamy; Lakshmi, Hothur; Kumari, Savarapu Sugnana; Anuradha, Chevva M; Kumar, Chitta Suresh

2012-01-01

The activity of sericulture is declining due the reduction of mulberry production area in sericulture practicing countries lead to adverse effects on silkworm rearing and cocoon production. Screening for nutrigenetic traits in silkworm, Bombyx mori L. (Lepidoptera: Bombycidae) is an essential prerequisite for better understanding and development of nutritionally efficient breeds/hybrids, which show less food consumption with higher efficiency conversion. The aim of this study was to identify nutritionally efficient polyvoltine silkworm strains using the germplasm breeds RMW(2), RMW(3), RMW(4), RMG(3), RMG(1), RMG(4), RMG(5), RMG(6) and APM(1) as the control. The 1(st) day of 5(th) stage silkworm larvae of polyvoltine strains were subjected to standard gravimetric analysis until spinning for three consecutive generations covering 3 different seasons on 19 nutrigenetic traits. Highly significant (p ≤ 0.001) differences were found among all nutrigenetic traits of polyvoltine silkworm strains in the experimental groups. The nutritionally efficient polvoltine silkworm strains were resulted by utilizing nutrition consumption index and efficiency of conversion of ingesta/cocoon traits as the index. Higher nutritional efficiency conversions were found in the polyvoltine silkworm strains on efficiency of conversion of ingesta to cocoon and shell than control. Comparatively smaller consumption index, respiration, metabolic rate with superior relative growth rate, and quantum of food ingesta and digesta requisite per gram of cocoon and shell were found; the lowest amount was in new polyvoltine strains compared to the control. Furthermore, based on the overall nutrigenetic traits utilized as index or 'biomarkers', three polyvoltine silkworm strains (RMG(4), RMW(2), and RMW(3)) were identified as having the potential for nutrition efficiency conversion. The data from the present study advances our knowledge for the development of nutritionally efficient silkworm breeds/hybrids and their effective commercial utilization in the sericulture industry.
Nutrigenetic screening strains of the mulberry silkworm, Bombyx mori, for nutritional efficiency.

PubMed

Chinnaswamy, Ramesha; Lakshmi, Hothur; Kumari, Savarapu S; Anuradha, Chebba M; Kumar, Chitta S

2012-01-01

The activity of sericulture is declining due the reduction of mulberry production area in sericulture practicing countries lead to adverse effects on silkworm rearing and cocoon production. Screening for nutrigenetic traits in silkworm, Bombyx mori L. (Lepidoptera: Bombycidae) is an essential prerequisite for better understanding and development of nutritionally efficient breeds/hybrids, which show less food consumption with higher efficiency conversion. The aim of this study was to identify nutritionally efficient polyvoltine silkworm strains using the germplasm breeds RMW(2), RMW(3), RMW(4), RMG(3), RMG(1), RMG(4), RMG(5), RMG(6) and APM(1) as the control. The 1(st) day of 5(th) stage silkworm larvae of polyvoltine strains were subjected to standard gravimetric analysis until spinning for three consecutive generations covering three different seasons on 19 nutrigenetic traits. Highly significant (p ≤ 0.001) differences were found among all nutrigenetic traits of polyvoltine silkworm strains in the experimental groups. The nutritionally efficient polvoltine silkworm strains were resulted by utilizing nutrition consumption index and efficiency of conversion of ingesta/cocoon traits as the index. Higher nutritional efficiency conversions were found in the polyvoltine silkworm strains on efficiency of conversion of ingesta to cocoon and shell than control. Comparatively smaller consumption index, respiration, metabolic rate with superior relative growth rate, and quantum of food ingesta and digesta requisite per gram of cocoon and shell were shown; the lowest amount was in new polyvoltine strains compared to the control. Furthermore, based on the overall nutrigenetic traits utilized as index or 'biomarkers', three polyvoltine silkworm strains (RMG(4), RMW(2), and RMW(3)) were identified as having the potential for nutrition efficiency conversion. The data from the present study advances our knowledge for the development of nutritionally efficient silkworm breeds/hybrids and their effective commercial utilization in the sericulture industry.
Nutrigenetic Screening Strains of the Mulberry Silkworm, Bombyx mori, for Nutritional Efficiency

PubMed Central

Chinnaswamy, Ramesha; Lakshmi, Hothur; Kumari, Savarapu S.; Anuradha, Chebba M.; Kumar, Chitta S.

2012-01-01

The activity of sericulture is declining due the reduction of mulberry production area in sericulture practicing countries lead to adverse effects on silkworm rearing and cocoon production. Screening for nutrigenetic traits in silkworm, Bombyx mori L. (Lepidoptera: Bombycidae) is an essential prerequisite for better understanding and development of nutritionally efficient breeds/hybrids, which show less food consumption with higher efficiency conversion. The aim of this study was to identify nutritionally efficient polyvoltine silkworm strains using the germplasm breeds RMW2, RMW3, RMW4, RMG3, RMG1, RMG4, RMG5, RMG6 and APM1 as the control. The 1st day of 5th stage silkworm larvae of polyvoltine strains were subjected to standard gravimetric analysis until spinning for three consecutive generations covering three different seasons on 19 nutrigenetic traits. Highly significant (p ≤ 0.001) differences were found among all nutrigenetic traits of polyvoltine silkworm strains in the experimental groups. The nutritionally efficient polvoltine silkworm strains were resulted by utilizing nutrition consumption index and efficiency of conversion of ingesta/cocoon traits as the index. Higher nutritional efficiency conversions were found in the polyvoltine silkworm strains on efficiency of conversion of ingesta to cocoon and shell than control. Comparatively smaller consumption index, respiration, metabolic rate with superior relative growth rate, and quantum of food ingesta and digesta requisite per gram of cocoon and shell were shown; the lowest amount was in new polyvoltine strains compared to the control. Furthermore, based on the overall nutrigenetic traits utilized as index or ‘biomarkers’, three polyvoltine silkworm strains (RMG4, RMW2, and RMW3) were identified as having the potential for nutrition efficiency conversion. The data from the present study advances our knowledge for the development of nutritionally efficient silkworm breeds/hybrids and their effective commercial utilization in the sericulture industry. PMID:22938037
Nutrigenetic Screening Strains of the Mulberry Silkworm, Bombyx mori, for Nutritional Efficiency

PubMed Central

Ramesha, Chinnaswamy; Lakshmi, Hothur; Kumari, Savarapu Sugnana; Anuradha, Chevva M.; Kumar, Chitta Suresh

2012-01-01

The activity of sericulture is declining due the reduction of mulberry production area in sericulture practicing countries lead to adverse effects on silkworm rearing and cocoon production. Screening for nutrigenetic traits in silkworm, Bombyx mori L. (Lepidoptera: Bombycidae) is an essential prerequisite for better understanding and development of nutritionally efficient breeds/hybrids, which show less food consumption with higher efficiency conversion. The aim of this study was to identify nutritionally efficient polyvoltine silkworm strains using the germplasm breeds RMW2, RMW3, RMW4, RMG3, RMG1, RMG4, RMG5, RMG6 and APM1 as the control. The 1st day of 5th stage silkworm larvae of polyvoltine strains were subjected to standard gravimetric analysis until spinning for three consecutive generations covering 3 different seasons on 19 nutrigenetic traits. Highly significant (p ≤ 0.001) differences were found among all nutrigenetic traits of polyvoltine silkworm strains in the experimental groups. The nutritionally efficient polvoltine silkworm strains were resulted by utilizing nutrition consumption index and efficiency of conversion of ingesta/cocoon traits as the index. Higher nutritional efficiency conversions were found in the polyvoltine silkworm strains on efficiency of conversion of ingesta to cocoon and shell than control. Comparatively smaller consumption index, respiration, metabolic rate with superior relative growth rate, and quantum of food ingesta and digesta requisite per gram of cocoon and shell were found; the lowest amount was in new polyvoltine strains compared to the control. Furthermore, based on the overall nutrigenetic traits utilized as index or ‘biomarkers’, three polyvoltine silkworm strains (RMG4, RMW2, and RMW3) were identified as having the potential for nutrition efficiency conversion. The data from the present study advances our knowledge for the development of nutritionally efficient silkworm breeds/hybrids and their effective commercial utilization in the sericulture industry. PMID:22934597
Fault Analysis of Space Station DC Power Systems-Using Neural Network Adaptive Wavelets to Detect Faults

NASA Technical Reports Server (NTRS)

Momoh, James A.; Wang, Yanchun; Dolce, James L.

1997-01-01

This paper describes the application of neural network adaptive wavelets for fault diagnosis of space station power system. The method combines wavelet transform with neural network by incorporating daughter wavelets into weights. Therefore, the wavelet transform and neural network training procedure become one stage, which avoids the complex computation of wavelet parameters and makes the procedure more straightforward. The simulation results show that the proposed method is very efficient for the identification of fault locations.
Characterizing Deep Brain Stimulation effects in computationally efficient neural network models.

PubMed

Latteri, Alberta; Arena, Paolo; Mazzone, Paolo

2011-04-15

Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to find efficient treatments to face with this important disease. Experimental results in fact show that the PD neurological diseases are characterized by a pathological signal synchronization in BG. Parkinsonian tremor, for example, is ascribed to be caused by neuron populations of the Thalamic and Striatal structures that undergo an abnormal synchronization. On the contrary, in normal conditions, the activity of the same neuron populations do not appear to be correlated and synchronized. To study in details the effect of the stimulation signal on a pathological neural medium, efficient models of these neural structures were built, which are able to show, without any external input, the intrinsic properties of a pathological neural tissue, mimicking the BG synchronized dynamics.We start considering a model already introduced in the literature to investigate the effects of electrical stimulation on pathologically synchronized clusters of neurons. This model used Morris Lecar type neurons. This neuron model, although having a high level of biological plausibility, requires a large computational effort to simulate large scale networks. For this reason we considered a reduced order model, the Izhikevich one, which is computationally much lighter. The comparison between neural lattices built using both neuron models provided comparable results, both without traditional stimulation and in presence of all the stimulation protocols. This was a first result toward the study and simulation of the large scale neural networks involved in pathological dynamics.Using the reduced order model an inspection on the activity of two neural lattices was also carried out at the aim to analyze how the stimulation in one area could affect the dynamics in another area, like the usual medical treatment protocols require.The study of population dynamics that was carried out allowed us to investigate, through simulations, the positive effects of the stimulation signals in terms of desynchronization of the neural dynamics. The results obtained constitute a significant added value to the analysis of synchronization and desynchronization effects due to neural stimulation. This work gives the opportunity to more efficiently study the effect of stimulation in large scale yet computationally efficient neural networks. Results were compared both with the other mathematical models, using Morris Lecar and Izhikevich neurons, and with simulated Local Field Potentials (LFP).
Photon energy conversion by near-zero permittivity nonlinear materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luk, Ting S.; Sinclair, Michael B.; Campione, Salvatore

Efficient harmonic light generation can be achieved with ultrathin films by coupling an incident pump wave to an epsilon-near-zero (ENZ) mode of the thin film. As an example, efficient third harmonic generation from an indium tin oxide nanofilm (.lamda./42 thick) on a glass substrate for a pump wavelength of 1.4 .mu.m was demonstrated. A conversion efficiency of 3.3.times.10.sup.-6 was achieved by exploiting the field enhancement properties of the ENZ mode with an enhancement factor of 200. This nanoscale frequency conversion method is applicable to other plasmonic materials and reststrahlen materials in proximity of the longitudinal optical phonon frequencies.

Numerical analysis of СО laser frequency conversion efficiency in BaGa2GeSe6 crystal

NASA Astrophysics Data System (ADS)

Ionin, A. A.; Kinyaevskiy, I. O.; Mozhaeva, V. A.

2018-03-01

Non-linear optical characteristics of a new BaGa2GeSe6 crystal were numerically studied and compared with ones of the well-known mid-IR nonlinear crystal ZnGeP2 (ZGP). The calculations demonstrated the new crystal to be more efficient or, at least, competitive with the ZGP crystal for frequency conversion of CO- and CO2-laser radiation. It was found that a broadband two-stage frequency conversion of multi-line CO-laser radiation in this crystal is possible within the 2.5-9.0 µm wavelength range, with higher efficiency than in the ZGP crystal.
Quantitative Analysis of Defects in Silicon. [to predict energy conversion efficiency of silicon samples for solar cells

NASA Technical Reports Server (NTRS)

Natesh, R.; Smith, J. M.; Qidwai, H. A.; Bruce, T.

1979-01-01

The evaluation and prediction of the conversion efficiency for a variety of silicon samples with differences in structural defects, such as grain boundaries, twin boundaries, precipitate particles, dislocations, etc. are discussed. Quantitative characterization of these structural defects, which were revealed by etching the surface of silicon samples, is performed by using an image analyzer. Due to different crystal growth and fabrication techniques the various types of silicon contain a variety of trace impurity elements and structural defects. The two most important criteria in evaluating the various silicon types for solar cell applications are cost and conversion efficiency.
Behavioral and Electrophysiological Correlates of Memory Binding Deficits in Patients at Different Risk Levels for Alzheimer's Disease.

PubMed

Pietto, Marcos; Parra, Mario A; Trujillo, Natalia; Flores, Facundo; García, Adolfo M; Bustin, Julian; Richly, Pablo; Manes, Facundo; Lopera, Francisco; Ibáñez, Agustín; Baez, Sandra

2016-06-30

Deficits in visual short-term memory (VSTM) binding have been proposed as an early and specific marker for Alzheimer's disease (AD). However, no studies have explored the neural correlates of this domain in clinical categories involving prodromal stages with different risk levels of conversion to AD. We assessed underlying electrophysiological modulations in patients with mild cognitive impairment (MCI), patients in the MCI stages of familial AD carrying the mutation E280A of the presenilin-1 gene (MCI-FAD), and healthy controls. Moreover, we compared the behavioral performance and neural correlates of both patient groups. Participants completed a change-detection VSTM task assessing recognition of changes between shapes or shape-color bindings, presented in two consecutive arrays (i.e., study and test) while event related potentials (ERPs) were recorded. Changes always occurred in the test array and consisted of new features replacing studied features (shape-only) or features swapping across items (shape-color binding). Both MCI and MCI-FAD patients performed worse than controls in the shape-color binding condition. Early electrophysiological activity (100-250 ms) was significantly reduced in both clinical groups, particularly over fronto-central and parieto-occipital regions. However, shape-color binding performance and their reduced neural correlates were similar between MCI and MCI-FAD. Our results support the validity of the VSTM binding test and their neural correlates in the early detection of AD and highlight the importance of studies comparing samples at different risk for AD conversion. The combined analysis of behavioral and ERP data gleaned with the VSTM binding task can offer a valuable memory biomarker for AD.
Unity-Efficiency Parametric Down-Conversion via Amplitude Amplification.

PubMed

Niu, Murphy Yuezhen; Sanders, Barry C; Wong, Franco N C; Shapiro, Jeffrey H

2017-03-24

We propose an optical scheme, employing optical parametric down-converters interlaced with nonlinear sign gates (NSGs), that completely converts an n-photon Fock-state pump to n signal-idler photon pairs when the down-converters' crystal lengths are chosen appropriately. The proof of this assertion relies on amplitude amplification, analogous to that employed in Grover search, applied to the full quantum dynamics of single-mode parametric down-conversion. When we require that all Grover iterations use the same crystal, and account for potential experimental limitations on crystal-length precision, our optimized conversion efficiencies reach unity for 1≤n≤5, after which they decrease monotonically for n values up to 50, which is the upper limit of our numerical dynamics evaluations. Nevertheless, our conversion efficiencies remain higher than those for a conventional (no NSGs) down-converter.
Auger Up-Conversion of Low-Intensity Infrared Light in Engineered Quantum Dots

DOE PAGES

Makarov, Nikolay S.; Lin, Qianglu; Pietryga, Jeffrey M.; ...

2016-11-29

One source of efficiency losses in photovoltaic cells is their transparency toward solar photons with energies below the band gap of the absorbing layer. This loss can be reduced using a process of up-conversion whereby two or more sub-band-gap photons generate a single above-gap exciton. Traditional approaches to up-conversion, such as nonlinear two-photon absorption (2PA) or triplet fusion, suffer from low efficiency at solar light intensities, a narrow absorption bandwidth, nonoptimal absorption energies, and difficulties for implementing in practical devices. We show that these deficiencies can be alleviated using the effect of Auger up-conversion in thick-shell PbSe/CdSe quantum dots. Thismore » process relies on Auger recombination whereby two low-energy, core-based excitons are converted into a single higher-energy, shell-based exciton. When compared to their monocomponent counterparts, the tailored PbSe/CdSe heterostructures feature enhanced absorption cross-sections, a higher efficiency of the “productive” Auger pathway involving re-excitation of a hole, and longer lifetimes of both core- and shell-localized excitons. These features lead to effective up-conversion cross-sections that are more than 6 orders of magnitude higher than for standard nonlinear 2PA, which allows for efficient up-conversion of continuous wave infrared light at intensities as low as a few watts per square centimeter.« less
Advanced Thermionic Technology Program

NASA Technical Reports Server (NTRS)

1977-01-01

Topics include surface studies (surface theory, basic surface experiments, and activation chamber experiments); plasma studies (converter theory and enhanced mode conversion experiments); and component development (low temperature conversion experiments, high efficiency conversion experiments, and hot shell development).
Conversational Entrainment of Vocal Fry in Young Adult Female American English Speakers.

PubMed

Borrie, Stephanie A; Delfino, Christine R

2017-07-01

Conversational entrainment, the natural tendency for people to modify their behaviors to more closely match their communication partner, is examined as one possible mechanism modulating the prevalence of vocal fry in the speech of young American women engaged in spoken dialogue. Twenty young adult female American English speakers engaged in two spoken dialogue tasks-one with a young adult female American English conversational partner who exhibited substantial vocal fry and one with a young adult female American English conversational partner who exhibited quantifiably less vocal fry. Dialogues were analyzed for proportion of vocal fry, by speaker, and two measures of communicative success (efficiency and enjoyment). Participants employed significantly more vocal fry when conversing with the partner who exhibited substantial vocal fry than when conversing with the partner who exhibited quantifiably less vocal fry. Further, greater similarity between communication partners in their use of vocal fry tracked with higher scores of communicative efficiency and communicative enjoyment. Conversational entrainment offers a mechanistic framework that may be used to explain, to some degree, the frequency with which vocal fry is employed by young American women engaged in spoken dialogue. Further, young American women who modulated their vocal patterns during dialogue to match those of their conversational partner gained more efficiency and enjoyment from their interactions, demonstrating the cognitive and social benefits of entrainment. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
Design of batch audio/video conversion platform based on JavaEE

NASA Astrophysics Data System (ADS)

Cui, Yansong; Jiang, Lianpin

2018-03-01

With the rapid development of digital publishing industry, the direction of audio / video publishing shows the diversity of coding standards for audio and video files, massive data and other significant features. Faced with massive and diverse data, how to quickly and efficiently convert to a unified code format has brought great difficulties to the digital publishing organization. In view of this demand and present situation in this paper, basing on the development architecture of Sptring+SpringMVC+Mybatis, and combined with the open source FFMPEG format conversion tool, a distributed online audio and video format conversion platform with a B/S structure is proposed. Based on the Java language, the key technologies and strategies designed in the design of platform architecture are analyzed emphatically in this paper, designing and developing a efficient audio and video format conversion system, which is composed of “Front display system”, "core scheduling server " and " conversion server ". The test results show that, compared with the ordinary audio and video conversion scheme, the use of batch audio and video format conversion platform can effectively improve the conversion efficiency of audio and video files, and reduce the complexity of the work. Practice has proved that the key technology discussed in this paper can be applied in the field of large batch file processing, and has certain practical application value.
Lead-free inverted planar formamidinium tin triiodide perovskite solar cells achieving power conversion efficiencies up to 6.22%

DOE PAGES

Liao, Weiqiang; Zhao, Dewei; Yu, Yue; ...

2016-08-29

Efficient lead (Pb)-free inverted planar formamidinium tin triiodide (FASnI 3) perovskite solar cells (PVSCs) are demonstrated. Our FASnI 3 PVSCs achieved average power conversion efficiencies (PCEs) of 5.41% ± 0.46% and a maximum PCE of 6.22% under forward voltage scan. Here, the PVSCs exhibit small photocurrent–voltage hysteresis and high reproducibility. The champion cell shows a steady-state efficiency of ≈6.00% for over 100 s.
Thermodynamic limits to the conversion of blackbody radiation by quantum systems. [with application to solar energy conversion devices

NASA Technical Reports Server (NTRS)

Buoncristiani, A. M.; Smith, B. T.; Byvik, C. E.

1982-01-01

Using general thermodynamic arguments, we analyze the conversion of the energy contained in the radiation from a blackbody to useful work by a quantum system. We show that the energy available for conversion is bounded above by the change in free energy in the incident and reradiated fields and that this free energy change depends upon the temperature of the receiving device. Universal efficiency curves giving the ultimate thermodynamic conversion efficiency of the quantum system are presented in terms of the blackbody temperature and the temperature and threshold energy of the quantum system. Application of these results is made to a variety of systems including biological photosynthetic, photovoltaic, and photoelectrochemical systems.
Potential natural sensitizers extracted from the skin of Canarium odontophyllum fruits for dye-sensitized solar cells.

PubMed

Lim, Andery; Kumara, N T R N; Tan, Ai Ling; Mirza, Aminul Huq; Chandrakanthi, R L N; Petra, Mohammad Iskandar; Ming, Lim Chee; Senadeera, G K R; Ekanayake, Piyasiri

2015-03-05

Possibility of use of dye extract from skin samples of a seasonal, indigenous fruit from Borneo, namely Canarium odontophyllum, in dye sensitized solar cells (DSSCs) are explored. Three main groups of flavonoid pigments are detected and these pigments exhibit different UV-vis absorption properties, and hence showing different light harvesting capabilities. When applied in DSSCs. The detected pigment constituents of the extract consist of aurone (maritimein), anthocyanidin (pelargonidin) and anthocyanidin (cyanidin derivatives). When tested in DSSC, the highest conversion efficiency of 1.43% is exhibited by cyanidin derivatives, and this is followed by conversion efficiencies of 0.51% and 0.79% for aurone and pelargonidin, respectively. It is shown that individual pigments, like cyanidin derivatives and pelargonidin, exhibit higher power conversion efficiency when compared to that of C.odontophyllum skin pigment mixture (with a conversion efficiency of only 0.68%). The results indicate a possibility of masking effects of the pigments when used as a mixture. The acidification of C.odontophyllum skin pigments with concentrated hydrochloric acid improves the conversion efficiency of the mixture from 0.68% to 0.99%. The discussion in this paper will draw data and observations from the variation in absorption and adsorption properties, the HOMO-LUMO levels, the energy band gaps and the functional group compositions of the detected flavonoids. Copyright © 2014 Elsevier B.V. All rights reserved.
Efficient amplitude-modulated pulses for triple- to single-quantum coherence conversion in MQMAS NMR.

PubMed

Colaux, Henri; Dawson, Daniel M; Ashbrook, Sharon E

2014-08-07

The conversion between multiple- and single-quantum coherences is integral to many nuclear magnetic resonance (NMR) experiments of quadrupolar nuclei. This conversion is relatively inefficient when effected by a single pulse, and many composite pulse schemes have been developed to improve this efficiency. To provide the maximum improvement, such schemes typically require time-consuming experimental optimization. Here, we demonstrate an approach for generating amplitude-modulated pulses to enhance the efficiency of the triple- to single-quantum conversion. The optimization is performed using the SIMPSON and MATLAB packages and results in efficient pulses that can be used without experimental reoptimisation. Most significant signal enhancements are obtained when good estimates of the inherent radio-frequency nutation rate and the magnitude of the quadrupolar coupling are used as input to the optimization, but the pulses appear robust to reasonable variations in either parameter, producing significant enhancements compared to a single-pulse conversion, and also comparable or improved efficiency over other commonly used approaches. In all cases, the ease of implementation of our method is advantageous, particularly for cases with low sensitivity, where the improvement is most needed (e.g., low gyromagnetic ratio or high quadrupolar coupling). Our approach offers the potential to routinely improve the sensitivity of high-resolution NMR spectra of nuclei and systems that would, perhaps, otherwise be deemed "too challenging".
Efficient Amplitude-Modulated Pulses for Triple- to Single-Quantum Coherence Conversion in MQMAS NMR

PubMed Central

2014-01-01

The conversion between multiple- and single-quantum coherences is integral to many nuclear magnetic resonance (NMR) experiments of quadrupolar nuclei. This conversion is relatively inefficient when effected by a single pulse, and many composite pulse schemes have been developed to improve this efficiency. To provide the maximum improvement, such schemes typically require time-consuming experimental optimization. Here, we demonstrate an approach for generating amplitude-modulated pulses to enhance the efficiency of the triple- to single-quantum conversion. The optimization is performed using the SIMPSON and MATLAB packages and results in efficient pulses that can be used without experimental reoptimisation. Most significant signal enhancements are obtained when good estimates of the inherent radio-frequency nutation rate and the magnitude of the quadrupolar coupling are used as input to the optimization, but the pulses appear robust to reasonable variations in either parameter, producing significant enhancements compared to a single-pulse conversion, and also comparable or improved efficiency over other commonly used approaches. In all cases, the ease of implementation of our method is advantageous, particularly for cases with low sensitivity, where the improvement is most needed (e.g., low gyromagnetic ratio or high quadrupolar coupling). Our approach offers the potential to routinely improve the sensitivity of high-resolution NMR spectra of nuclei and systems that would, perhaps, otherwise be deemed “too challenging”. PMID:25047226
Bio-inspired cofacial Fe porphyrin dimers for efficient electrocatalytic CO2 to CO conversion: Overpotential tuning by substituents at the porphyrin rings

PubMed Central

Zahran, Zaki N.; Mohamed, Eman A.; Naruta, Yoshinori

2016-01-01

Efficient reduction of CO2 into useful carbon resources particularly CO is an essential reaction for developing alternate sources of fuels and for reducing the greenhouse effect of CO2. The binuclear Ni, Fe−containing carbon monoxide dehydrogenase (CODHs) efficiently catalyzes the reduction of CO2 to CO. The location of Ni and Fe at proper positions allows their cooperation for CO2 to CO conversion through a push−pull mechanism. Bio−inspired from CODHs, we used several cofacial porphyrin dimers with different substituents as suitable ligands for holding two Fe ions with suitable Fe−Fe separation distance to efficiently and selectively promote CO2 to CO conversion with high turnover frequencies, TOFs. The substituents on the porphyrin rings greatly affect the catalysis process. By introducing electron-withdrawing/-donating groups, e.g. electron-withdrawing perfluorophenyl, at all meso positions of the porphyrin rings, the catalysis overpotential, η was minimized by ≈0.3 V compared to that obtained by introducing electron-donating mesityl groups. The Fe porphyrin dimers among reported catalysts are the most efficient ones for CO2 to CO conversion. Control experiments indicate that the high performance of the current CO2 to CO conversion catalysts is due to the presence of binuclear Fe centers at suitable Fe−Fe separation distance. PMID:27087483
Bio-inspired cofacial Fe porphyrin dimers for efficient electrocatalytic CO2 to CO conversion: Overpotential tuning by substituents at the porphyrin rings.

PubMed

Zahran, Zaki N; Mohamed, Eman A; Naruta, Yoshinori

2016-04-18

Efficient reduction of CO2 into useful carbon resources particularly CO is an essential reaction for developing alternate sources of fuels and for reducing the greenhouse effect of CO2. The binuclear Ni, Fe-containing carbon monoxide dehydrogenase (CODHs) efficiently catalyzes the reduction of CO2 to CO. The location of Ni and Fe at proper positions allows their cooperation for CO2 to CO conversion through a push-pull mechanism. Bio-inspired from CODHs, we used several cofacial porphyrin dimers with different substituents as suitable ligands for holding two Fe ions with suitable Fe-Fe separation distance to efficiently and selectively promote CO2 to CO conversion with high turnover frequencies, TOFs. The substituents on the porphyrin rings greatly affect the catalysis process. By introducing electron-withdrawing/-donating groups, e.g. electron-withdrawing perfluorophenyl, at all meso positions of the porphyrin rings, the catalysis overpotential, η was minimized by ≈0.3 V compared to that obtained by introducing electron-donating mesityl groups. The Fe porphyrin dimers among reported catalysts are the most efficient ones for CO2 to CO conversion. Control experiments indicate that the high performance of the current CO2 to CO conversion catalysts is due to the presence of binuclear Fe centers at suitable Fe-Fe separation distance.
Bio-inspired cofacial Fe porphyrin dimers for efficient electrocatalytic CO2 to CO conversion: Overpotential tuning by substituents at the porphyrin rings

NASA Astrophysics Data System (ADS)

Zahran, Zaki N.; Mohamed, Eman A.; Naruta, Yoshinori

2016-04-01

Efficient reduction of CO2 into useful carbon resources particularly CO is an essential reaction for developing alternate sources of fuels and for reducing the greenhouse effect of CO2. The binuclear Ni, Fe-containing carbon monoxide dehydrogenase (CODHs) efficiently catalyzes the reduction of CO2 to CO. The location of Ni and Fe at proper positions allows their cooperation for CO2 to CO conversion through a push-pull mechanism. Bio-inspired from CODHs, we used several cofacial porphyrin dimers with different substituents as suitable ligands for holding two Fe ions with suitable Fe-Fe separation distance to efficiently and selectively promote CO2 to CO conversion with high turnover frequencies, TOFs. The substituents on the porphyrin rings greatly affect the catalysis process. By introducing electron-withdrawing/-donating groups, e.g. electron-withdrawing perfluorophenyl, at all meso positions of the porphyrin rings, the catalysis overpotential, η was minimized by ≈0.3 V compared to that obtained by introducing electron-donating mesityl groups. The Fe porphyrin dimers among reported catalysts are the most efficient ones for CO2 to CO conversion. Control experiments indicate that the high performance of the current CO2 to CO conversion catalysts is due to the presence of binuclear Fe centers at suitable Fe-Fe separation distance.
Energy conversion approaches and materials for high-efficiency photovoltaics.

PubMed

Green, Martin A; Bremner, Stephen P

2016-12-20

The past five years have seen significant cost reductions in photovoltaics and a correspondingly strong increase in uptake, with photovoltaics now positioned to provide one of the lowest-cost options for future electricity generation. What is becoming clear as the industry develops is that area-related costs, such as costs of encapsulation and field-installation, are increasingly important components of the total costs of photovoltaic electricity generation, with this trend expected to continue. Improved energy-conversion efficiency directly reduces such costs, with increased manufacturing volume likely to drive down the additional costs associated with implementing higher efficiencies. This suggests the industry will evolve beyond the standard single-junction solar cells that currently dominate commercial production, where energy-conversion efficiencies are fundamentally constrained by Shockley-Queisser limits to practical values below 30%. This Review assesses the overall prospects for a range of approaches that can potentially exceed these limits, based on ultimate efficiency prospects, material requirements and developmental outlook.
Molecular approaches to third generation photovoltaics: photochemical up-conversion

NASA Astrophysics Data System (ADS)

Cheng, Yuen Yap; Fückel, Burkhard; Roberts, Derrick A.; Khoury, Tony; Clady, Rapha"l. G. C. R.; Tayebjee, Murad J. Y.; Piper, Roland; Ekins-Daukes, N. J.; Crossley, Maxwell J.; Schmidt, Timothy W.

2010-08-01

We have investigated a photochemical up-conversion system comprising a molecular mixture of a palladium porphyrin to harvest light, and a polycyclic aromatic hydrocarbon to emit light. The energy of harvested photons is stored as molecular triplet states which then annihilate to bring about up-converted fluorescence. The limiting efficiency of such triplet-triplet annihilation up-conversion has been believed to be 11% for some time. However, by rigorously investigating the kinetics of delayed fluorescence following pulsed excitation, we demonstrate instantaneous annihilation efficiencies exceeding 40%, and limiting efficiencies for the current system of ~60%. We attribute the high efficiencies obtained to the electronic structure of the emitting molecule, which exhibits an exceptionally high T2 molecular state. We utilize the kinetic data obtained to model an up-converting layer irradiated with broadband sunlight, finding that ~3% efficiencies can be obtained with the current system, with this improving dramatically upon optimization of various parameters.
Integrating a dual-silicon photoelectrochemical cell into a redox flow battery for unassisted photocharging.

PubMed

Liao, Shichao; Zong, Xu; Seger, Brian; Pedersen, Thomas; Yao, Tingting; Ding, Chunmei; Shi, Jingying; Chen, Jian; Li, Can

2016-05-04

Solar rechargeable flow cells (SRFCs) provide an attractive approach for in situ capture and storage of intermittent solar energy via photoelectrochemical regeneration of discharged redox species for electricity generation. However, overall SFRC performance is restricted by inefficient photoelectrochemical reactions. Here we report an efficient SRFC based on a dual-silicon photoelectrochemical cell and a quinone/bromine redox flow battery for in situ solar energy conversion and storage. Using narrow bandgap silicon for efficient photon collection and fast redox couples for rapid interface charge injection, our device shows an optimal solar-to-chemical conversion efficiency of ∼5.9% and an overall photon-chemical-electricity energy conversion efficiency of ∼3.2%, which, to our knowledge, outperforms previously reported SRFCs. The proposed SRFC can be self-photocharged to 0.8 V and delivers a discharge capacity of 730 mAh l(-1). Our work may guide future designs for highly efficient solar rechargeable devices.
Efficient diode-end-pumped actively Q-switched Nd:YAG/SrWO4/KTP yellow laser.

PubMed

Cong, Zhenhua; Zhang, Xingyu; Wang, Qingpu; Liu, Zhaojun; Li, Shutao; Chen, Xiaohan; Zhang, Xiaolei; Fan, Shuzhen; Zhang, Huaijin; Tao, Xutang

2009-09-01

An efficient intracavity frequency-doubled Raman laser was obtained by using an SrWO(4) Raman medium, an Nd:YAG ceramic gain medium, and a KTP frequency-doubling medium. Three laser cavities, including a two-mirror cavity, a three-mirror coupled cavity, and a folded cavity, were investigated. With the coupled cavity, a 2.93 W, 590 nm laser was obtained at an incident pump power of 16.2 W and a pulse repetition frequency of 20 kHz; the corresponding conversion efficiency was 18.1%. The highest conversion efficiency of 19.2% was obtained at an incident pump power of 14.1 W and a pulse repetition frequency of 15 kHz. The obtained maximum output power and conversion efficiency were much higher than the results previously obtained with intracavity frequency-doubled solid-state Raman lasers.

Broadband high-efficiency half-wave plate: a supercell-based plasmonic metasurface approach.

PubMed

Ding, Fei; Wang, Zhuoxian; He, Sailing; Shalaev, Vladimir M; Kildishev, Alexander V

2015-04-28

We design, fabricate, and experimentally demonstrate an ultrathin, broadband half-wave plate in the near-infrared range using a plasmonic metasurface. The simulated results show that the linear polarization conversion efficiency is over 97% with over 90% reflectance across an 800 nm bandwidth. Moreover, simulated and experimental results indicate that such broadband and high-efficiency performance is also sustained over a wide range of incident angles. To further obtain a background-free half-wave plate, we arrange such a plate as a periodic array of integrated supercells made of several plasmonic antennas with high linear polarization conversion efficiency, consequently achieving a reflection-phase gradient for the cross-polarized beam. In this design, the anomalous (cross-polarized) and the normal (copolarized) reflected beams become spatially separated, hence enabling highly efficient and robust, background-free polarization conversion along with broadband operation. Our results provide strategies for creating compact, integrated, and high-performance plasmonic circuits and devices.
Solid polymeric electrolyte based dye-sensitized solar cell with improved stability

NASA Astrophysics Data System (ADS)

Prasad, Narottam; Kumar, Manish; Patel, K. R.; Roy, M. S.

2018-05-01

The impact of polymeric electrolyte was investigated over the performance of dye-sensitized solar cell made with Rose Bengal as sensitizer. Further, the selective influence of TiCl4 treatment and pre-sensitizer deoxycholic acid on nc-TiO2 photoanode was determined in terms of improvement in conversion efficiency of the cell. It is found that the effect of TiCl4 treatment was comparatively more than pre-sensitization with de-oxy cholic acid towards improving the efficiency of the cell. The conversion efficiency on TiCl4 treatment was 0.2% whereas on pre-sensitization with deoxy chollic acid it was 0.1%. The combined effect of both TiCl4 treatment & pre-sensitization with deoxycholic acid leads conversion efficiency to 0.33%.
High Photoelectric Conversion Efficiency of Metal Phthalocyanine/Fullerene Heterojunction Photovoltaic Device

PubMed Central

Lin, Chi-Feng; Zhang, Mi; Liu, Shun-Wei; Chiu, Tien-Lung; Lee, Jiun-Haw

2011-01-01

This paper introduces the fundamental physical characteristics of organic photovoltaic (OPV) devices. Photoelectric conversion efficiency is crucial to the evaluation of quality in OPV devices, and enhancing efficiency has been spurring on researchers to seek alternatives to this problem. In this paper, we focus on organic photovoltaic (OPV) devices and review several approaches to enhance the energy conversion efficiency of small molecular heterojunction OPV devices based on an optimal metal-phthalocyanine/fullerene (C60) planar heterojunction thin film structure. For the sake of discussion, these mechanisms have been divided into electrical and optical sections: (1) Electrical: Modification on electrodes or active regions to benefit carrier injection, charge transport and exciton dissociation; (2) Optical: Optional architectures or infilling to promote photon confinement and enhance absorption. PMID:21339999
Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing

NASA Astrophysics Data System (ADS)

Lu, Yichen; Lyu, Hongming; Richardson, Andrew G.; Lucas, Timothy H.; Kuzum, Duygu

2016-09-01

Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In in vivo experiments with rodents, same array is used to sense brain activity patterns with high spatio-temporal resolution and to control leg muscles with high-precision electrical stimulation from the cortical surface. Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial.
Non-phase-matched enhancement of second-harmonic generation in multilayer nonlinear structures with internal reflections.

PubMed

Centini, Marco; D'Aguanno, Giuseppe; Sciscione, Letizia; Sibilia, Concita; Bertolotti, Mario; Scalora, Michael; Bloemer, Mark J

2004-08-15

Traditional notions of second-harmonic generation rely on phase matching or quasi phase matching to achieve good conversion efficiencies. We present an entirely new concept for efficient second-harmonic generation that is based on the interference of counterpropagating waves in multilayer structures. Conversion efficiencies are an order of magnitude larger than with phase-matched second-harmonic generation in similar multilayer structures.
Intelligence related upper alpha desynchronization in a semantic memory task.

PubMed

Doppelmayr, M; Klimesch, W; Hödlmoser, K; Sauseng, P; Gruber, W

2005-07-30

Recent evidence shows that event-related (upper) alpha desynchronization (ERD) is related to cognitive performance. Several studies observed a positive, some a negative relationship. The latter finding, interpreted in terms of the neural efficiency hypothesis, suggests that good performance is associated with a more 'efficient', smaller extent of cortical activation. Other studies found that ERD increases with semantic processing demands and that this increase is larger for good performers. Studies supporting the neural efficiency hypothesis used tasks that do not specifically require semantic processing. Thus, we assume that the lack of semantic processing demands may at least in part be responsible for the reduced ERD. In the present study we measured ERD during a difficult verbal-semantic task. The findings demonstrate that during semantic processing, more intelligent (as compared to less intelligent) subjects exhibited a significantly larger upper alpha ERD over the left hemisphere. We conclude that more intelligent subjects exhibit a more extensive activation in a semantic processing system and suggest that divergent findings regarding the neural efficiency hypotheses are due to task specific differences in semantic processing demands.
High-power 671 nm laser by second-harmonic generation with 93% efficiency in an external ring cavity.

PubMed

Cui, Xing-Yang; Shen, Qi; Yan, Mei-Chen; Zeng, Chao; Yuan, Tao; Zhang, Wen-Zhuo; Yao, Xing-Can; Peng, Cheng-Zhi; Jiang, Xiao; Chen, Yu-Ao; Pan, Jian-Wei

2018-04-15

Second-harmonic generation (SHG) is useful for obtaining single-frequency continuous-wave laser sources at various wavelengths for applications ranging from biology to fundamental physics. Using an external power-enhancement cavity is an effective approach to improve the frequency conversion efficiency. However, thermal effects limit the efficiency, particularly, in high-power operation. Therefore, reducing thermal effects is important when designing a cavity. This Letter reports the use of an external ring cavity for SHG, yielding a 5.2 W, 671 nm laser light with a conversion efficiency of 93.8±0.8% which, to the best of our knowledge, is a new record of conversion efficiency for an external ring cavity. It is achieved using a 10 mm length periodically poled potassium titanyl phosphate crystal and a 65 μm radius beam waist in the cavity so as to minimize thermal dephasing and thermal lensing. Furthermore, a method is developed to determine a conversion efficiency more accurately based on measuring the pump depletion using a photodiode detector and a maximum pump depletion up to 97% is recorded. In this method, the uncertainty is much less than that achieved in a common method by direct measuring with a power meter.
A Novel Oscillating Rectenna for Wireless Microwave Power Transmission

NASA Technical Reports Server (NTRS)

McSpadden, J. O.; Dickinson, R. M.; Fan, L.; Chang, K.

1998-01-01

A new concept for solid state wireless microwave power transmission is presented. A 2.45 GHz rectenna element that was designed for over 85% RF to dc power conversion efficiency has been used to oscillate at 3.3 GHz with an approximate 1% dc to RF conversion efficiency.
Rational construction of a stable Zn4O-based MOF for highly efficient CO2 capture and conversion.

PubMed

Zhou, Hui-Fang; Liu, Bo; Hou, Lei; Zhang, Wen-Yan; Wang, Yao-Yu

2018-01-11

By employing a carboxylate ligand derived from benzene-1,4-dicarboxylate, a chemically stable Zn 4 O-based self-penetrating metal-organic framework has been rationally synthesized, which exhibits high CO 2 adsorption and efficient catalytic conversion for CO 2 cycloaddition.
Suppression of Tla1 gene expression for improved solar conversion efficiency and photosynthetic productivity in plants and algae

DOEpatents

Melis, Anastasios; Mitra, Mautusi

2010-06-29

The invention provides method and compositions to minimize the chlorophyll antenna size of photosynthesis by decreasing TLA1 gene expression, thereby improving solar conversion efficiencies and photosynthetic productivity in plants, e.g., green microalgae, under bright sunlight conditions.
Evaluating Energy Conversion Efficiency

NASA Technical Reports Server (NTRS)

Byvik, C. E.; Smith, B. T.; Buoncristiani, A. M.

1983-01-01

Devices that convert solar radiation directly into storable chemical or electrical energy, have characteristic energy absorption spectrum; specifically, each of these devices has energy threshold. The conversion efficiency of generalized system that emcompasses all threshold devices is analyzed, resulting in family of curves for devices of various threshold energies operating at different temperatures.
Emotional System for Military Target Identification

DTIC Science & Technology

2009-10-01

algorithm [23], and used it to solve a facial recognition problem. In other works [24,25], we explored the potential of using emotional neural...other application areas, such as security ( facial recognition ) and medical (blood cell identification), can be also efficiently used in military...Application of an emotional neural network to facial recognition . Neural Computing and Applications, 18(4), 309-320. [25] Khashman, A. (2009). Blood cell
[Ecological management model of agriculture-pasture ecotone based on the theory of energy and material flow--a case study in Houshan dryland area of Inner Mongolia].

PubMed

Fan, Jinlong; Pan, Zhihua; Zhao, Ju; Zheng, Dawei; Tuo, Debao; Zhao, Peiyi

2004-04-01

The degradation of ecological environment in the agriculture-pasture ecotone in northern China has been paid more attentions. Based on our many years' research and under the guide of energy and material flow theory, this paper put forward an ecological management model, with a hill as the basic cell and according to the natural, social and economic characters of Houshan dryland farming area inside the north agriculture-pasture ecotone. The input and output of three models, i.e., the traditional along-slope-tillage model, the artificial grassland model and the ecological management model, were observed and recorded in detail in 1999. Energy and material flow analysis based on field test showed that compared with traditional model, ecological management model could increase solar use efficiency by 8.3%, energy output by 8.7%, energy conversion efficiency by 19.4%, N output by 26.5%, N conversion efficiency by 57.1%, P output by 12.1%, P conversion efficiency by 45.0%, and water use efficiency by 17.7%. Among the models, artificial grassland model had the lowest solar use efficiency, energy output and energy conversion efficiency; while the ecological management model had the most outputs and benefits, was the best model with high economic effect, and increased economic benefits by 16.1%, compared with the traditional model.
Energy Conversion Alternatives Study (ECAS), Westinghouse phase 1. Volume 5: Combined gas-steam turbine cycles. [energy conversion efficiency in electric power plants

NASA Technical Reports Server (NTRS)

Amos, D. J.; Foster-Pegg, R. W.; Lee, R. M.

1976-01-01

The energy conversion efficiency of gas-steam turbine cycles was investigated for selected combined cycle power plants. Results indicate that it is possible for combined cycle gas-steam turbine power plants to have efficiencies several point higher than conventional steam plants. Induction of low pressure steam into the steam turbine is shown to improve the plant efficiency. Post firing of the boiler of a high temperature combined cycle plant is found to increase net power but to worsen efficiency. A gas turbine pressure ratio of 12 to 1 was found to be close to optimum at all gas turbine inlet temperatures that were studied. The coal using combined cycle plant with an integrated low-Btu gasifier was calculated to have a plant efficiency of 43.6%, a capitalization of $497/kW, and a cost of electricity of 6.75 mills/MJ (24.3 mills/kwh). This combined cycle plant should be considered for base load power generation.
Design and modeling of an SJ infrared solar cell approaching upper limit of theoretical efficiency

NASA Astrophysics Data System (ADS)

Sahoo, G. S.; Mishra, G. P.

2018-01-01

Recent trends of photovoltaics account for the conversion efficiency limit making them more cost effective. To achieve this we have to leave the golden era of silicon cell and make a path towards III-V compound semiconductor groups to take advantages like bandgap engineering by alloying these compounds. In this work we have used a low bandgap GaSb material and designed a single junction (SJ) cell with a conversion efficiency of 32.98%. SILVACO ATLAS TCAD simulator has been used to simulate the proposed model using both Ray Tracing and Transfer Matrix Method (under 1 sun and 1000 sun of AM1.5G spectrum). A detailed analyses of photogeneration rate, spectral response, potential developed, external quantum efficiency (EQE), internal quantum efficiency (IQE), short-circuit current density (JSC), open-circuit voltage (VOC), fill factor (FF) and conversion efficiency (η) are discussed. The obtained results are compared with previously reported SJ solar cell reports.
Direct solar-to-hydrogen conversion via inverted metamorphic multi-junction semiconductor architectures

DOE PAGES

Young, James L.; Steiner, Myles A.; Döscher, Henning; ...

2017-03-13

Solar water splitting via multi-junction semiconductor photoelectrochemical cells provides direct conversion of solar energy to stored chemical energy as hydrogen bonds. Economical hydrogen production demands high conversion efficiency to reduce balance-of-systems costs. For sufficient photovoltage, water-splitting efficiency is proportional to the device photocurrent, which can be tuned by judicious selection and integration of optimal semiconductor bandgaps. Here, we demonstrate highly efficient, immersed water-splitting electrodes enabled by inverted metamorphic epitaxy and a transparent graded buffer that allows the bandgap of each junction to be independently varied. Voltage losses at the electrolyte interface are reduced by 0.55 V over traditional, uniformly p-dopedmore » photocathodes by using a buried p-n junction. Lastly, advanced on-sun benchmarking, spectrally corrected and validated with incident photon-to-current efficiency, yields over 16% solar-to-hydrogen efficiency with GaInP/GaInAs tandem absorbers, representing a 60% improvement over the classical, high-efficiency tandem III-V device.« less
Efficiency Enhancement of Hybrid Perovskite Solar Cells with MEH-PPV Hole-Transporting Layers

PubMed Central

Chen, Hsin-Wei; Huang, Tzu-Yen; Chang, Ting-Hsiang; Sanehira, Yoshitaka; Kung, Chung-Wei; Chu, Chih-Wei; Ikegami, Masashi; Miyasaka, Tsutomu; Ho, Kuo-Chuan

2016-01-01

In this study, hybrid perovskite solar cells are fabricated using poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) and poly(3-hexylthiophene-2,5-diyl) (P3HT) as dopant-free hole-transporting materials (HTMs), and two solution processes (one- and two-step methods, respectively) for preparing methylammonium lead iodide perovskite. By optimizing the concentrations and solvents of MEH-PPV solutions, a power conversion efficiency of 9.65% with hysteresis-less performance is achieved, while the device with 2,2′,7,7′-tetrakis(N,N-di-p-methoxyphenylamine)-9,9′spirobifluorene (Spiro-OMeTAD) doped with lithium salts and tert-butylpyridine (TBP) exhibits an efficiency of 13.38%. This result shows that non-doped MEH-PPV is a suitable, low-cost HTM for efficient polymer-based perovskite solar cells. The effect of different morphologies of methylammonium lead iodide perovskite on conversion efficiency is also investigated by incident photon-to-electron conversion efficiency (IPCE) curves and electrochemical impedance spectroscopy (EIS). PMID:27698464
Conversion efficiency limits and bandgap designs for multi-junction solar cells with internal radiative efficiencies below unity.

PubMed

Zhu, Lin; Mochizuki, Toshimitsu; Yoshita, Masahiro; Chen, Shaoqiang; Kim, Changsu; Akiyama, Hidefumi; Kanemitsu, Yoshihiko

2016-05-16

We calculated the conversion-efficiency limit ηsc and the optimized subcell bandgap energies of 1 to 5 junction solar cells without and with intermediate reflectors under 1-sun AM1.5G and 1000-sun AM1.5D irradiations, particularly including the impact of internal radiative efficiency (ηint) below unity for realistic subcell materials on the basis of an extended detailed-balance theory. We found that the conversion-efficiency limit ηsc significantly drops when the geometric mean ηint* of all subcell ηint in the stack reduces from 1 to 0.1, and that ηsc degrades linearly to logηint* for ηint* below 0.1. For ηint*<0.1 differences in ηsc due to additional intermediate reflectors became very small if all subcells are optically thick for sun light. We obtained characteristic optimized bandgap energies, which reflect both ηint* decrease and AM1.5 spectral gaps. These results provide realistic efficiency targets and design principles.
Direct solar-to-hydrogen conversion via inverted metamorphic multi-junction semiconductor architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, James L.; Steiner, Myles A.; Döscher, Henning

Solar water splitting via multi-junction semiconductor photoelectrochemical cells provides direct conversion of solar energy to stored chemical energy as hydrogen bonds. Economical hydrogen production demands high conversion efficiency to reduce balance-of-systems costs. For sufficient photovoltage, water-splitting efficiency is proportional to the device photocurrent, which can be tuned by judicious selection and integration of optimal semiconductor bandgaps. Here, we demonstrate highly efficient, immersed water-splitting electrodes enabled by inverted metamorphic epitaxy and a transparent graded buffer that allows the bandgap of each junction to be independently varied. Voltage losses at the electrolyte interface are reduced by 0.55 V over traditional, uniformly p-dopedmore » photocathodes by using a buried p-n junction. Lastly, advanced on-sun benchmarking, spectrally corrected and validated with incident photon-to-current efficiency, yields over 16% solar-to-hydrogen efficiency with GaInP/GaInAs tandem absorbers, representing a 60% improvement over the classical, high-efficiency tandem III-V device.« less
Kinetic modeling of cellulosic biomass to ethanol via simultaneous saccharification and fermentation: Part I. Accommodation of intermittent feeding and analysis of staged reactors.

PubMed

Shao, Xiongjun; Lynd, Lee; Wyman, Charles; Bakker, André

2009-01-01

The model of South et al. [South et al. (1995) Enzyme Microb Technol 17(9): 797-803] for simultaneous saccharification of fermentation of cellulosic biomass is extended and modified to accommodate intermittent feeding of substrate and enzyme, cascade reactor configurations, and to be more computationally efficient. A dynamic enzyme adsorption model is found to be much more computationally efficient than the equilibrium model used previously, thus increasing the feasibility of incorporating the kinetic model in a computational fluid dynamic framework in the future. For continuous or discretely fed reactors, it is necessary to use particle conversion in conversion-dependent hydrolysis rate laws rather than reactor conversion. Whereas reactor conversion decreases due to both reaction and exit of particles from the reactor, particle conversion decreases due to reaction only. Using the modified models, it is predicted that cellulose conversion increases with decreasing feeding frequency (feedings per residence time, f). A computationally efficient strategy for modeling cascade reactors involving a modified rate constant is shown to give equivalent results relative to an exhaustive approach considering the distribution of particles in each successive fermenter.

Decomposing Fuel Economy and Greenhouse Gas Regulatory Standards in the Energy Conversion Efficiency and Tractive Energy Domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pannone, Greg; Thomas, John F; Reale, Michael

The three foundational elements that determine mobile source energy use and tailpipe carbon dioxide (CO2) emissions are the tractive energy requirements of the vehicle, the on-cycle energy conversion efficiency of the propulsion system, and the energy source. The tractive energy requirements are determined by the vehicle's mass, aerodynamic drag, tire rolling resistance, and parasitic drag. Oncycle energy conversion of the propulsion system is dictated by the tractive efficiency, non-tractive energy use, kinetic energy recovery, and parasitic losses. The energy source determines the mobile source CO2 emissions. For current vehicles, tractive energy requirements and overall energy conversion efficiency are readily availablemore » from the decomposition of test data. For future applications, plausible levels of mass reduction, aerodynamic drag improvements, and tire rolling resistance can be transposed into the tractive energy domain. Similarly, by combining thermodynamic, mechanical efficiency, and kinetic energy recovery fundamentals with logical proxies, achievable levels of energy conversion efficiency can be established to allow for the evaluation of future powertrain requirements. Combining the plausible levels of tractive energy and on-cycle efficiency provides a means to compute sustainable vehicle and propulsion system scenarios that can achieve future regulations. Using these principles, the regulations established in the United States (U.S.) for fuel consumption and CO2 emissions are evaluated. Fleet-level scenarios are generated and compared to the technology deployment assumptions made during rule-making. When compared to the rule-making assumptions, the results indicate that a greater level of advanced vehicle and propulsion system technology deployment will be required to achieve the model year 2025 U.S. standards for fuel economy and CO2 emissions.« less
Neural Correlates of Irony Comprehension: The Role of Schizotypal Personality Traits

ERIC Educational Resources Information Center

Rapp, A. M.; Mutschler, D. E.; Wild, B.; Erb, M.; Lengsfeld, I.; Saura, R.; Grodd, W.

2010-01-01

To detect that a conversational turn is intended to be ironic is a difficult challenge in everyday language comprehension. Most authors suggested a theory of mind deficit is crucial for irony comprehension deficits in psychiatric disorders like schizophrenia; however, the underlying pathophysiology and neurobiology are unknown and recent research…
Polymer bulk heterojunction solar cells with PEDOT:PSS bilayer structure as hole extraction layer.

PubMed

Kim, Wanjung; Kim, Namhun; Kim, Jung Kyu; Park, Insun; Choi, Yeong Suk; Wang, Dong Hwan; Chae, Heeyeop; Park, Jong Hyeok

2013-06-01

A high current density obtained in a limited, nanometer-thick region is important for high efficiency polymer solar cells (PSCs). The conversion of incident photons to charge carriers only occurs in confined active layers; therefore, charge-carrier extraction from the active layer within the device by using solar light has an important impact on the current density and the related to power conversion efficiency. In this study, we observed a surprising result, that is, extracting the charge carrier generated in the active layer of a PSC device, with a thickness-controlled PEDOT:PSS bilayer that acted as a hole extraction layer (HEL), yielded a dramatically improved power conversion efficiency in two different model systems (P3HT:PC₆₀BM and PCDTBT:PC₇₀BM). To understand this phenomenon, we conducted optical strength simulation, photocurrent-voltage measurements, incident photon to charge carrier efficiency measurements, ultraviolet photoelectron spectroscopy, and AFM studies. The results revealed that approximately 60 nm was the optimum PEDOT:PSS bilayer HEL thickness in PSCs for producing the maximum power conversion efficiency. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Evaluation of saw damage using diamond-coated wire in crystalline silicon solar cells by photoluminescence imaging

NASA Astrophysics Data System (ADS)

Kinoshita, Kosuke; Kojima, Takuto; Suzuki, Ryota; Kawatsu, Tomoyuki; Nakamura, Kyotaro; Ohshita, Yoshio; Ogura, Atsushi

2018-05-01

Si ingots were sliced using a diamond-coated wire, and saw damage was observed even after damage removal etching and texturization. Since invisible microscopic damage was observed only under uncontrolled slice conditions, such damage was identified as saw damage. The wafers with saw damage exhibited the degradation of solar cell conversion efficiency (approximately 1–2% absolute). The results of external quantum efficiency (EQE) measurements showed a slight deterioration of EQE in the short wavelength region. Current–voltage characteristic measurements showed similar results that agreed with the EQE measurement results. In addition, EQE mapping measurements were carried out at various irradiation wavelengths between 350 and 1150 nm. Areas with dark contrasts in EQE mapping correspond to saw damage. In the cells with a low conversion efficiency, both EQE mapping and PL images exhibited dark areas and lines. On the other hand, in the cells with a high conversion efficiency, a uniform distribution of saw damage was observed even with the saw damage in the PL images. We believe that sophisticated control to suppress saw damage during sawing is required to realize higher conversion efficiency solar cells in the future.
Numerical investigation of output beam quality in efficient broadband optical parametric chirped pulse amplification

NASA Astrophysics Data System (ADS)

Liu, Xiao-Di; Xu, Lu; Liang, Xiao-Yan

2017-01-01

We theoretically analyzed output beam quality of broad bandwidth non-collinear optical parametric chirped pulse amplification (NOPCPA) in LiB3O5 (LBO) centered at 800 nm. With a three-dimensional numerical model, the influence of the pump intensity, pump and signal spatial modulations, and the walk-off effect on the OPCPA output beam quality are presented, together with conversion efficiency and the gain spectrum. The pump modulation is a dominant factor that affects the output beam quality. Comparatively, the influence of signal modulation is insignificant. For a low-energy system with small beam sizes, walk-off effect has to be considered. Pump modulation and walk-off effect lead to asymmetric output beam profile with increased modulation. A special pump modulation type is found to optimize output beam quality and efficiency. For a high-energy system with large beam sizes, the walk-off effect can be neglected, certain back conversion is beneficial to reduce the output modulation. A trade-off must be made between the output beam quality and the conversion efficiency, especially when the pump modulation is large since. A relatively high conversion efficiency and a low output modulation are both achievable by controlling the pump modulation and intensity.
Bi2S3microspheres grown on graphene sheets as low-cost counter-electrode materials for dye-sensitized solar cells.

PubMed

Li, Guang; Chen, Xiaoshuang; Gao, Guandao

2014-03-21

In this work, we synthesized 3D Bi2S3 microspheres comprised of nanorods grown along the (211) facet on graphene sheets by a solvothermal route, and investigated its catalytic activities through I-V curves and conversion efficiency tests as the CE in DSSCs. Although the (211) facet has a large band gap for a Bi2S3 semiconductor, owing to the introduction of graphene into the system, its short-circuit current density, open-circuit voltage, fill factor, and efficiency were Jsc = 12.2 mA cm(-2), Voc = 0.75 V, FF = 0.60, and η = 5.5%, respectively. By integrating it with graphene sheets, our material achieved the conversion efficiency of 5.5%, which is almost triple the best conversion efficiency value of the DSSCs with (211)-faceted 3D Bi2S3 without graphene (1.9%) reported in the latest literature. Since this conversion-efficient 3D material grown on the graphene sheets significantly improves its catalytic properties, it paves the way for designing and applying low-cost Pt-free CE materials in DSSC from inorganic nanostructures.
Large-scale cauliflower-shaped hierarchical copper nanostructures for efficient photothermal conversion.

PubMed

Fan, Peixun; Wu, Hui; Zhong, Minlin; Zhang, Hongjun; Bai, Benfeng; Jin, Guofan

2016-08-14

Efficient solar energy harvesting and photothermal conversion have essential importance for many practical applications. Here, we present a laser-induced cauliflower-shaped hierarchical surface nanostructure on a copper surface, which exhibits extremely high omnidirectional absorption efficiency over a broad electromagnetic spectral range from the UV to the near-infrared region. The measured average hemispherical absorptance is as high as 98% within the wavelength range of 200-800 nm, and the angle dependent specular reflectance stays below 0.1% within the 0-60° incident angle. Such a structured copper surface can exhibit an apparent heating up effect under the sunlight illumination. In the experiment of evaporating water, the structured surface yields an overall photothermal conversion efficiency over 60% under an illuminating solar power density of ∼1 kW m(-2). The presented technology provides a cost-effective, reliable, and simple way for realizing broadband omnidirectional light absorptive metal surfaces for efficient solar energy harvesting and utilization, which is highly demanded in various light harvesting, anti-reflection, and photothermal conversion applications. Since the structure is directly formed by femtosecond laser writing, it is quite suitable for mass production and can be easily extended to a large surface area.
Rectenna session: Micro aspects. [energy conversion

NASA Technical Reports Server (NTRS)

Gutmann, R. J.

1980-01-01

Two micro aspects of the rectenna design are addressed: evaluation of the degradation in net rectenna RF to DC conversion efficiency due to power density variations across the rectenna (power combining analysis) and design of Yagi-Uda receiving elements to reduce rectenna cost by decreasing the number of conversion circuits (directional receiving elements). The first of these micro aspects involves resolving a fundamental question of efficiency potential with a rectenna, while the second involves a design modification with a large potential cost saving.
High efficiency thermal to electric energy conversion using selective emitters and spectrally tuned solar cells

NASA Technical Reports Server (NTRS)

Chubb, Donald L.; Flood, Dennis J.; Lowe, Roland A.

1992-01-01

Thermophotovoltaic (TPV) systems are attractive possibilities for direct thermal-to-electric energy conversion, but have typically required the use of black body radiators operating at high temperatures. Recent advances in both the understanding and performance of solid rare-earth oxide selective emitters make possible the use of TPV at temperatures as low as 1500 K. Depending on the nature of parasitic losses, overall thermal-to-electric conversion efficiencies greater than 20 percent are feasible.
Thermophotovoltaic conversion using selective infrared line emitters and large band gap photovoltaic devices

DOEpatents

Brandhorst, Jr., Henry W.; Chen, Zheng

2000-01-01

Efficient thermophotovoltaic conversion can be performed using photovoltaic devices with a band gap in the 0.75-1.4 electron volt range, and selective infrared emitters chosen from among the rare earth oxides which are thermally stimulated to emit infrared radiation whose energy very largely corresponds to the aforementioned band gap. It is possible to use thermovoltaic devices operating at relatively high temperatures, up to about 300.degree. C., without seriously impairing the efficiency of energy conversion.
Megawatt level UV output from [110] Cr⁴⁺:YAG passively Q-switched microchip laser.

PubMed

Bhandari, Rakesh; Taira, Takunori

2011-11-07

Recent development of megawatt peak power, giant pulse microchip lasers has opened new opportunities for efficient wavelength conversion, provided the output of the microchip laser is linearly polarized. We obtain > 2 MW peak power, 260 ps, 100 Hz pulses at 266 nm by fourth harmonic conversion of a linearly polarized Nd:YAG microchip laser that is passively Q-switched with [110] cut Cr⁴⁺:YAG. The SHG and FHG conversion efficiencies are 85% and 51%, respectively.
Efficient biological conversion of carbon monoxide (CO) to carbon dioxide (CO2) and for utilization in bioplastic production by Ralstonia eutropha through the display of an enzyme complex on the cell surface.

PubMed

Hyeon, Jeong Eun; Kim, Seung Wook; Park, Chulhwan; Han, Sung Ok

2015-06-25

An enzyme complex for biological conversion of CO to CO2 was anchored on the cell surface of the CO2-utilizing Ralstonia eutropha and successfully resulted in a 3.3-fold increase in conversion efficiency. These results suggest that this complexed system may be a promising strategy for CO2 utilization as a biological tool for the production of bioplastics.
Differential theory of learning for efficient neural network pattern recognition

NASA Astrophysics Data System (ADS)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-09-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.
Differential theory of learning for efficient neural network pattern recognition

NASA Astrophysics Data System (ADS)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-08-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generalize well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.
Improvement of force factor of magnetostrictive vibration power generator for high efficiency

NASA Astrophysics Data System (ADS)

Kita, Shota; Ueno, Toshiyuki; Yamada, Sotoshi

2015-05-01

We develop high power magnetostrictive vibration power generator for battery-free wireless electronics. The generator is based on a cantilever of parallel beam structure consisting of coil-wound Galfenol and stainless plates with permanent magnet for bias. Oscillating force exerted on the tip bends the cantilever in vibration yields stress variation of Galfenol plate, which causes flux variation and generates voltage on coil due to the law of induction. This generator has advantages over conventional, such as piezoelectric or moving magnet types, in the point of high efficiency, highly robust, and low electrical impedance. Our concern is the improvement of energy conversion efficiency dependent on the dimension. Especially, force factor, the conversion ratio of the electromotive force (voltage) on the tip velocity in vibration, has an important role in energy conversion process. First, the theoretical value of the force factor is formulated and then the validity was verified by experiments, where we compare four types of prototype with parameters of the dimension using 7.0 × 1.5 × 50 mm beams of Galfenol with 1606-turn wound coil. In addition, the energy conversion efficiency of the prototypes depending on load resistance was measured. The most efficient prototype exhibits the maximum instantaneous power of 0.73 W and energy of 4.7 mJ at a free vibration of frequency of 202 Hz in the case of applied force is 25 N. Further, it was found that energy conversion efficiency depends not only on the force factor but also on the damping (mechanical loss) of the vibration.
Energy Conversion Alternatives Study (ECAS), General Electric Phase 1. Volume 1: Executive summary. [using coal or coal derived fuels

NASA Technical Reports Server (NTRS)

Corman, J. C.

1976-01-01

A data base for the comparison of advanced energy conversion systems for utility applications using coal or coal-derived fuels was developed. Estimates of power plant performance (efficiency), capital cost, cost of electricity, natural resource requirements, and environmental intrusion characteristics were made for ten advanced conversion systems. Emphasis was on the energy conversion system in the context of a base loaded utility power plant. All power plant concepts were premised on meeting emission standard requirements. A steam power plant (3500 psig, 1000 F) with a conventional coal-burning furnace-boiler was analyzed as a basis for comparison. Combined cycle gas/steam turbine system results indicated competitive efficiency and a lower cost of electricity compared to the reference steam plant. The Open-Cycle MHD system results indicated the potential for significantly higher efficiency than the reference steam plant but with a higher cost of electricity.
Conversion of far ultraviolet to visible radiation: absolute measurements of the conversion efficiency of tetraphenyl butadiene

NASA Astrophysics Data System (ADS)

Vest, Robert E.; Coplan, Michael A.; Clark, Charles W.

Far ultraviolet (FUV) scintillation of noble gases is used in dark matter and neutrino research and in neutron detection. Upon collisional excitation, noble gas atoms recombine into excimer molecules that decay by FUV emission. Direct detection of FUV is difficult. Another approach is to convert it to visible light using a wavelength-shifting medium. One such medium, tetraphenyl butadiene (TPB) can be vapor-deposited on substrates. Thus the quality of thin TPB films can be tightly controlled. We have measured the absolute efficiency of FUV-to-visible conversion by 1 μm-thick TPB films vs. FUV wavelengths between 130 and 300 nm, with 1 nm resolution. The energy efficiency of FUV to visible conversion varies between 1% and 5%. We make comparisons with other recent results. Work performed at the NIST SURF III Synchrotron Ultraviolet Radiation Facility,.
High-Efficiency Artificial Photosynthesis Using a Novel Alkaline Membrane Cell

NASA Technical Reports Server (NTRS)

Narayan, Sri; Haines, Brennan; Blosiu, Julian; Marzwell, Neville

2009-01-01

A new cell designed to mimic the photosynthetic processes of plants to convert carbon dioxide into carbonaceous products and oxygen at high efficiency, has an improved configuration using a polymer membrane electrolyte and an alkaline medium. This increases efficiency of the artificial photosynthetic process, achieves high conversion rates, permits the use of inexpensive catalysts, and widens the range of products generated by this type of process. The alkaline membrane electrolyte allows for the continuous generation of sodium formate without the need for any additional separation system. The electrolyte type, pH, electrocatalyst type, and cell voltage were found to have a strong effect on the efficiency of conversion of carbon dioxide to formate. Indium electrodes were found to have higher conversion efficiency compared to lead. Bicarbonate electrolyte offers higher conversion efficiency and higher rates than water solutions saturated with carbon dioxide. pH values between 8 and 9 lead to the maximum values of efficiency. The operating cell voltage of 2.5 V, or higher, ensures conversion of the carbon dioxide to formate, although the hydrogen evolution reaction begins to compete strongly with the formate production reaction at higher cell voltages. Formate is produced at indium and lead electrodes at a conversion efficiency of 48 mg of CO2/kilojoule of energy input. This efficiency is about eight times that of natural photosynthesis in green plants. The electrochemical method of artificial photosynthesis is a promising approach for the conversion, separation and sequestration of carbon dioxide for confined environments as in space habitats, and also for carbon dioxide management in the terrestrial context. The heart of the reactor is a membrane cell fabricated from an alkaline polymer electrolyte membrane and catalyst- coated electrodes. This cell is assembled and held in compression in gold-plated hardware. The cathode side of the cell is supplied with carbon dioxide-saturated water or bicarbonate solution. The anode side of the cell is supplied with sodium hydroxide solution. The solutions are circulated past the electrodes in the electrochemical cell using pumps. A regulated power supply provides the electrical energy required for the reactions. Photovoltaic cells can be used to better mimic the photosynthetic reaction. The current flowing through the electrochemical cell, and the cell voltage, are monitored during experimentation. The products of the electrochemical reduction of carbon dioxide are allowed to accumulate in the cathode reservoir. Samples of the cathode solution are withdrawn for product analysis. Oxygen is generated on the anode side and is allowed to vent out of the reservoir.
Conversion of broadband thermal radiation in lithium niobate crystals of various compositions

NASA Astrophysics Data System (ADS)

Syuy, A. V.; Litvinova, M. N.; Goncharova, P. S.; Sidorov, N. V.; Palatnikov, M. N.; Krishtop, V. V.; Likhtin, V. V.

2013-05-01

The conversion of the broadband thermal radiation in stoichiometric ( R = 1) lithium niobate single crystals that are grown from melt with 58.6 mol % of LiO2, congruent ( R = Li/Nb = 0.946) melt with the K2O flux admixture (4.5 and 6.0 wt %), and congruent melt and in congruent single crystals doped with the Zn2+, Gd3+, and Er3+ cations is studied. It is demonstrated that the conversion efficiency of the stoichiometric crystal that is grown from the melt with 58.6 mol % of LiO2 is less than the conversion efficiency of congruent crystal. In addition, the stoichiometric and almost stoichiometric crystals and the doped congruent crystals exhibit the blue shift of the peak conversion intensity in comparison with a nominally pure congruent crystal. For the congruent crystals, the conversion intensities peak at 520 and 495 nm, respectively.
A subthreshold aVLSI implementation of the Izhikevich simple neuron model.

PubMed

Rangan, Venkat; Ghosh, Abhishek; Aparin, Vladimir; Cauwenberghs, Gert

2010-01-01

We present a circuit architecture for compact analog VLSI implementation of the Izhikevich neuron model, which efficiently describes a wide variety of neuron spiking and bursting dynamics using two state variables and four adjustable parameters. Log-domain circuit design utilizing MOS transistors in subthreshold results in high energy efficiency, with less than 1pJ of energy consumed per spike. We also discuss the effects of parameter variations on the dynamics of the equations, and present simulation results that replicate several types of neural dynamics. The low power operation and compact analog VLSI realization make the architecture suitable for human-machine interface applications in neural prostheses and implantable bioelectronics, as well as large-scale neural emulation tools for computational neuroscience.

Luminance- and Texture-Defined Information Processing in School-Aged Children with Autism

PubMed Central

Rivest, Jessica B.; Jemel, Boutheina; Bertone, Armando; McKerral, Michelle; Mottron, Laurent

2013-01-01

According to the complexity-specific hypothesis, the efficacy with which individuals with autism spectrum disorder (ASD) process visual information varies according to the extensiveness of the neural network required to process stimuli. Specifically, adults with ASD are less sensitive to texture-defined (or second-order) information, which necessitates the implication of several cortical visual areas. Conversely, the sensitivity to simple, luminance-defined (or first-order) information, which mainly relies on primary visual cortex (V1) activity, has been found to be either superior (static material) or intact (dynamic material) in ASD. It is currently unknown if these autistic perceptual alterations are present in childhood. In the present study, behavioural (threshold) and electrophysiological measures were obtained for static luminance- and texture-defined gratings presented to school-aged children with ASD and compared to those of typically developing children. Our behavioural and electrophysiological (P140) results indicate that luminance processing is likely unremarkable in autistic children. With respect to texture processing, there was no significant threshold difference between groups. However, unlike typical children, autistic children did not show reliable enhancements of brain activity (N230 and P340) in response to texture-defined gratings relative to luminance-defined gratings. This suggests reduced efficiency of neuro-integrative mechanisms operating at a perceptual level in autism. These results are in line with the idea that visual atypicalities mediated by intermediate-scale neural networks emerge before or during the school-age period in autism. PMID:24205355
Luminance- and texture-defined information processing in school-aged children with autism.

PubMed

Rivest, Jessica B; Jemel, Boutheina; Bertone, Armando; McKerral, Michelle; Mottron, Laurent

2013-01-01

According to the complexity-specific hypothesis, the efficacy with which individuals with autism spectrum disorder (ASD) process visual information varies according to the extensiveness of the neural network required to process stimuli. Specifically, adults with ASD are less sensitive to texture-defined (or second-order) information, which necessitates the implication of several cortical visual areas. Conversely, the sensitivity to simple, luminance-defined (or first-order) information, which mainly relies on primary visual cortex (V1) activity, has been found to be either superior (static material) or intact (dynamic material) in ASD. It is currently unknown if these autistic perceptual alterations are present in childhood. In the present study, behavioural (threshold) and electrophysiological measures were obtained for static luminance- and texture-defined gratings presented to school-aged children with ASD and compared to those of typically developing children. Our behavioural and electrophysiological (P140) results indicate that luminance processing is likely unremarkable in autistic children. With respect to texture processing, there was no significant threshold difference between groups. However, unlike typical children, autistic children did not show reliable enhancements of brain activity (N230 and P340) in response to texture-defined gratings relative to luminance-defined gratings. This suggests reduced efficiency of neuro-integrative mechanisms operating at a perceptual level in autism. These results are in line with the idea that visual atypicalities mediated by intermediate-scale neural networks emerge before or during the school-age period in autism.
Accessing quadratic nonlinearities of metals through metallodielectric photonic-band-gap structures.

PubMed

D'Aguanno, Giuseppe; Mattiucci, Nadia; Bloemer, Mark J; Scalora, Michael

2006-09-01

We study second harmonic generation in a metallodielectric photonic-band-gap structure made of alternating layers of silver and a generic, dispersive, linear, dielectric material. We find that under ideal conditions the conversion efficiency can be more than two orders of magnitude greater than the maximum conversion efficiency achievable in a single layer of silver. We interpret this enhancement in terms of the simultaneous availability of phase matching conditions over the structure and good field penetration into the metal layers. We also give a realistic example of a nine-period, Si3/N4Ag stack, where the backward conversion efficiency is enhanced by a factor of 50 compared to a single layer of silver.
A linear polarization converter with near unity efficiency in microwave regime

NASA Astrophysics Data System (ADS)

Xu, Peng; Wang, Shen-Yun; Geyi, Wen

2017-04-01

In this paper, we present a linear polarization converter in the reflective mode with near unity conversion efficiency. The converter is designed in an array form on the basis of a pair of orthogonally arranged three-dimensional split-loop resonators sharing a common terminal coaxial port and a continuous metallic ground slab. It converts the linearly polarized incident electromagnetic wave at resonance to its orthogonal counterpart upon the reflection mode. The conversion mechanism is explained by an equivalent circuit model, and the conversion efficiency can be tuned by changing the impedance of the terminal port. Such a scheme of the linear polarization converter has potential applications in microwave communications, remote sensing, and imaging.
Frequency doubling in poled polymers using anomalous dispersion phase-matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kowalczyk, T.C.; Singer, K.D.; Cahill, P.A.

1995-10-01

The authors report on a second harmonic generation in a poled polymer waveguide using anomalous dispersion phase-matching. Blue light ({lambda} = 407 nm) was produced by phase-matching the lowest order fundamental and harmonic modes over a distance of 32 {micro}m. The experimental conversion efficiency was {eta} = 1.2 {times} 10{sup {minus}4}, in agreement with theory. Additionally, they discuss a method of enhancing the conversion efficiency for second harmonic generation using anomalous dispersion phase-matching to optimize Cerenkov second harmonic generation. The modeling shows that a combination of phase-matching techniques creates larger conversion efficiencies and reduces critical fabrication requirements of the individualmore » phase-matching techniques.« less
Application of artificial neural networks to composite ply micromechanics

NASA Technical Reports Server (NTRS)

Brown, D. A.; Murthy, P. L. N.; Berke, L.

1991-01-01

Artificial neural networks can provide improved computational efficiency relative to existing methods when an algorithmic description of functional relationships is either totally unavailable or is complex in nature. For complex calculations, significant reductions in elapsed computation time are possible. The primary goal is to demonstrate the applicability of artificial neural networks to composite material characterization. As a test case, a neural network was trained to accurately predict composite hygral, thermal, and mechanical properties when provided with basic information concerning the environment, constituent materials, and component ratios used in the creation of the composite. A brief introduction on neural networks is provided along with a description of the project itself.
Conversion disorder: towards a neurobiological understanding

PubMed Central

Harvey, Samuel B; Stanton, Biba R; David, Anthony S

2006-01-01

Conversion disorders are a common cause of neurological disability, but the diagnosis remains controversial and the mechanism by which psychological stress can result in physical symptoms “unconsciously” is poorly understood. This review summarises research examining conversion disorder from a neurobiological perspective. Early observations suggesting a role for hemispheric specialization have not been replicated consistently. Patients with sensory conversion symptoms have normal evoked responses in primary and secondary somatosensory cortex but a reduction in the P300 potential, which is thought to reflect a lack of conscious processing of sensory stimuli. The emergence of functional imaging has provided the greatest opportunity for understanding the neural basis of conversion symptoms. Studies have been limited by small patient numbers and failure to control for confounding variables. The evidence available would suggest a broad hypothesis that frontal cortical and limbic activation associated with emotional stress may act via inhibitory basal ganglia–thalamocortical circuits to produce a deficit of conscious sensory or motor processing. The conceptual difficulties that have limited progress in this area are discussed. A better neuropsychiatric understanding of the mechanisms of conversion symptoms may improve our understanding of normal attention and volition and reduce the controversy surrounding this diagnosis. PMID:19412442
Conversive disorders among children and adolescents: towards new "complementarist" paradigms?

PubMed

Ouss, L; Tordjman, E

2014-10-01

This paper aims to describe current questions concerning conversive disorders among children and adolescents. We first describe prevalence and clinical characteristics of these. Many unresolved questions remain. Why do patients show excess, or loss of function? Attachment theory offers a relevant framework to answer this question. Does neurobiology of conversion disorders shed light on conversive processes? Current neurobiological research paradigms focus on the symptom, trying to infer processes, instead of proposing paradigms that test theoretical hypotheses. The most convincing theoretical framework that has already proposed a coherent theory of conversion is a psychodynamic one, which has not yet been tested with neurobiological paradigms. The interest of studying child and adolescent conversive disorders is to provide a means to more deeply investigate the two challenges we face: theoretical, and clinical ones. It provides the opportunity to access a pathopsychological process at its roots, not yet hidden by many defensive, rationalizing attitudes, and to better explore environmental features. We propose a "complementarist" model, which allows the combination of different approaches (neural, cognitive, environmental, attachment, intra-psychic) and permits proposal of different levels of therapeutic targets and means. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarov, Nikolay S.; Lin, Qianglu; Pietryga, Jeffrey M.

One source of efficiency losses in photovoltaic cells is their transparency toward solar photons with energies below the band gap of the absorbing layer. This loss can be reduced using a process of up-conversion whereby two or more sub-band-gap photons generate a single above-gap exciton. Traditional approaches to up-conversion, such as nonlinear two-photon absorption (2PA) or triplet fusion, suffer from low efficiency at solar light intensities, a narrow absorption bandwidth, nonoptimal absorption energies, and difficulties for implementing in practical devices. We show that these deficiencies can be alleviated using the effect of Auger up-conversion in thick-shell PbSe/CdSe quantum dots. Thismore » process relies on Auger recombination whereby two low-energy, core-based excitons are converted into a single higher-energy, shell-based exciton. When compared to their monocomponent counterparts, the tailored PbSe/CdSe heterostructures feature enhanced absorption cross-sections, a higher efficiency of the “productive” Auger pathway involving re-excitation of a hole, and longer lifetimes of both core- and shell-localized excitons. These features lead to effective up-conversion cross-sections that are more than 6 orders of magnitude higher than for standard nonlinear 2PA, which allows for efficient up-conversion of continuous wave infrared light at intensities as low as a few watts per square centimeter.« less
Highly Efficient Spin-to-Charge Current Conversion in Strained HgTe Surface States Protected by a HgCdTe Layer

NASA Astrophysics Data System (ADS)

Noel, P.; Thomas, C.; Fu, Y.; Vila, L.; Haas, B.; Jouneau, P.-H.; Gambarelli, S.; Meunier, T.; Ballet, P.; Attané, J. P.

2018-04-01

We report the observation of spin-to-charge current conversion in strained mercury telluride at room temperature, using spin pumping experiments. We show that a HgCdTe barrier can be used to protect the HgTe from direct contact with the ferromagnet, leading to very high conversion rates, with inverse Edelstein lengths up to 2.0 ±0.5 nm . The influence of the HgTe layer thickness on the conversion efficiency is found to differ strongly from what is expected in spin Hall effect systems. These measurements, associated with the temperature dependence of the resistivity, suggest that these high conversion rates are due to the spin momentum locking property of HgTe surface states.
Enhancement of conversion efficiency of extreme ultraviolet radiation from a liquid aqueous solution microjet target by use of dual laser pulses

NASA Astrophysics Data System (ADS)

Higashiguchi, Takeshi; Dojyo, Naoto; Hamada, Masaya; Kawasaki, Keita; Sasaki, Wataru; Kubodera, Shoichi

2006-03-01

We demonstrated a debris-free, efficient laser-produced plasma extreme ultraviolet (EUV) source by use of a regenerative liquid microjet target containing tin-dioxide (SnO II) nano-particles. By using a low SnO II concentration (6%) solution and dual laser pulses for the plasma control, we observed the EUV conversion efficiency of 1.2% with undetectable debris.
Prosopagnosia as a Type of Conversion Disorder.

PubMed

Power, Clodagh; Hannigan, Oisin; Coen, Robert; Bruce, Irene; Gibb, Matthew; McCarthy, Marie; Robinson, David; Lawlor, Brian A

2018-01-01

Conversion disorder is a common and debilitating condition that remains poorly understood. We present a previously undescribed form of conversion disorder to highlight the complexity of the condition and consider the interplay of factors that produce conversion symptoms. A 50-year-old male presented with acquired prosopagnosia and language impairment. Neuropsychological testing indicated right temporal lobe dysfunction. Extensive work-up outruled an organic aetiology. Reactivation of childhood trauma coincided with the onset of his symptoms. Childhood trauma is known to have adverse effects on the developing brain which may affect an individual's emotional behaviour and coping style. Functional neuroimaging techniques suggest that conversion symptoms may be linked to the disruption of higher order neural circuitry involved in the integration of emotional processing and cortical functioning. We propose that our patient's adverse childhood experiences led to the development of a particular personality and coping style that "primed" him for a later abnormal emotional and behavioural response when confronted with reminders of his traumatic background. Further interdisciplinary studies are required to further elucidate the neurobiological basis for this condition.
Representation of the Characteristics of Piezoelectric Fiber Composites with Neural Networks

NASA Astrophysics Data System (ADS)

Yapici, A.; Bickraj, K.; Yenilmez, A.; Li, M.; Tansel, I. N.; Martin, S. A.; Pereira, C. M.; Roth, L. E.

2007-03-01

Ideal sensors for the future should be economical, efficient, highly intelligent, and capable of obtaining their operation power from the environment. The use of piezoelectric fiber composites coupled with a low power microprocessor and backpropagation type neural networks is proposed for the development of a simple sensor to estimate the characteristics of harmonic forces. Three neural networks were used for the estimation of amplitude, gain and variation of the load in the time domain. The average estimation errors of the neural networks were less than 8% in all of the studied cases.
Calibration of a shock wave position sensor using artificial neural networks

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Weiland, Kenneth E.

1993-01-01

This report discusses the calibration of a shock wave position sensor. The position sensor works by using artificial neural networks to map cropped CCD frames of the shadows of the shock wave into the value of the shock wave position. This project was done as a tutorial demonstration of method and feasibility. It used a laboratory shadowgraph, nozzle, and commercial neural network package. The results were quite good, indicating that artificial neural networks can be used efficiently to automate the semi-quantitative applications of flow visualization.
High efficiency and output power from second- and third-harmonic millimeter-wave InP-TED oscillators at frequencies above 170 GHz

NASA Astrophysics Data System (ADS)

Rydberg, Anders

1990-10-01

InP TED (transferred electron device) oscillators have been experimentally investigated for frequencies between 170 and 279 GHz. It has been found that output powers of more than 7 and 0.2 mW are possible at 180 and 272 GHz using second- and third-harmonic mode operation, respectively. Conversion efficiencies of more than 13 percent and 0.3 percent between fundamental and second harmonic and fundamental and third harmonic, respectively, have been found. The conversion efficiencies are comparable to GaAs TEDs. The output powers, conversion efficiencies, and tuning ranges (more than 22 percent) are the largest reported for InP TEDs at these frequencies. The output power at third harmonic was sufficient for supplying a superconducting mixer with local oscillator power.
Dark states and delocalization: Competing effects of quantum coherence on the efficiency of light harvesting systems.

PubMed

Hu, Zixuan; Engel, Gregory S; Alharbi, Fahhad H; Kais, Sabre

2018-02-14

Natural light harvesting systems exploit electronic coupling of identical chromophores to generate efficient and robust excitation transfer and conversion. Dark states created by strong coupling between chromophores in the antenna structure can significantly reduce radiative recombination and enhance energy conversion efficiency. Increasing the number of the chromophores increases the number of dark states and the associated enhanced energy conversion efficiency yet also delocalizes excitations away from the trapping center and reduces the energy conversion rate. Therefore, a competition between dark state protection and delocalization must be considered when designing the optimal size of a light harvesting system. In this study, we explore the two competing mechanisms in a chain-structured antenna and show that dark state protection is the dominant mechanism, with an intriguing dependence on the parity of the number of chromophores. This dependence is linked to the exciton distribution among eigenstates, which is strongly affected by the coupling strength between chromophores and the temperature. Combining these findings, we propose that increasing the coupling strength between the chromophores can significantly increase the power output of the light harvesting system.
Numerical study of hydrodynamic behavior and conversion efficiency of a two-buoy wave energy converter

NASA Astrophysics Data System (ADS)

Yang, Cen; Zhang, Yong-liang

2018-04-01

In this paper we propose a two-buoy wave energy converter composed of a heaving semi-submerged cylindrical buoy, a fixed submerged cylindrical buoy and a power take-off (PTO) system, and investigate the effect of the fixed submerged buoy on the hydrodynamics of the heaving semi-submerged buoy based on the three-dimensional potential theory. And the dynamic response of the semi-submerged buoy and the wave energy conversion efficiency of the converter are analyzed. The difference of the hydrodynamics and the wave energy conversion efficiency of a semi-submerged buoy converter with and without a fixed submerged buoy is discussed. It is revealed that the influence of the fixed submerged buoy on the exciting wave force, the added mass, the radiation damping coefficient and the wave energy conversion efficiency can be significant with a considerable variation, depending on the vertical distance between the heaving semi-submerged buoy and the fixed submerged buoy, the diameter ratio of the fixed submerged buoy to the heaving semi-submerged buoy and the water depth.
Efficient extreme-UV-to-extreme-UV conversion by four-wave mixing with intense near-IR pulses in highly charged ion plasmas

NASA Astrophysics Data System (ADS)

Chu, Hsu-hsin; Wang, Jyhpyng

2018-05-01

Nonlinear optics in the extreme-ultraviolet (EUV) has been limited by lack of transparent media and small conversion efficiency. To overcome this problem we explore the advantage of using multiply charged ion plasmas as the interacting media between EUV and intense near-infrared (NIR) pulses. Such media are transparent to EUV and can withstand intense NIR driving pulses without damage. We calculate the third-order nonlinear polarizabilities of Ar2 + and Ar3 + ions for EUV and NIR four-wave mixing by using the well-proven Cowan code and find that the EUV-to-EUV conversion efficiency as high as 26% can be expected for practical experimental configurations using multi-terawatt NIR lasers. Such a high efficiency is possible because the driving pulse intensity can be scaled up to several orders of magnitude higher than in conventional nonlinear media, and the group-velocity and phase mismatch are insignificant at the experimental plasma densities. This effective scheme of wave mixing can be utilized for ultrafast EUV waveform measurement and control as well as wavelength conversion.
Efficient Solar-Thermal Energy Harvest Driven by Interfacial Plasmonic Heating-Assisted Evaporation.

PubMed

Chang, Chao; Yang, Chao; Liu, Yanming; Tao, Peng; Song, Chengyi; Shang, Wen; Wu, Jianbo; Deng, Tao

2016-09-07

The plasmonic heating effect of noble nanoparticles has recently received tremendous attention for various important applications. Herein, we report the utilization of interfacial plasmonic heating-assisted evaporation for efficient and facile solar-thermal energy harvest. An airlaid paper-supported gold nanoparticle thin film was placed at the thermal energy conversion region within a sealed chamber to convert solar energy into thermal energy. The generated thermal energy instantly vaporizes the water underneath into hot vapors that quickly diffuse to the thermal energy release region of the chamber to condense into liquids and release the collected thermal energy. The condensed water automatically flows back to the thermal energy conversion region under the capillary force from the hydrophilic copper mesh. Such an approach simultaneously realizes efficient solar-to-thermal energy conversion and rapid transportation of converted thermal energy to target application terminals. Compared to conventional external photothermal conversion design, the solar-thermal harvesting device driven by the internal plasmonic heating effect has reduced the overall thermal resistance by more than 50% and has demonstrated more than 25% improvement of solar water heating efficiency.
Synergic solventing-out crystallization with subsequent time-delay thermal annealing of PbI2 precursor in mesostructured perovskite solar cells

NASA Astrophysics Data System (ADS)

Jia, Fujin; Guo, Yanqun; Che, Lijia; Liu, Zhiyong; Zeng, Zhigang; Cai, Chuanbing

2018-06-01

Although the two-step sequential deposition method provides an efficient route to fabricate high performance perovskite solar cells (PSSCs) with increasing reproducibility, the inefficient and incomplete conversion of PbI2 to perovskite is still quite a challenge. Following pioneering works, we found that the conversion process from PbI2 to perovskite mainly involves diffusion, infiltration, contact and reaction. In order to facilitate the conversion from PbI2 to perovskite, we demonstrate an effective method to regulate supersaturation level (the driving force to crystallization) of PbI2 by solventing-out crystallization combining with subsequent time-delay thermal annealing of PbI2 wet film. Enough voids and spaces in resulting porous PbI2 layer will be in favor of efficient diffusion, infiltration of CH3NH3I solution, and further enhance the contact and reaction between PbI2 and CH3NH3I in the whole film, leading to rapid, efficient and complete perovskite conversion with a conversion level of about 99.9%. Enhancement of light harvesting ranging from visible to near-IR region was achieved for the resultant high-quality perovskite. Upon this combined method, the fabricated mesostructured solar cells show tremendous power conversion efficiency (PCE) improvement from 3.2% to about 12.3% with less hysteresis owing to the simultaneous enhancement of short-circuit photocurrent density (J sc), open-circuit voltage (V oc) and fill factor (FF).

Neural joint control for Space Shuttle Remote Manipulator System

NASA Technical Reports Server (NTRS)

Atkins, Mark A.; Cox, Chadwick J.; Lothers, Michael D.; Pap, Robert M.; Thomas, Charles R.

1992-01-01

Neural networks are being used to control a robot arm in a telerobotic operation. The concept uses neural networks for both joint and inverse kinematics in a robotic control application. An upper level neural network is trained to learn inverse kinematic mappings. The output, a trajectory, is then fed to the Decentralized Adaptive Joint Controllers. This neural network implementation has shown that the controlled arm recovers from unexpected payload changes while following the reference trajectory. The neural network-based decentralized joint controller is faster, more robust and efficient than conventional approaches. Implementations of this architecture are discussed that would relax assumptions about dynamics, obstacles, and heavy loads. This system is being developed to use with the Space Shuttle Remote Manipulator System.
Lead-Free Inverted Planar Formamidinium Tin Triiodide Perovskite Solar Cells Achieving Power Conversion Efficiencies up to 6.22.

PubMed

Liao, Weiqiang; Zhao, Dewei; Yu, Yue; Grice, Corey R; Wang, Changlei; Cimaroli, Alexander J; Schulz, Philip; Meng, Weiwei; Zhu, Kai; Xiong, Ren-Gen; Yan, Yanfa

2016-11-01

Efficient lead (Pb)-free inverted planar formamidinium tin triiodide (FASnI 3 ) perovskite solar cells (PVSCs) are demonstrated. Our FASnI 3 PVSCs achieved average power conversion efficiencies (PCEs) of 5.41% ± 0.46% and a maximum PCE of 6.22% under forward voltage scan. The PVSCs exhibit small photocurrent-voltage hysteresis and high reproducibility. The champion cell shows a steady-state efficiency of ≈6.00% for over 100 s. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A soft-switching coupled inductor bidirectional DC-DC converter with high-conversion ratio

NASA Astrophysics Data System (ADS)

Chao, Kuei-Hsiang; Jheng, Yi-Cing

2018-01-01

A soft-switching bidirectional DC-DC converter is presented herein as a way to improve the conversion efficiency of a photovoltaic (PV) system. Adoption of coupled inductors enables the presented converter not only to provide a high-conversion ratio but also to suppress the transient surge voltage via the release of the energy stored in leakage flux of the coupled inductors, and the cost can kept down consequently. A combined use of a switching mechanism and an auxiliary resonant branch enables the converter to successfully perform zero-voltage switching operations on the main switches and improves the efficiency accordingly. It was testified by experiments that our proposed converter works relatively efficiently in full-load working range. Additionally, the framework of the converter intended for testifying has high-conversion ratio. The results of a test, where a generating system using PV module array coupled with batteries as energy storage device was used as the low-voltage input side, and DC link was used as high-voltage side, demonstrated our proposed converter framework with high-conversion ratio on both high-voltage and low-voltage sides.
Electromechanical conversion efficiency for dielectric elastomer generator in different energy harvesting cycles

NASA Astrophysics Data System (ADS)

Cao, Jian-Bo; E, Shi-Ju; Guo, Zhuang; Gao, Zhao; Luo, Han-Pin

2017-11-01

In order to improve electromechanical conversion efficiency for dielectric elastomer generators (DEG), on the base of studying DEG energy harvesting cycles of constant voltage, constant charge and constant electric field intensity, a new combined cycle mode and optimization theory in terms of the generating mechanism and electromechanical coupling process have been built. By controlling the switching point to achieve the best energy conversion cycle, the energy loss in the energy conversion process is reduced. DEG generating test bench which was used to carry out comparative experiments has been established. Experimental results show that the collected energy in constant voltage cycle, constant charge cycle and constant electric field intensity energy harvesting cycle decreases in turn. Due to the factors such as internal resistance losses, electrical losses and so on, actual energy values are less than the theoretical values. The electric energy conversion efficiency by combining constant electric field intensity cycle with constant charge cycle is larger than that of constant electric field intensity cycle. The relevant conclusions provide a basis for the further applications of DEG.
Carbon dioxide splitting in a dielectric barrier discharge plasma: a combined experimental and computational study.

PubMed

Aerts, Robby; Somers, Wesley; Bogaerts, Annemie

2015-02-01

Plasma technology is gaining increasing interest for the splitting of CO2 into CO and O2 . We have performed experiments to study this process in a dielectric barrier discharge (DBD) plasma with a wide range of parameters. The frequency and dielectric material did not affect the CO2 conversion and energy efficiency, but the discharge gap can have a considerable effect. The specific energy input has the most important effect on the CO2 conversion and energy efficiency. We have also presented a plasma chemistry model for CO2 splitting, which shows reasonable agreement with the experimental conversion and energy efficiency. This model is used to elucidate the critical reactions that are mostly responsible for the CO2 conversion. Finally, we have compared our results with other CO2 splitting techniques and we identified the limitations as well as the benefits and future possibilities in terms of modifications of DBD plasmas for greenhouse gas conversion in general. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.
Neural rotational speed control for wave energy converters

NASA Astrophysics Data System (ADS)

Amundarain, M.; Alberdi, M.; Garrido, A. J.; Garrido, I.

2011-02-01

Among the benefits arising from an increasing use of renewable energy are: enhanced security of energy supply, stimulation of economic growth, job creation and protection of the environment. In this context, this study analyses the performance of an oscillating water column device for wave energy conversion in function of the stalling behaviour in Wells turbines, one of the most widely used turbines in wave energy plants. For this purpose, a model of neural rotational speed control system is presented, simulated and implemented. This scheme is employed to appropriately adapt the speed of the doubly-fed induction generator coupled to the turbine according to the pressure drop entry, so as to avoid the undesired stalling behaviour. It is demonstrated that the proposed neural rotational speed control design adequately matches the desired relationship between the slip of the doubly-fed induction generator and the pressure drop input, improving the power generated by the turbine generator module.
Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

PubMed Central

Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

2013-01-01

Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines. PMID:23408775
Integrating the behavioral and neural dynamics of response selection in a dual-task paradigm: a dynamic neural field model of Dux et al. (2009).

PubMed

Buss, Aaron T; Wifall, Tim; Hazeltine, Eliot; Spencer, John P

2014-02-01

People are typically slower when executing two tasks than when only performing a single task. These dual-task costs are initially robust but are reduced with practice. Dux et al. (2009) explored the neural basis of dual-task costs and learning using fMRI. Inferior frontal junction (IFJ) showed a larger hemodynamic response on dual-task trials compared with single-task trial early in learning. As dual-task costs were eliminated, dual-task hemodynamics in IFJ reduced to single-task levels. Dux and colleagues concluded that the reduction of dual-task costs is accomplished through increased efficiency of information processing in IFJ. We present a dynamic field theory of response selection that addresses two questions regarding these results. First, what mechanism leads to the reduction of dual-task costs and associated changes in hemodynamics? We show that a simple Hebbian learning mechanism is able to capture the quantitative details of learning at both the behavioral and neural levels. Second, is efficiency isolated to cognitive control areas such as IFJ, or is it also evident in sensory motor areas? To investigate this, we restrict Hebbian learning to different parts of the neural model. None of the restricted learning models showed the same reductions in dual-task costs as the unrestricted learning model, suggesting that efficiency is distributed across cognitive control and sensory motor processing systems.
Deficits in context-dependent adaptive coding of reward in schizophrenia

PubMed Central

Kirschner, Matthias; Hager, Oliver M; Bischof, Martin; Hartmann-Riemer, Matthias N; Kluge, Agne; Seifritz, Erich; Tobler, Philippe N; Kaiser, Stefan

2016-01-01

Theoretical principles of information processing and empirical findings suggest that to efficiently represent all possible rewards in the natural environment, reward-sensitive neurons have to adapt their coding range dynamically to the current reward context. Adaptation ensures that the reward system is most sensitive for the most likely rewards, enabling the system to efficiently represent a potentially infinite range of reward information. A deficit in neural adaptation would prevent precise representation of rewards and could have detrimental effects for an organism’s ability to optimally engage with its environment. In schizophrenia, reward processing is known to be impaired and has been linked to different symptom dimensions. However, despite the fundamental significance of coding reward adaptively, no study has elucidated whether adaptive reward processing is impaired in schizophrenia. We therefore studied patients with schizophrenia (n=27) and healthy controls (n=25), using functional magnetic resonance imaging in combination with a variant of the monetary incentive delay task. Compared with healthy controls, patients with schizophrenia showed less efficient neural adaptation to the current reward context, which leads to imprecise neural representation of reward. Importantly, the deficit correlated with total symptom severity. Our results suggest that some of the deficits in reward processing in schizophrenia might be due to inefficient neural adaptation to the current reward context. Furthermore, because adaptive coding is a ubiquitous feature of the brain, we believe that our findings provide an avenue in defining a general impairment in neural information processing underlying this debilitating disorder. PMID:27430009
Ictal high frequency oscillations distinguish two types of seizure territories in humans

PubMed Central

Weiss, Shennan A.; Banks, Garrett P.; McKhann, Guy M.; Goodman, Robert R.; Emerson, Ronald G.; Trevelyan, Andrew J.

2013-01-01

High frequency oscillations have been proposed as a clinically useful biomarker of seizure generating sites. We used a unique set of human microelectrode array recordings (four patients, 10 seizures), in which propagating seizure wavefronts could be readily identified, to investigate the basis of ictal high frequency activity at the cortical (subdural) surface. Sustained, repetitive transient increases in high gamma (80–150 Hz) amplitude, phase-locked to the low-frequency (1–25 Hz) ictal rhythm, correlated with strong multi-unit firing bursts synchronized across the core territory of the seizure. These repetitive high frequency oscillations were seen in recordings from subdural electrodes adjacent to the microelectrode array several seconds after seizure onset, following ictal wavefront passage. Conversely, microelectrode recordings demonstrating only low-level, heterogeneous neural firing correlated with a lack of high frequency oscillations in adjacent subdural recording sites, despite the presence of a strong low-frequency signature. Previously, we reported that this pattern indicates a failure of the seizure to invade the area, because of a feedforward inhibitory veto mechanism. Because multi-unit firing rate and high gamma amplitude are closely related, high frequency oscillations can be used as a surrogate marker to distinguish the core seizure territory from the surrounding penumbra. We developed an efficient measure to detect delayed-onset, sustained ictal high frequency oscillations based on cross-frequency coupling between high gamma amplitude and the low-frequency (1–25 Hz) ictal rhythm. When applied to the broader subdural recording, this measure consistently predicted the timing or failure of ictal invasion, and revealed a surprisingly small and slowly spreading seizure core surrounded by a far larger penumbral territory. Our findings thus establish an underlying neural mechanism for delayed-onset, sustained ictal high frequency oscillations, and provide a practical, efficient method for using them to identify the small ictal core regions. Our observations suggest that it may be possible to reduce substantially the extent of cortical resections in epilepsy surgery procedures without compromising seizure control. PMID:24176977
Glucose buffer is suitable for blood group conversion with α-N acetylgalactosaminidase and α-galactosidase

PubMed Central

Gao, Hong-Wei; Li, Su-Bo; Bao, Guo-Qiang; Zhang, Xue; Li, Hui; Wang, Ying-Li; Tan, Ying-Xia; Ji, Shou-Ping; Gong, Feng

2014-01-01

Background It is well known that the buffer plays a key role in the enzymatic reaction involved in blood group conversion. In previous study, we showed that a glycine buffer is suitable for A to O or B to O blood group conversion. In this study, we investigated the use of 5% glucose and other buffers for A to O or B to O blood group conversion by α-N-acetylgalactosaminidase or α-galactosidase. Materials and methods We compared the binding ability of α-N-acetylgalactosaminidase/α-galactosidase with red blood cells (RBC) in different reaction buffers, such as normal saline, phosphate-buffered saline (PBS), a disodium hydrogen phosphate-based buffer (PCS), and 5% commercial glucose solution. The doses of enzymes necessary for the A/B to O conversion in different reaction buffers were determined and compared. The enzymes’ ability to bind to RBC was evaluated by western blotting, and routine blood typing and fluorescence activated cell sorting was used to evaluate B/A to O conversion efficiency. Results The A to O conversion efficiency in glucose buffer was similar to that in glycine buffer with the same dose (>0.06 mg/mL pRBC). B to O conversion efficiency in glucose buffer was also similar to that in glycine buffer with the same dose (>0.005 mg/mL pRBC). Most enzymes could bind with RBC in glycine or glucose buffer, but few enzymes could bind with RBC in PBS, PCS, or normal saline. Conclusion These results indicate that 5% glucose solution provides a suitable condition for enzymolysis, especially for enzymes combining with RBC. Meanwhile, the conversion efficiency of A/B to O was similar in glucose buffer and glycine buffer. Moreover, 5% glucose solution has been used for years in venous transfusion, it is safe for humans and its cost is lower. Our results do, therefore, suggest that 5% glucose solution could become a novel suitable buffer for A/B to O blood group conversion. PMID:24333060
Prediction of moving bed biofilm reactor (MBBR) performance for the treatment of aniline using artificial neural networks (ANN).

PubMed

Delnavaz, M; Ayati, B; Ganjidoust, H

2010-07-15

In this study, the results of 1-year efficiency forecasting using artificial neural networks (ANN) models of a moving bed biofilm reactor (MBBR) for a toxic and hard biodegradable aniline removal were investigated. The reactor was operated in an aerobic batch and continuous condition with 50% by volume which was filled with light expanded clay aggregate (LECA) as carrier. Efficiency evaluation of the reactors was obtained at different retention time (RT) of 8, 24, 48 and 72 h with an influent COD from 100 to 4000 mg/L. Exploratory data analysis was used to detect relationships between the data and dependent evaluated one. The appropriate architecture of the neural network models was determined using several steps of training and testing of the models. The ANN-based models were found to provide an efficient and a robust tool in predicting MBBR performance for treating aromatic amine compounds. 2010 Elsevier B.V. All rights reserved.
Neural Correlates of Intersensory Processing in Five-Month-Old Infants

PubMed Central

Reynolds, Greg D.; Bahrick, Lorraine E.; Lickliter, Robert; Guy, Maggie W.

2014-01-01

Two experiments assessing event-related potentials in 5-month-old infants were conducted to examine neural correlates of attentional salience and efficiency of processing of a visual event (woman speaking) paired with redundant (synchronous) speech, nonredundant (asynchronous) speech, or no speech. In Experiment 1, the Nc component associated with attentional salience was greater in amplitude following synchronous audiovisual as compared with asynchronous audiovisual and unimodal visual presentations. A block design was utilized in Experiment 2 to examine efficiency of processing of a visual event. Only infants exposed to synchronous audiovisual speech demonstrated a significant reduction in amplitude of the late slow wave associated with successful stimulus processing and recognition memory from early to late blocks of trials. These findings indicate that events that provide intersensory redundancy are associated with enhanced neural responsiveness indicative of greater attentional salience and more efficient stimulus processing as compared with the same events when they provide no intersensory redundancy in 5-month-old infants. PMID:23423948
Coherent Microwave-to-Optical Conversion via Six-Wave Mixing in Rydberg Atoms

NASA Astrophysics Data System (ADS)

Han, Jingshan; Vogt, Thibault; Gross, Christian; Jaksch, Dieter; Kiffner, Martin; Li, Wenhui

2018-03-01

We present an experimental demonstration of converting a microwave field to an optical field via frequency mixing in a cloud of cold 87Rb atoms, where the microwave field strongly couples to an electric dipole transition between Rydberg states. We show that the conversion allows the phase information of the microwave field to be coherently transferred to the optical field. With the current energy level scheme and experimental geometry, we achieve a photon-conversion efficiency of ˜0.3 % at low microwave intensities and a broad conversion bandwidth of more than 4 MHz. Theoretical simulations agree well with the experimental data, and they indicate that near-unit efficiency is possible in future experiments.
Solar power from satellites

NASA Technical Reports Server (NTRS)

Glaser, P. E.

1977-01-01

Microwave beaming of satellite-collected solar energy to earth for conversion to useful industrial power is evaluated for feasibility, with attention given to system efficiencies and costs, ecological impact, hardware to be employed, available options for energy conversion and transmission, and orbiting and assembly. Advantages of such a power generation and conversion system are listed, plausible techniques for conversion of solar energy (thermionic, thermal electric, photovoltaic) and transmission to earth (lasers, arrays of mirrors, microwave beams) are compared. Structural fatigue likely to result from brief daily eclipses, 55% system efficiency at the present state of the art, present projections of system costs, and projected economic implications of the technology are assessed. Two-stage orbiting and assembly plans are described.
Model validation of untethered, ultrasonic neural dust motes for cortical recording.

PubMed

Seo, Dongjin; Carmena, Jose M; Rabaey, Jan M; Maharbiz, Michel M; Alon, Elad

2015-04-15

A major hurdle in brain-machine interfaces (BMI) is the lack of an implantable neural interface system that remains viable for a substantial fraction of the user's lifetime. Recently, sub-mm implantable, wireless electromagnetic (EM) neural interfaces have been demonstrated in an effort to extend system longevity. However, EM systems do not scale down in size well due to the severe inefficiency of coupling radio-waves at those scales within tissue. This paper explores fundamental system design trade-offs as well as size, power, and bandwidth scaling limits of neural recording systems built from low-power electronics coupled with ultrasonic power delivery and backscatter communication. Such systems will require two fundamental technology innovations: (1) 10-100 μm scale, free-floating, independent sensor nodes, or neural dust, that detect and report local extracellular electrophysiological data via ultrasonic backscattering and (2) a sub-cranial ultrasonic interrogator that establishes power and communication links with the neural dust. We provide experimental verification that the predicted scaling effects follow theory; (127 μm)(3) neural dust motes immersed in water 3 cm from the interrogator couple with 0.002064% power transfer efficiency and 0.04246 ppm backscatter, resulting in a maximum received power of ∼0.5 μW with ∼1 nW of change in backscatter power with neural activity. The high efficiency of ultrasonic transmission can enable the scaling of the sensing nodes down to 10s of micrometer. We conclude with a brief discussion of the application of neural dust for both central and peripheral nervous system recordings, and perspectives on future research directions. Copyright © 2014 Elsevier B.V. All rights reserved.
Comparison of oil refining and biodiesel production process between screw press and n-hexane techniques from beauty leaf feedstock

NASA Astrophysics Data System (ADS)

Bhuiya, M. M. K.; Rasul, M. G.; Khan, M. M. K.; Ashwath, N.

2016-07-01

The Beauty Leaf Tree (Callophylum inophyllum) is regarded as an alternative source of energy to produce 2nd generation biodiesel due to its potentiality as well as high oil yield content in the seed kernels. The treating process is indispensable during the biodiesel production process because it can augment the yield as well as quality of the product. Oil extracted from both mechanical screw press and solvent extraction using n-hexane was refined. Five replications each of 25 gm of crude oil for screw press and five replications each of 25 gm of crude oil for n-hexane were selected for refining as well as biodiesel conversion processes. The oil refining processes consists of degumming, neutralization as well as dewaxing. The degumming, neutralization and dewaxing processes were performed to remove all the gums (phosphorous-based compounds), free fatty acids, and waxes from the fresh crude oil before the biodiesel conversion process carried out, respectively. The results indicated that up to 73% and 81% of mass conversion efficiency of the refined oil in the screw press and n-hexane refining processes were obtained, respectively. It was also found that up to 88% and 90% of biodiesel were yielded in terms of mass conversion efficiency in the transesterification process for the screw press and n-hexane techniques, respectively. While the entire processes (refining and transesterification) were considered, the conversion of beauty leaf tree (BLT) refined oil into biodiesel was yielded up to 65% and 73% of mass conversion efficiency for the screw press and n-hexane techniques, respectively. Physico-chemical properties of crude and refined oil, and biodiesel were characterized according to the ASTM standards. Overall, BLT has the potential to contribute as an alternative energy source because of high mass conversion efficiency.
A High-Performance Lossless Compression Scheme for EEG Signals Using Wavelet Transform and Neural Network Predictors

PubMed Central

Sriraam, N.

2012-01-01

Developments of new classes of efficient compression algorithms, software systems, and hardware for data intensive applications in today's digital health care systems provide timely and meaningful solutions in response to exponentially growing patient information data complexity and associated analysis requirements. Of the different 1D medical signals, electroencephalography (EEG) data is of great importance to the neurologist for detecting brain-related disorders. The volume of digitized EEG data generated and preserved for future reference exceeds the capacity of recent developments in digital storage and communication media and hence there is a need for an efficient compression system. This paper presents a new and efficient high performance lossless EEG compression using wavelet transform and neural network predictors. The coefficients generated from the EEG signal by integer wavelet transform are used to train the neural network predictors. The error residues are further encoded using a combinational entropy encoder, Lempel-Ziv-arithmetic encoder. Also a new context-based error modeling is also investigated to improve the compression efficiency. A compression ratio of 2.99 (with compression efficiency of 67%) is achieved with the proposed scheme with less encoding time thereby providing diagnostic reliability for lossless transmission as well as recovery of EEG signals for telemedicine applications. PMID:22489238
A high-performance lossless compression scheme for EEG signals using wavelet transform and neural network predictors.

PubMed

Sriraam, N

2012-01-01

Developments of new classes of efficient compression algorithms, software systems, and hardware for data intensive applications in today's digital health care systems provide timely and meaningful solutions in response to exponentially growing patient information data complexity and associated analysis requirements. Of the different 1D medical signals, electroencephalography (EEG) data is of great importance to the neurologist for detecting brain-related disorders. The volume of digitized EEG data generated and preserved for future reference exceeds the capacity of recent developments in digital storage and communication media and hence there is a need for an efficient compression system. This paper presents a new and efficient high performance lossless EEG compression using wavelet transform and neural network predictors. The coefficients generated from the EEG signal by integer wavelet transform are used to train the neural network predictors. The error residues are further encoded using a combinational entropy encoder, Lempel-Ziv-arithmetic encoder. Also a new context-based error modeling is also investigated to improve the compression efficiency. A compression ratio of 2.99 (with compression efficiency of 67%) is achieved with the proposed scheme with less encoding time thereby providing diagnostic reliability for lossless transmission as well as recovery of EEG signals for telemedicine applications.

Understanding the Implications of Neural Population Activity on Behavior

NASA Astrophysics Data System (ADS)

Briguglio, John

Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests a variety of hypotheses that will be useful in helping to understand the relationship between neural activity and behavior as recorded neural populations continue to grow.
A method for compression of intra-cortically-recorded neural signals dedicated to implantable brain-machine interfaces.

PubMed

Shaeri, Mohammad Ali; Sodagar, Amir M

2015-05-01

This paper proposes an efficient data compression technique dedicated to implantable intra-cortical neural recording devices. The proposed technique benefits from processing neural signals in the Discrete Haar Wavelet Transform space, a new spike extraction approach, and a novel data framing scheme to telemeter the recorded neural information to the outside world. Based on the proposed technique, a 64-channel neural signal processor was designed and prototyped as a part of a wireless implantable extra-cellular neural recording microsystem. Designed in a 0.13- μ m standard CMOS process, the 64-channel neural signal processor reported in this paper occupies ∼ 0.206 mm(2) of silicon area, and consumes 94.18 μW when operating under a 1.2-V supply voltage at a master clock frequency of 1.28 MHz.
The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex.

PubMed

Petroni, Agustin; Cohen, Samantha S; Ai, Lei; Langer, Nicolas; Henin, Simon; Vanderwal, Tamara; Milham, Michael P; Parra, Lucas C

2018-01-01

Neural development is generally marked by an increase in the efficiency and diversity of neural processes. In a large sample ( n = 114) of human children and adults with ages ranging from 5 to 44 yr, we investigated the neural responses to naturalistic video stimuli. Videos from both real-life classroom settings and Hollywood feature films were used to probe different aspects of attention and engagement. For all stimuli, older ages were marked by more variable neural responses. Variability was assessed by the intersubject correlation of evoked electroencephalographic responses. Young males also had less-variable responses than young females. These results were replicated in an independent cohort ( n = 303). When interpreted in the context of neural maturation, we conclude that neural function becomes more variable with maturity, at least during the passive viewing of real-world stimuli.
Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

PubMed

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.
Theoretical analysis of improved efficiency of silicon-wafer solar cells with textured nanotriangular grating structure

NASA Astrophysics Data System (ADS)

Zhang, Yaoju; Zheng, Jun; Zhao, Xuesong; Ruan, Xiukai; Cui, Guihua; Zhu, Haiyong; Dai, Yuxing

2018-03-01

A practical model of crystalline silicon-wafer solar cells is proposed in order to enhance the light absorption and improve the conversion efficiency of silicon solar cells. In the model, the front surface of the silicon photovoltaic film is designed to be a textured-triangular-grating (TTG) structure, and the ITO contact film and the antireflection coating (ARC) of glass are coated on the TTG surface of silicon solar cells. The optical absorption spectrum of solar cells are simulated by applying the finite difference time domain method. Electrical parameters of the solar cells are calculated using two models with and without carrier loss. The effect of structure parameters on the performance of the TTG cell is discussed in detail. It is found that the thickness (tg) of the ARC, period (p) of grating, and base angle (θ) of triangle have a crucial influence on the conversion efficiency. The optimal structure of the TTG cell is designed. The TTG solar cell can produce higher efficiency in a wide range of solar incident angle and the average efficiency of the optimal TTG cell over 7:30-16:30 time of day is 8% higher than that of the optimal plane solar cell. In addition, the study shows that the bulk recombination of carriers has an influence on the conversion efficiency of the cell, the conversion efficiency of the actual solar cell with carrier recombination is reduced by 20.0% of the ideal cell without carrier recombination.
Comparison of holographic lens and filter systems for lateral spectrum splitting

NASA Astrophysics Data System (ADS)

Vorndran, Shelby; Chrysler, Benjamin; Kostuk, Raymond K.

2016-09-01

Spectrum splitting is an approach to increasing the conversion efficiency of a photovoltaic (PV) system. Several methods can be used to perform this function which requires efficient spatial separation of different spectral bands of the incident solar radiation. In this paper several of holographic methods for implementing spectrum splitting are reviewed along with the benefits and disadvantages associated with each approach. The review indicates that a volume holographic lens has many advantages for spectrum splitting in terms of both power conversion efficiency and energy yield. A specific design for a volume holographic spectrum splitting lens is discussed for use with high bandgap InGaP and low bandgap silicon PV cells. The holographic lenses are modeled using rigorous coupled wave analysis, and the optical efficiency is evaluated using non-sequential raytracing. A proof-of-concept off-axis holographic lens is also recorded in dichromated gelatin film and the spectral diffraction efficiency of the hologram is measured with multiple laser sources across the diffracted spectral band. The experimental volume holographic lens (VHL) characteristics are compared to an ideal spectrum splitting filter in terms of power conversion efficiency and energy yield in environments with high direct normal incidence (DNI) illumination and high levels of diffuse illumination. The results show that the experimental VHL can achieve 62.5% of the ideal filter power conversion efficiency, 64.8% of the ideal filter DNI environment energy yield, and 57.7% of the ideal diffuse environment energy yield performance.
Sulfide catalysts for reducing SO2 to elemental sulfur

DOEpatents

Jin, Yun; Yu, Qiquan; Chang, Shih-Ger

2001-01-01

A highly efficient sulfide catalyst for reducing sulfur dioxide to elemental sulfur, which maximizes the selectivity of elemental sulfur over byproducts and has a high conversion efficiency. Various feed stream contaminants, such as water vapor are well tolerated. Additionally, hydrogen, carbon monoxide, or hydrogen sulfides can be employed as the reducing gases while maintaining high conversion efficiency. This allows a much wider range of uses and higher level of feed stream contaminants than prior art catalysts.
Contextual Modulation is Related to Efficiency in a Spiking Network Model of Visual Cortex.

PubMed

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo; Vanni, Simo

2015-01-01

In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response.
Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles

PubMed Central

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P. Read; Camerer, Colin F.

2014-01-01

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations—price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation. PMID:25002476
Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

PubMed

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

2014-07-22

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.
Highly efficient continuous-wave Nd:YAG ceramic lasers at 946 nm

NASA Astrophysics Data System (ADS)

Zhu, H. Y.; Xu, C. W.; Zhang, J.; Tang, D. Y.; Luo, D. W.; Duan, Y. M.

2013-07-01

Highly efficient CW operation of diode-end-pumped Nd:YAG ceramic lasers at 946 nm is experimentally demonstrated. When a 5 mm long in-house fabricated Nd:YAG ceramic was used as the gain medium, a maximum output power of 10.5 W was obtained under an incident pump power of 35 W, corresponding to an optical conversion efficiency of 30%, while, when a 3 mm long ceramic sample was used, a maximum output power of 8.7 W was generated with a slope efficiency of 65% with respect to the absorbed pump power. Both the optical conversion efficiency and slope efficiency are the highest results reported so far for the diode-pumped 946 nm lasers.
A Streaming PCA VLSI Chip for Neural Data Compression.

PubMed

Wu, Tong; Zhao, Wenfeng; Guo, Hongsun; Lim, Hubert H; Yang, Zhi

2017-12-01

Neural recording system miniaturization and integration with low-power wireless technologies require compressing neural data before transmission. Feature extraction is a procedure to represent data in a low-dimensional space; its integration into a recording chip can be an efficient approach to compress neural data. In this paper, we propose a streaming principal component analysis algorithm and its microchip implementation to compress multichannel local field potential (LFP) and spike data. The circuits have been designed in a 65-nm CMOS technology and occupy a silicon area of 0.06 mm. Throughout the experiments, the chip compresses LFPs by 10 at the expense of as low as 1% reconstruction errors and 144-nW/channel power consumption; for spikes, the achieved compression ratio is 25 with 8% reconstruction errors and 3.05-W/channel power consumption. In addition, the algorithm and its hardware architecture can swiftly adapt to nonstationary spiking activities, which enables efficient hardware sharing among multiple channels to support a high-channel count recorder.
On supertaskers and the neural basis of efficient multitasking.

PubMed

Medeiros-Ward, Nathan; Watson, Jason M; Strayer, David L

2015-06-01

The present study used brain imaging to determine the neural basis of individual differences in multitasking, the ability to successfully perform at least two attention-demanding tasks at once. Multitasking is mentally taxing and, therefore, should recruit the prefrontal cortex to maintain task goals when coordinating attentional control and managing the cognitive load. To investigate this possibility, we used functional neuroimaging to assess neural activity in both extraordinary multitaskers (Supertaskers) and control subjects who were matched on working memory capacity. Participants performed a challenging dual N-back task in which auditory and visual stimuli were presented simultaneously, requiring independent and continuous maintenance, updating, and verification of the contents of verbal and spatial working memory. With the task requirements and considerable cognitive load that accompanied increasing N-back, relative to the controls, the multitasking of Supertaskers was characterized by more efficient recruitment of anterior cingulate and posterior frontopolar prefrontal cortices. Results are interpreted using neuropsychological and evolutionary perspectives on individual differences in multitasking ability and the neural correlates of attentional control.
Heparan Sulfate Proteoglycans as Drivers of Neural Progenitors Derived From Human Mesenchymal Stem Cells.

PubMed

Okolicsanyi, Rachel K; Oikari, Lotta E; Yu, Chieh; Griffiths, Lyn R; Haupt, Larisa M

2018-01-01

Background: Due to their relative ease of isolation and their high ex vivo and in vitro expansive potential, human mesenchymal stem cells (hMSCs) are an attractive candidate for therapeutic applications in the treatment of brain injury and neurological diseases. Heparan sulfate proteoglycans (HSPGs) are a family of ubiquitous proteins involved in a number of vital cellular processes including proliferation and stem cell lineage differentiation. Methods: Following the determination that hMSCs maintain neural potential throughout extended in vitro expansion, we examined the role of HSPGs in mediating the neural potential of hMSCs. hMSCs cultured in basal conditions (undifferentiated monolayer cultures) were found to co-express neural markers and HSPGs throughout expansion with modulation of the in vitro niche through the addition of exogenous HS influencing cellular HSPG and neural marker expression. Results: Conversion of hMSCs into hMSC Induced Neurospheres (hMSC IN) identified distinctly localized HSPG staining within the spheres along with altered gene expression of HSPG core protein and biosynthetic enzymes when compared to undifferentiated hMSCs. Conclusion: Comparison of markers of pluripotency, neural self-renewal and neural lineage specification between hMSC IN, hMSC and human neural stem cell (hNSC H9) cultures suggest that in vitro generated hMSC IN may represent an intermediary neurogenic cell type, similar to a common neural progenitor cell. In addition, this data demonstrates HSPGs and their biosynthesis machinery, are associated with hMSC IN formation. The identification of specific HSPGs driving hMSC lineage-specification will likely provide new markers to allow better use of hMSCs in therapeutic applications and improve our understanding of human neurogenesis.
Application of neural network technique to determine a corrector surface for global geopotential model using GPS/levelling measurements in Egypt

NASA Astrophysics Data System (ADS)

Elshambaky, Hossam Talaat

2018-01-01

Owing to the appearance of many global geopotential models, it is necessary to determine the most appropriate model for use in Egyptian territory. In this study, we aim to investigate three global models, namely EGM2008, EIGEN-6c4, and GECO. We use five mathematical transformation techniques, i.e., polynomial expression, exponential regression, least-squares collocation, multilayer feed forward neural network, and radial basis neural networks to make the conversion from regional geometrical geoid to global geoid models and vice versa. From a statistical comparison study based on quality indexes between previous transformation techniques, we confirm that the multilayer feed forward neural network with two neurons is the most accurate of the examined transformation technique, and based on the mean tide condition, EGM2008 represents the most suitable global geopotential model for use in Egyptian territory to date. The final product gained from this study was the corrector surface that was used to facilitate the transformation process between regional geometrical geoid model and the global geoid model.
An integrated interface for peripheral neural system recording and stimulation: system design, electrical tests and in-vivo results.

PubMed

Carboni, Caterina; Bisoni, Lorenzo; Carta, Nicola; Puddu, Roberto; Raspopovic, Stanisa; Navarro, Xavier; Raffo, Luigi; Barbaro, Massimo

2016-04-01

The prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of 2 integrated circuits: a standard CMOS device for neural recording and a HVCMOS device for neural stimulation. The integrated circuits have been realized in 2 different 0.35μ m CMOS processes available from ams. The complete system incorporates 8 channels each including the analog front-end, the A/D conversion, based on a sigma delta architecture and a programmable stimulation module implemented as a 5-bit current DAC; two voltage boosters supply the output stimulation stage with a programmable voltage scalable up to 17V. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μ V r m s , and to selectively elicit the tibial and plantar muscles using different active sites of the electrode.
Dynamics of modularity of neural activity in the brain during development

NASA Astrophysics Data System (ADS)

Deem, Michael; Chen, Man

2014-03-01

Theory suggests that more modular systems can have better response functions at short times. This theory suggests that greater cognitive performance may be achieved for more modular neural activity, and that modularity of neural activity may, therefore, likely increase with development in children. We study the relationship between age and modularity of brain neural activity in developing children. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. We interpret these results as evidence of selection for plasticity in the cognitive function of the human brain. We present a model to illustrate how modularity can provide greater cognitive performance at short times and enhance fast, low-level, automatic cognitive processes. Conversely, high-level, effortful, conscious cognitive processes may not benefit from modularity. We use quasispecies theory to predict how the average modularity evolves with age, given a fitness function extracted from the model. We suggest further experiments exploring the effect of modularity on cognitive performance and suggest that modularity may be a potential biomarker for injury, rehabilitation, or disease.
Adaptive Neural Control for Space Structure Vibration Suppression.

DTIC Science & Technology

1996-08-01

based implementations is the subject of the next chapter. 17 ANC Final Report Kam VdI k (~k)A .. loco[ Excitation --Control ON 1 15 20 25 30 Figure 2...must’write something to the update register to cause ~ 1* a conversion. * #def ine MODE OxOOOO 1* Keep things in range * #def ine NAXDA 2048 #define DASENS
Nanocrystal Size-Dependent Efficiency of Quantum Dot Sensitized Solar Cells in the Strongly Coupled CdSe Nanocrystals/TiO2 System.

PubMed

Yun, Hyeong Jin; Paik, Taejong; Diroll, Benjamin; Edley, Michael E; Baxter, Jason B; Murray, Christopher B

2016-06-15

Light absorption and electron injection are important criteria determining solar energy conversion efficiency. In this research, monodisperse CdSe quantum dots (QDs) are synthesized with five different diameters, and the size-dependent solar energy conversion efficiency of CdSe quantum dot sensitized solar cell (QDSSCs) is investigated by employing the atomic inorganic ligand, S(2-). Absorbance measurements and transmission electron microscopy show that the diameters of the uniform CdSe QDs are 2.5, 3.2, 4.2, 6.4, and 7.8 nm. Larger CdSe QDs generate a larger amount of charge under the irradiation of long wavelength photons, as verified by the absorbance results and the measurements of the external quantum efficiencies. However, the smaller QDs exhibit faster electron injection kinetics from CdSe QDs to TiO2 because of the high energy level of CBCdSe, as verified by time-resolved photoluminescence and internal quantum efficiency results. Importantly, the S(2-) ligand significantly enhances the electronic coupling between the CdSe QDs and TiO2, yielding an enhancement of the charge transfer rate at the interfacial region. As a result, the S(2-) ligand helps improve the new size-dependent solar energy conversion efficiency, showing best performance with 4.2-nm CdSe QDs, whereas conventional ligand, mercaptopropionic acid, does not show any differences in efficiency according to the size of the CdSe QDs. The findings reported herein suggest that the atomic inorganic ligand reinforces the influence of quantum confinement on the solar energy conversion efficiency of QDSSCs.
Integrating a dual-silicon photoelectrochemical cell into a redox flow battery for unassisted photocharging

PubMed Central

Liao, Shichao; Zong, Xu; Seger, Brian; Pedersen, Thomas; Yao, Tingting; Ding, Chunmei; Shi, Jingying; Chen, Jian; Li, Can

2016-01-01

Solar rechargeable flow cells (SRFCs) provide an attractive approach for in situ capture and storage of intermittent solar energy via photoelectrochemical regeneration of discharged redox species for electricity generation. However, overall SFRC performance is restricted by inefficient photoelectrochemical reactions. Here we report an efficient SRFC based on a dual-silicon photoelectrochemical cell and a quinone/bromine redox flow battery for in situ solar energy conversion and storage. Using narrow bandgap silicon for efficient photon collection and fast redox couples for rapid interface charge injection, our device shows an optimal solar-to-chemical conversion efficiency of ∼5.9% and an overall photon–chemical–electricity energy conversion efficiency of ∼3.2%, which, to our knowledge, outperforms previously reported SRFCs. The proposed SRFC can be self-photocharged to 0.8 V and delivers a discharge capacity of 730 mAh l−1. Our work may guide future designs for highly efficient solar rechargeable devices. PMID:27142885

Methods and analysis of factors impact on the efficiency of the photovoltaic generation

NASA Astrophysics Data System (ADS)

Tianze, Li; Xia, Zhang; Chuan, Jiang; Luan, Hou

2011-02-01

First of all, the thesis elaborates two important breakthroughs which happened In the field of the application of solar energy in the 1950s.The 21st century the development of solar photovoltaic power generation will have the following characteristics: the continued high growth of industrial development, the significantly reducing cost of the solar cell, the large-scale high-tech development of photovoltaic industries, the breakthroughs of the film battery technology, the rapid development of solar PV buildings integration and combined to the grids. The paper makes principles of solar cells the theoretical analysis. On the basis, we study the conversion efficiency of solar cells, find the factors impact on the efficiency of the photovoltaic generation, solve solar cell conversion efficiency of technical problems through the development of new technology, and open up new ways to improve the solar cell conversion efficiency. Finally, the paper connecting with the practice establishes policies and legislation to the use of encourage renewable energy, development strategy, basic applied research etc.
High-strength fermentable wastewater reclamation through a sequential process of anaerobic fermentation followed by microalgae cultivation.

PubMed

Qi, Wenqiang; Chen, Taojing; Wang, Liang; Wu, Minghong; Zhao, Quanyu; Wei, Wei

2017-03-01

In this study, the sequential process of anaerobic fermentation followed by microalgae cultivation was evaluated from both nutrient and energy recovery standpoints. The effects of different fermentation type on the biogas generation, broth metabolites' composition, algal growth and nutrients' utilization, and energy conversion efficiencies for the whole processes were discussed. When the fermentation was designed to produce hydrogen-dominating biogas, the total energy conversion efficiency (TECE) of the sequential process was higher than that of the methane fermentation one. With the production of hydrogen in anaerobic fermentation, more organic carbon metabolites were left in the broth to support better algal growth with more efficient incorporation of ammonia nitrogen. By applying the sequential process, the heat value conversion efficiency (HVCE) for the wastewater could reach 41.2%, if methane was avoided in the fermentation biogas. The removal efficiencies of organic metabolites and NH 4 + -N in the better case were 100% and 98.3%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.
Power conversion efficiency exceeding the Shockley-Queisser limit in a ferroelectric insulator

NASA Astrophysics Data System (ADS)

Spanier, Jonathan E.; Fridkin, Vladimir M.; Rappe, Andrew M.; Akbashev, Andrew R.; Polemi, Alessia; Qi, Yubo; Gu, Zongquan; Young, Steve M.; Hawley, Christopher J.; Imbrenda, Dominic; Xiao, Geoffrey; Bennett-Jackson, Andrew L.; Johnson, Craig L.

2016-09-01

Ferroelectric absorbers, which promote carrier separation and exhibit above-gap photovoltages, are attractive candidates for constructing efficient solar cells. Using the ferroelectric insulator BaTiO3 we show how photogeneration and the collection of hot, non-equilibrium electrons through the bulk photovoltaic effect (BPVE) yields a greater-than-unity quantum efficiency. Despite absorbing less than a tenth of the solar spectrum, the power conversion efficiency of the BPVE device under 1 sun illumination exceeds the Shockley-Queisser limit for a material of this bandgap. We present data for devices that feature a single-tip electrode contact and an array with 24 tips (total planar area of 1 × 1 μm2) capable of generating a current density of 17 mA cm-2 under illumination of AM1.5 G. In summary, the BPVE at the nanoscale provides an exciting new route for obtaining high-efficiency photovoltaic solar energy conversion.
Compact, Energy-Efficient High-Frequency Switched Capacitor Neural Stimulator With Active Charge Balancing.

PubMed

Hsu, Wen-Yang; Schmid, Alexandre

2017-08-01

Safety and energy efficiency are two major concerns for implantable neural stimulators. This paper presents a novel high-frequency, switched capacitor (HFSC) stimulation and active charge balancing scheme, which achieves high energy efficiency and well-controlled stimulation charge in the presence of large electrode impedance variations. Furthermore, the HFSC can be implemented in a compact size without any external component to simultaneously enable multichannel stimulation by deploying multiple stimulators. The theoretical analysis shows significant benefits over the constant-current and voltage-mode stimulation methods. The proposed solution was fabricated using a 0.18 μm high-voltage technology, and occupies only 0.035 mm 2 for a single stimulator. The measurement result shows 50% peak energy efficiency and confirms the effectiveness of active charge balancing to prevent the electrode dissolution.
Large-scale cauliflower-shaped hierarchical copper nanostructures for efficient photothermal conversion

NASA Astrophysics Data System (ADS)

Fan, Peixun; Wu, Hui; Zhong, Minlin; Zhang, Hongjun; Bai, Benfeng; Jin, Guofan

2016-07-01

Efficient solar energy harvesting and photothermal conversion have essential importance for many practical applications. Here, we present a laser-induced cauliflower-shaped hierarchical surface nanostructure on a copper surface, which exhibits extremely high omnidirectional absorption efficiency over a broad electromagnetic spectral range from the UV to the near-infrared region. The measured average hemispherical absorptance is as high as 98% within the wavelength range of 200-800 nm, and the angle dependent specular reflectance stays below 0.1% within the 0-60° incident angle. Such a structured copper surface can exhibit an apparent heating up effect under the sunlight illumination. In the experiment of evaporating water, the structured surface yields an overall photothermal conversion efficiency over 60% under an illuminating solar power density of ~1 kW m-2. The presented technology provides a cost-effective, reliable, and simple way for realizing broadband omnidirectional light absorptive metal surfaces for efficient solar energy harvesting and utilization, which is highly demanded in various light harvesting, anti-reflection, and photothermal conversion applications. Since the structure is directly formed by femtosecond laser writing, it is quite suitable for mass production and can be easily extended to a large surface area.Efficient solar energy harvesting and photothermal conversion have essential importance for many practical applications. Here, we present a laser-induced cauliflower-shaped hierarchical surface nanostructure on a copper surface, which exhibits extremely high omnidirectional absorption efficiency over a broad electromagnetic spectral range from the UV to the near-infrared region. The measured average hemispherical absorptance is as high as 98% within the wavelength range of 200-800 nm, and the angle dependent specular reflectance stays below 0.1% within the 0-60° incident angle. Such a structured copper surface can exhibit an apparent heating up effect under the sunlight illumination. In the experiment of evaporating water, the structured surface yields an overall photothermal conversion efficiency over 60% under an illuminating solar power density of ~1 kW m-2. The presented technology provides a cost-effective, reliable, and simple way for realizing broadband omnidirectional light absorptive metal surfaces for efficient solar energy harvesting and utilization, which is highly demanded in various light harvesting, anti-reflection, and photothermal conversion applications. Since the structure is directly formed by femtosecond laser writing, it is quite suitable for mass production and can be easily extended to a large surface area. Electronic supplementary information (ESI) available: XRD patterns of the fs laser structured Cu surface as produced and after the photothermal conversion test, directly measured temperature values on Cu surfaces, temperature rise on Cu surfaces at varied solar irradiation angles, comparison of the white light and IR images of the structured Cu surface with the polished Cu surface, temperature rise on the peripheral zones of the blue coating surface. See DOI: 10.1039/c6nr03662g
Condenser design for AMTEC power conversion

NASA Technical Reports Server (NTRS)

Crowley, Christopher J.

1991-01-01

The condenser and the electrodes are the two elements of an alkali metal thermal-to-electric conversion (AMTEC) cell which most greatly affect the energy conversion performance. A condenser is described which accomplishes two critical functions in an AMTEC cell: management of the fluid under microgravity conditions and optimization of conversion efficiency. The first function is achieved via the use of a controlled surface shape, along with drainage grooves and arteries to collect the fluid. Capillary forces manage the fluid in microgravity and dominate hydrostatic effects on the ground so the device is ground-testable. The second function is achieved via a smooth film of highly reflective liquid sodium on the condensing surface, resulting in minimization of parasitic heat losses due to radiation heat transfer. Power conversion efficiencies of 25 percent to 30 percent are estimated with this condenser using present technology for the electrodes.
Potential for Increasing the Output of Existing Hydroelectric Plants.

DTIC Science & Technology

1981-06-01

existing units to higher generating capacity by rehabilitating, modifying or replacing turbines and/or generators; increasing the effective...loss in converting fluid energy (flow and head) to mechanical energy ( turbine output) to electrical energy (generator output). The significant practical...opportunity is improvement of the energy conversion efficiency of the hydraulic turbine since the energy conversion efficiency of electrical
Scaling Studies of Efficient Raman Converters.

DTIC Science & Technology

1983-07-01

allowed without deleterious effects due to competing processes. These processes include amplified spontaneous emission (Raman superfluorescence...tively introducing noise injection that could potentially degrade conversion efficiency and/or beam quality. The conditions under which these competing ...good beam qual- ity. Section 5.1 discusses Stokes injection level requirements in terms of suppressing competing effects which can reduce conversion
Coherent Beam Combining of Fiber Amplifiers via LOCSET (Postprint)

DTIC Science & Technology

2012-07-10

load on final optics , and atmospheric turbulence compensation [20]. More importantly, tiled array systems are being investigated for extension to...compactness, near diffraction limited beam quality, superior thermal- optical properties, and high optical to optical conversion efficiencies. Despite...including: compactness, near diffraction limited beam quality, superior thermal- optical properties, and high optical to optical conversion efficiencies
The effect of the DSSC photoanode area based on TiO2/Ag on the conversion efficiency of solar energy into electrical energy

NASA Astrophysics Data System (ADS)

Ibrayev, N.; Serikov, T.; Zavgorodniy, A.; Sadykova, A.

2018-01-01

A module based on dye-sensitized solar cells with Ag/TiO2 structure was developed. It is shown that the addition of the core-shell structure to the semiconductor film of titanium dioxide, where the nanoparticle Ag serves as the core, and the TiO2 is shell, increases the coefficient of solar energy conversion into electrical energy. The effect of the photoanode area on the efficiency of conversion of solar energy into electrical energy is studied. It is shown that the density of the photocurrent decreases with increasing of the photoanode area, which leads to a drop in the efficiency of solar cells.
The influence of cellular uptake on gold nanorods photostability and photoacoustic conversion efficiency

NASA Astrophysics Data System (ADS)

Cavigli, Lucia; Ratto, Fulvio; Tatini, Francesca; Matteini, Paolo; Cini, Alberto; Giovannelli, Ilaria; de Angelis, Marella; Rossi, Francesca; Centi, Sonia; Pini, Roberto

2015-03-01

Their intense optical absorbance in the near-infrared window and chemical versatility make gold nanorods attractive for biomedical applications, such as photothermal therapies and photoacoustic imaging. However, their limited photostability remains a drawback of practical concern. In fact, when gold nanorods are irradiated with nanosecond laser pulses in resonance with their plasmon oscillations, there may occur reshaping into spherical particles or even fragmentation at higher optical fluences, which cause substantial modifications of their optical features with a loss of photoacoustic conversion efficiency. In this contribution, we focus on how the gold nanorods photostability is affected when these particles are modified for cellular uptake, by investigating their stability and photoacoustic conversion efficiency under near infrared pulsed irradiation at different laser fluences.
An efficient copper phthalocyanine additive of perovskite precursor for improving the photovoltaic performance of planar perovskite solar cells

NASA Astrophysics Data System (ADS)

Wu, Shufang; Liu, Qingwei; Zheng, Ya; Li, Renjie; Peng, Tianyou

2017-08-01

Solution processable planar heterojunction perovskite solar cell has drawn much attention as a promising low-cost photovoltaic device, and much effort has been made to improve its power conversion efficiency by choosing appropriate additives for the perovskite precursor solution. Different to those additives reported, a soluble and thermal stable tert-butyl substituted copper phthalocyanine (CuPc(tBu)4) as additive is first introduced into the perovskite precursor solution of a planar perovskite solar cell that is fabricated via the one-step solution process. It is found that the pristine device without CuPc(tBu)4 additive exhibits a power conversion efficiency of 15.3%, while an extremely low concentration (4.4 × 10-3 mM) of CuPc(tBu)4 in the precursor solution leads to the corresponding device achieving an enhanced power conversion efficiency of 17.3%. CuPc(tBu)4 as an additive can improve the quality of perovskite layer with higher crystallinity and surface coverage, then resulting in enhanced light absorption and reduced charge recombination, and thus the better power conversion efficiency. The finding presented here provides a new choice for improving the quality of perovskite layer and the photovoltaic performance of the planar heterojunction perovskite solar cells.
Applications of novel effects derived from Si ingot growth inside Si melt without contact with crucible wall using noncontact crucible method to high-efficiency solar cells

NASA Astrophysics Data System (ADS)

Nakajima, Kazuo; Ono, Satoshi; Kaneko, Yuzuru; Murai, Ryota; Shirasawa, Katsuhiko; Fukuda, Tetsuo; Takato, Hidetaka; Jensen, Mallory A.; Youssef, Amanda; Looney, Erin E.; Buonassisi, Tonio; Martel, Benoit; Dubois, Sèbastien; Jouini, Anis

2017-06-01

The noncontact crucible (NOC) method was proposed for obtaining Si single bulk crystals with a large diameter and volume using a cast furnace and solar cells with high conversion efficiency and yield. This method has several novel characteristics that originate from its key feature that ingots can be grown inside a Si melt without contact with a crucible wall. Si ingots for solar cells were grown by utilizing the merits resulting from these characteristics. Single ingots with high quality were grown by the NOC method after furnace cleaning, and the minority carrier lifetime was measured to investigate reduction of the number of impurities. A p-type ingot with a convex growth interface in the growth direction was also grown after furnace cleaning. For p-type solar cells prepared using wafers cut from the ingot, the highest and average conversion efficiencies were 19.14% and 19.0%, respectively, which were obtained using the same solar cell structure and process as those employed to obtain a conversion efficiency of 19.1% for a p-type Czochralski (CZ) wafer. Using the cast furnace, solar cells with a conversion efficiency and yield as high as those of CZ solar cells were obtained by the NOC method.
Interfacial engineering of CuO nanorod/ZnO nanowire hybrid nanostructure photoanode in dye-sensitized solar cell

NASA Astrophysics Data System (ADS)

Kilic, Bayram; Turkdogan, Sunay; Astam, Aykut; Baran, Sümeyra Seniha; Asgin, Mansur; Gur, Emre; Kocak, Yusuf

2018-01-01

Developing efficient and cost-effective photoanode plays a vital role determining the photocurrent and photovoltage in dye-sensitized solar cells (DSSCs). Here, we demonstrate DSSCs that achieve relatively high power conversion efficiencies (PCEs) by using one-dimensional (1D) zinc oxide (ZnO) nanowires and copper (II) oxide (CuO) nanorods hybrid nanostructures. CuO nanorod-based thin films were prepared by hydrothermal method and used as a blocking layer on top of the ZnO nanowires' layer. The use of 1D ZnO nanowire/CuO nanorod hybrid nanostructures led to an exceptionally high photovoltaic performance of DSSCs with a remarkably high open-circuit voltage (0.764 V), short current density (14.76 mA/cm2 under AM1.5G conditions), and relatively high solar to power conversion efficiency (6.18%) . The enhancement of the solar to power conversion efficiency can be explained in terms of the lag effect of the interfacial recombination dynamics of CuO nanorod-blocking layer on ZnO nanowires. This work shows more economically feasible method to bring down the cost of the nano-hybrid cells and promises for the growth of other important materials to further enhance the solar to power conversion efficiency.
Effect of Copper Oxide Nanoparticles as a barrier for Efficiency Improvement in ZnO Dye-Sensitized Solar Cells

NASA Astrophysics Data System (ADS)

Sonthila, A.; Ruankham, P.; Choopun, S.; Wongratanaphisan, D.; Phadungdhitidhada, S.; Gardchareon, A.

2017-09-01

CuO nanoparticles (CuO NPs) were used as a barrier layer in ZnO dye-sensitized solar cells (DSSCs) to obtain high power conversion efficiency. The barrier layer was investigated in terms of the size of CuO NPs by varying power of pulsed Nd:YAG (1064 nm) laser ablation. Morphological and optical properties of CuO NPs were characterized by transmission electron microscopy (TEM), UV-visible spectrophotometry (UV-vis) and dynamic light scattering (DLS). It was found that the CuO NPs are rather spherical in shape with diameter in between 20 - 132 nm. In addition, the energy gap of CuO decreases with the increase of CuO NPs size. The power conversion efficiency of ZnO DSSCs was measured under illumination of simulated sunlight obtained from a solar simulator with the radiant power of 100 mW/cm2. The results showed that the ZnO DSSC with the CuO NPs with size of 37 nm exhibits the optimum power conversion efficiency of 1.01% which is higher than that of one without CuO NPs. Moreover, the power conversion efficiency of the ZnO DSSCs decreases with the increase of CuO NPs size.
Efficient and Selective Electrochemical and Photoelectrochemical Reduction of 5-Hydroxymethylfurfural to 2,5-Bis(hydroxymethyl)furan using Water as the Hydrogen Source

DOE PAGES

Roylance, John J.; Kim, Tae Woo; Choi, Kyoung-Shin

2016-02-17

Reductive biomass conversion has been conventionally conducted using H 2 gas under high-temperature and-pressure conditions. Here, efficient electrochemical reduction of 5-hydroxymethylfurfural (HMF), a key intermediate for biomass conversion, to 2,5-bis(hydroxymethyl)furan (BHMF), an important monomer for industrial processes, was demonstrated using Ag catalytic electrodes. This process uses water as the hydrogen source under ambient conditions and eliminates the need to generate and consume H 2 for hydrogenation, providing a practical and efficient route for BHMF production. By systematic investigation of HMF reduction on the Ag electrode surface, BHMF production was achieved with the Faradaic efficiency and selectivity nearing 100%, and plausiblemore » reduction mechanisms were also elucidated. Furthermore, construction of a photoelectrochemical cell (PEC) composed of an n-type BiVO 4 semiconductor anode, which uses photogenerated holes for water oxidation, and a catalytic Ag cathode, which uses photoexcited electrons from BiVO 4 for the reduction of HMF to BHMF, was demonstrated to utilize solar energy to significantly decrease the external voltage necessary for HMF reduction. This shows the possibility of coupling electrochemical HMF reduction and solar energy conversion, which can provide more efficient and environmentally benign routes for reductive biomass conversion.« less
An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture.

PubMed

Zhang, Xiaopu; Lin, Jun; Chen, Zubin; Sun, Feng; Zhu, Xi; Fang, Gengfa

2018-06-05

Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.
Equivalent Skin Analysis of Wing Structures Using Neural Networks

NASA Technical Reports Server (NTRS)

Liu, Youhua; Kapania, Rakesh K.

2000-01-01

An efficient method of modeling trapezoidal built-up wing structures is developed by coupling. in an indirect way, an Equivalent Plate Analysis (EPA) with Neural Networks (NN). Being assumed to behave like a Mindlin-plate, the wing is solved using the Ritz method with Legendre polynomials employed as the trial functions. This analysis method can be made more efficient by avoiding most of the computational effort spent on calculating contributions to the stiffness and mass matrices from each spar and rib. This is accomplished by replacing the wing inner-structure with an "equivalent" material that combines to the skin and whose properties are simulated by neural networks. The constitutive matrix, which relates the stress vector to the strain vector, and the density of the equivalent material are obtained by enforcing mass and stiffness matrix equities with rec,ard to the EPA in a least-square sense. Neural networks for the material properties are trained in terms of the design variables of the wing structure. Examples show that the present method, which can be called an Equivalent Skin Analysis (ESA) of the wing structure, is more efficient than the EPA and still fairly good results can be obtained. The present ESA is very promising to be used at the early stages of wing structure design.
Review of solar fuel-producing quantum conversion processes

NASA Technical Reports Server (NTRS)

Peterson, D. B.; Biddle, J. R.; Fujita, T.

1984-01-01

The status and potential of fuel-producing solar photochemical processes are discussed. Research focused on splitting water to produce dihydrogen and is at a relatively early stage of development. Current emphasis is primarily directed toward understanding the basic chemistry underlying such quantum conversion processes. Theoretical analyses by various investigators predict a limiting thermodynamic efficiency of 31% for devices with a single photosystem operating with unfocused sunlight at 300 K. When non-idealities are included, it appears unlikely that actual devices will have efficiencies greater than 12 to 15%. Observed efficiencies are well below theoretical limits. Cyclic homogeneous photochemical processes for splitting water have efficiencies considerably less than 1%. Efficiency can be significantly increased by addition of a sacrificial reagent; however, such systems are no longer cyclic and it is doubtful that they would be economical on a commercial scale. The observed efficiencies for photoelectrochemical processes are also low but such systems appear more promising than homogeneous photochemical systems. Operating and systems options, including operation at elevated temperature and hybrid and coupled quantum-thermal conversion processes, are also considered.
Long vertically aligned titania nanotubes on transparent conducting oxide for highly efficient solar cells.

PubMed

Varghese, Oomman K; Paulose, Maggie; Grimes, Craig A

2009-09-01

Dye-sensitized solar cells consist of a random network of titania nanoparticles that serve both as a high-surface-area support for dye molecules and as an electron-transporting medium. Despite achieving high power conversion efficiencies, their performance is limited by electron trapping in the nanoparticle film. Electron diffusion lengths can be increased by transporting charge through highly ordered nanostructures such as titania nanotube arrays. Although titania nanotube array films have been shown to enhance the efficiencies of both charge collection and light harvesting, it has not been possible to grow them on transparent conducting oxide glass with the lengths needed for high-efficiency device applications (tens of micrometres). Here, we report the fabrication of transparent titania nanotube array films on transparent conducting oxide glass with lengths between 0.3 and 33.0 microm using a novel electrochemistry approach. Dye-sensitized solar cells containing these arrays yielded a power conversion efficiency of 6.9%. The incident photon-to-current conversion efficiency ranged from 70 to 80% for wavelengths between 450 and 650 nm.

Endocytotic potential governs magnetic particle loading in dividing neural cells: studying modes of particle inheritance

PubMed Central

Tickle, Jacqueline A; Jenkins, Stuart I; Polyak, Boris; Pickard, Mark R; Chari, Divya M

2016-01-01

Aim: To achieve high and sustained magnetic particle loading in a proliferative and endocytotically active neural transplant population (astrocytes) through tailored magnetite content in polymeric iron oxide particles. Materials & methods: MPs of varying magnetite content were applied to primary-derived rat cortical astrocytes ± static/oscillating magnetic fields to assess labeling efficiency and safety. Results: Higher magnetite content particles display high but safe accumulation in astrocytes, with longer-term label retention versus lower/no magnetite content particles. Magnetic fields enhanced loading extent. Dynamic live cell imaging of dividing labeled astrocytes demonstrated that particle distribution into daughter cells is predominantly ‘asymmetric’. Conclusion: These findings could inform protocols to achieve efficient MP loading into neural transplant cells, with significant implications for post-transplantation tracking/localization. PMID:26785794
Silicon Nanowire/Polymer Hybrid Solar Cell-Supercapacitor: A Self-Charging Power Unit with a Total Efficiency of 10.5.

PubMed

Liu, Ruiyuan; Wang, Jie; Sun, Teng; Wang, Mingjun; Wu, Changsheng; Zou, Haiyang; Song, Tao; Zhang, Xiaohong; Lee, Shuit-Tong; Wang, Zhong Lin; Sun, Baoquan

2017-07-12

An integrated self-charging power unit, combining a hybrid silicon nanowire/polymer heterojunction solar cell with a polypyrrole-based supercapacitor, has been demonstrated to simultaneously harvest solar energy and store it. By efficiency enhancement of the hybrid nanowire solar cells and a dual-functional titanium film serving as conjunct electrode of the solar cell and supercapacitor, the integrated system is able to yield a total photoelectric conversion to storage efficiency of 10.5%, which is the record value in all the integrated solar energy conversion and storage system. This system may not only serve as a buffer that diminishes the solar power fluctuations from light intensity, but also pave its way toward cost-effective high efficiency self-charging power unit. Finally, an integrated device based on ultrathin Si substrate is demonstrated to expand its feasibility and potential application in flexible energy conversion and storage devices.
Highly efficient frequency conversion with bandwidth compression of quantum light

PubMed Central

Allgaier, Markus; Ansari, Vahid; Sansoni, Linda; Eigner, Christof; Quiring, Viktor; Ricken, Raimund; Harder, Georg; Brecht, Benjamin; Silberhorn, Christine

2017-01-01

Hybrid quantum networks rely on efficient interfacing of dissimilar quantum nodes, as elements based on parametric downconversion sources, quantum dots, colour centres or atoms are fundamentally different in their frequencies and bandwidths. Although pulse manipulation has been demonstrated in very different systems, to date no interface exists that provides both an efficient bandwidth compression and a substantial frequency translation at the same time. Here we demonstrate an engineered sum-frequency-conversion process in lithium niobate that achieves both goals. We convert pure photons at telecom wavelengths to the visible range while compressing the bandwidth by a factor of 7.47 under preservation of non-classical photon-number statistics. We achieve internal conversion efficiencies of 61.5%, significantly outperforming spectral filtering for bandwidth compression. Our system thus makes the connection between previously incompatible quantum systems as a step towards usable quantum networks. PMID:28134242
Use of neural image analysis methods in the process to determine the dry matter content in the compost

NASA Astrophysics Data System (ADS)

Wojcieszak, D.; Przybył, J.; Lewicki, A.; Ludwiczak, A.; Przybylak, A.; Boniecki, P.; Koszela, K.; Zaborowicz, M.; Przybył, K.; Witaszek, K.

2015-07-01

The aim of this research was investigate the possibility of using methods of computer image analysis and artificial neural networks for to assess the amount of dry matter in the tested compost samples. The research lead to the conclusion that the neural image analysis may be a useful tool in determining the quantity of dry matter in the compost. Generated neural model may be the beginning of research into the use of neural image analysis assess the content of dry matter and other constituents of compost. The presented model RBF 19:19-2-1:1 characterized by test error 0.092189 may be more efficient.
The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.
Intelligence and working memory systems: evidence of neural efficiency in alpha band ERD.

PubMed

Grabner, R H; Fink, A; Stipacek, A; Neuper, C; Neubauer, A C

2004-07-01

Starting from the well-established finding that brighter individuals display a more efficient brain function when performing cognitive tasks (i.e., neural efficiency), we investigated the relationship between intelligence and cortical activation in the context of working memory (WM) tasks. Fifty-five male (n=28) and female (n=27) participants worked on (1) a classical forward digit span task demanding only short-term memory (STM), (2) an attention-switching task drawing on the central executive (CE) of WM and (3) a WM task involving both STM storage and CE processes. During performance of these three types of tasks, cortical activation was quantified by the extent of Event-Related Desynchronization (ERD) in the alpha band of the human EEG. Correlational analyses revealed associations between the amount of ERD in the upper alpha band and intelligence in several brain regions. In all tasks, the males were more likely to display the negative intelligence-cortical activation relationship. Furthermore, stronger associations between ERD and intelligence were found for fluid rather than crystallized intelligence. Analyses also point to topographical differences in neural efficiency depending on sex, task type and the associated cognitive subsystems engaged during task performance.
Hybrid response surface methodology-artificial neural network optimization of drying process of banana slices in a forced convective dryer.

PubMed

Taheri-Garavand, Amin; Karimi, Fatemeh; Karimi, Mahmoud; Lotfi, Valiullah; Khoobbakht, Golmohammad

2018-06-01

The aim of the study is to fit models for predicting surfaces using the response surface methodology and the artificial neural network to optimize for obtaining the maximum acceptability using desirability functions methodology in a hot air drying process of banana slices. The drying air temperature, air velocity, and drying time were chosen as independent factors and moisture content, drying rate, energy efficiency, and exergy efficiency were dependent variables or responses in the mentioned drying process. A rotatable central composite design as an adequate method was used to develop models for the responses in the response surface methodology. Moreover, isoresponse contour plots were useful to predict the results by performing only a limited set of experiments. The optimum operating conditions obtained from the artificial neural network models were moisture content 0.14 g/g, drying rate 1.03 g water/g h, energy efficiency 0.61, and exergy efficiency 0.91, when the air temperature, air velocity, and drying time values were equal to -0.42 (74.2 ℃), 1.00 (1.50 m/s), and -0.17 (2.50 h) in the coded units, respectively.
Decision-making conflict and the neural efficiency hypothesis of intelligence: a functional near-infrared spectroscopy investigation.

PubMed

Di Domenico, Stefano I; Rodrigo, Achala H; Ayaz, Hasan; Fournier, Marc A; Ruocco, Anthony C

2015-04-01

Research on the neural efficiency hypothesis of intelligence (NEH) has revealed that the brains of more intelligent individuals consume less energy when performing easy cognitive tasks but more energy when engaged in difficult mental operations. However, previous studies testing the NEH have relied on cognitive tasks that closely resemble psychometric tests of intelligence, potentially confounding efficiency during intelligence-test performance with neural efficiency per se. The present study sought to provide a novel test of the NEH by examining patterns of prefrontal activity while participants completed an experimental paradigm that is qualitatively distinct from the contents of psychometric tests of intelligence. Specifically, participants completed a personal decision-making task (e.g., which occupation would you prefer, dancer or chemist?) in which they made a series of forced choices according to their subjective preferences. The degree of decisional conflict (i.e., choice difficulty) between the available response options was manipulated on the basis of participants' unique preference ratings for the target stimuli, which were obtained prior to scanning. Evoked oxygenation of the prefrontal cortex was measured using 16-channel continuous-wave functional near-infrared spectroscopy. Consistent with the NEH, intelligence predicted decreased activation of the right inferior frontal gyrus (IFG) during low-conflict situations and increased activation of the right-IFG during high-conflict situations. This pattern of right-IFG activity among more intelligent individuals was complemented by faster reaction times in high-conflict situations. These results provide new support for the NEH and suggest that the neural efficiency of more intelligent individuals generalizes to the performance of cognitive tasks that are distinct from intelligence tests. Copyright © 2015 Elsevier Inc. All rights reserved.
Discrimination of Stem Cell Status after Subjecting Cynomolgus Monkey Pluripotent Stem Cells to Naïve Conversion

PubMed Central

Honda, Arata; Kawano, Yoshihiro; Izu, Haruna; Choijookhuu, Narantsog; Honsho, Kimiko; Nakamura, Tomonori; Yabuta, Yukihiro; Yamamoto, Takuya; Takashima, Yasuhiro; Hirose, Michiko; Sankai, Tadashi; Hishikawa, Yoshitaka; Ogura, Atsuo; Saitou, Mitinori

2017-01-01

Experimental animal models have played an indispensable role in the development of human induced pluripotent stem cell (iPSC) research. The derivation of high-quality (so-called “true naïve state”) iPSCs of non-human primates enhances their application and safety for human regenerative medicine. Although several attempts have been made to convert human and non-human primate PSCs into a truly naïve state, it is unclear which evaluation methods can discriminate them as being truly naïve. Here we attempted to derive naïve cynomolgus monkey (Cm) (Macaca fascicularis) embryonic stem cells (ESCs) and iPSCs. Several characteristics of naïve Cm ESCs including colony morphology, appearance of naïve-related mRNAs and proteins, leukaemia inhibitory factor dependency, and mitochondrial respiration were confirmed. Next, we generated Cm iPSCs and converted them to a naïve state. Transcriptomic comparison of PSCs with early Cm embryos elucidated the partial achievement (termed naïve-like) of their conversion. When these were subjected to in vitro neural differentiation, enhanced differentiating capacities were observed after naïve-like conversion, but some lines exhibited heterogeneity. The difficulty of achieving contribution to chimeric mouse embryos was also demonstrated. These results suggest that Cm PSCs could ameliorate their in vitro neural differentiation potential even though they could not display true naïve characteristics. PMID:28349944
Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level

DOE PAGES

Chakma, Gangotree; Adnan, Md Musabbir; Wyer, Austin R.; ...

2017-11-23

Neuromorphic computing is non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing contributes effectively in this research. Here in this paper, we present a memristive neuromorphic system for improved power and area efficiency. Our particular mixed-signal approach implements neural networks with spiking events in a synchronous way. Moreover, the use of nano-scale memristive devices saves both area and power in the system. We also provide device-level considerations that make the system more energy-efficient. The proposed systemmore » additionally includes synchronous digital long term plasticity, an online learning methodology that helps the system train the neural networks during the operation phase and improves the efficiency in learning considering the power consumption and area overhead.« less
Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakma, Gangotree; Adnan, Md Musabbir; Wyer, Austin R.

Neuromorphic computing is non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing contributes effectively in this research. Here in this paper, we present a memristive neuromorphic system for improved power and area efficiency. Our particular mixed-signal approach implements neural networks with spiking events in a synchronous way. Moreover, the use of nano-scale memristive devices saves both area and power in the system. We also provide device-level considerations that make the system more energy-efficient. The proposed systemmore » additionally includes synchronous digital long term plasticity, an online learning methodology that helps the system train the neural networks during the operation phase and improves the efficiency in learning considering the power consumption and area overhead.« less
Mn-doped quantum dot sensitized solar cells: a strategy to boost efficiency over 5%.

PubMed

Santra, Pralay K; Kamat, Prashant V

2012-02-08

To make Quantum Dot Sensitized Solar Cells (QDSC) competitive, it is necessary to achieve power conversion efficiencies comparable to other emerging solar cell technologies. By employing Mn(2+) doping of CdS, we have now succeeded in significantly improving QDSC performance. QDSC constructed with Mn-doped-CdS/CdSe deposited on mesoscopic TiO(2) film as photoanode, Cu(2)S/Graphene Oxide composite electrode, and sulfide/polysulfide electrolyte deliver power conversion efficiency of 5.4%.
Enhanced efficiency of the second harmonic inhomogeneous component in an opaque cavity.

PubMed

Roppo, V; Raineri, F; Raj, R; Sagnes, I; Trull, J; Vilaseca, R; Scalora, M; Cojocaru, C

2011-05-15

In this Letter, we experimentally demonstrate the enhancement of the inhomogeneous second harmonic conversion in the opaque region of a GaAs cavity with efficiencies of the order of 0.1% at 612 nm, using 3 ps pump pulses having peak intensities of the order of 10 MW/cm(2). We show that the conversion efficiency of the inhomogeneous, phase-locked second harmonic component is a quadratic function of the cavity factor Q. © 2011 Optical Society of America
Absorber for solar power.

PubMed

Powell, W R

1974-10-01

A simple, economical absorber utilizing a new principle of operation to achieve very low reradiation losses while generating temperatures limited by material properties of quartz is described. Its performance is analyzed and indicates approximately 90% thermal efficiency and 73% conversion efficiency for an earth based unit with moderately concentrated (~tenfold) sunlight incident. It is consequently compatible with the most economic of concentrator mirrors (stamped) or mirrors deployable in space. Space applications are particularly attractive, as temperatures significantly below 300 K are possible and permit even higher conversion efficiency.
Tailoring perovskite compounds for broadband light absorption

NASA Astrophysics Data System (ADS)

Lu, Hengchang; Guo, Xiaowei; Yang, Cheng; Li, Shaorong

2018-01-01

Perovskite solar cells have experienced an outstanding advance in power conversion efficiency (PCE) by optimizing the perovskite layer morphology, composition, interfaces, and charge collection efficiency. To enhance PCE, the mixed perovskites were proposed in recent years. In this study, optoelectronic performance of pure perovskites and mixed ones were investigated. It was demonstrated that the mixed perovskites exhibit superior to the pure ones. The mixed material can absorb broadband light absorption and result in increased short circuit current density and power conversion efficiency.
Implementation of pulse-coupled neural networks in a CNAPS environment.

PubMed

Kinser, J M; Lindblad, T

1999-01-01

Pulse coupled neural networks (PCNN's) are biologically inspired algorithms very well suited for image/signal preprocessing. While several analog implementations are proposed we suggest a digital implementation in an existing environment, the connected network of adapted processors system (CNAPS). The reason for this is two fold. First, CNAPS is a commercially available chip which has been used for several neural-network implementations. Second, the PCNN is, in almost all applications, a very efficient component of a system requiring subsequent and additional processing. This may include gating, Fourier transforms, neural classifiers, data mining, etc, with or without feedback to the PCNN.
A neural network approach to burst detection.

PubMed

Mounce, S R; Day, A J; Wood, A S; Khan, A; Widdop, P D; Machell, J

2002-01-01

This paper describes how hydraulic and water quality data from a distribution network may be used to provide a more efficient leakage management capability for the water industry. The research presented concerns the application of artificial neural networks to the issue of detection and location of leakage in treated water distribution systems. An architecture for an Artificial Neural Network (ANN) based system is outlined. The neural network uses time series data produced by sensors to directly construct an empirical model for predication and classification of leaks. Results are presented using data from an experimental site in Yorkshire Water's Keighley distribution system.
Neural manufacturing: a novel concept for processing modeling, monitoring, and control

NASA Astrophysics Data System (ADS)

Fu, Chi Y.; Petrich, Loren; Law, Benjamin

1995-09-01

Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process.
Neural network decoder for quantum error correcting codes

NASA Astrophysics Data System (ADS)

Krastanov, Stefan; Jiang, Liang

Artificial neural networks form a family of extremely powerful - albeit still poorly understood - tools used in anything from image and sound recognition through text generation to, in our case, decoding. We present a straightforward Recurrent Neural Network architecture capable of deducing the correcting procedure for a quantum error-correcting code from a set of repeated stabilizer measurements. We discuss the fault-tolerance of our scheme and the cost of training the neural network for a system of a realistic size. Such decoders are especially interesting when applied to codes, like the quantum LDPC codes, that lack known efficient decoding schemes.
Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

1999-01-01

Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

Design of a MIMD neural network processor

NASA Astrophysics Data System (ADS)

Saeks, Richard E.; Priddy, Kevin L.; Pap, Robert M.; Stowell, S.

1994-03-01

The Accurate Automation Corporation (AAC) neural network processor (NNP) module is a fully programmable multiple instruction multiple data (MIMD) parallel processor optimized for the implementation of neural networks. The AAC NNP design fully exploits the intrinsic sparseness of neural network topologies. Moreover, by using a MIMD parallel processing architecture one can update multiple neurons in parallel with efficiency approaching 100 percent as the size of the network increases. Each AAC NNP module has 8 K neurons and 32 K interconnections and is capable of 140,000,000 connections per second with an eight processor array capable of over one billion connections per second.
High efficiency GaP power conversion for Betavoltaic applications

NASA Astrophysics Data System (ADS)

Sims, Paul E.; Dinetta, Louis C.; Barnett, Allen M.

1994-09-01

AstroPower is developing a gallium phosphide (GaP) based energy converter optimized for radio luminescent light-based power supplies. A 'two-step' or 'indirect' process is used where a phosphor is excited by radioactive decay products to produce light that is then converted to electricity by a photovoltaic energy converter. This indirect conversion of beta-radiation to electrical energy can be realized by applying recent developments in tritium based radio luminescent (RL) light sources in combination with the high conversion efficiencies that can be achieved under low illumination with low leakage, gallium phosphide based devices. This tritium to light approach is inherently safer than battery designs that incorporate high activity radionuclides because the beta particles emitted by tritium are of low average energy and are easily stopped by a thin layer of glass. GaP layers were grown by liquid phase epitaxy and p/n junction devices were fabricated and characterized for low light intensity power conversion. AstroPower has demonstrated the feasibility of the GaP based energy converter with the following key results: 23.54 percent conversion efficiency under 968 muW/sq cm 440 nm blue light, 14.59 percent conversion efficiency for 2.85 muW/sq cm 440 nm blue light, and fabrication of working 5 V array. We have also determined that at least 20 muW/sq cm optical power is available for betavoltaic power systems. Successful developments of this device is an enabling technology for low volume, safe, high voltage, milliwatt power supplies with service lifetimes in excess of 12 years.
Dual-Function Au@Y2O3:Eu3+ Smart Film for Enhanced Power Conversion Efficiency and Long-Term Stability of Perovskite Solar Cells.

PubMed

Kim, Chang Woo; Eom, Tae Young; Yang, In Seok; Kim, Byung Su; Lee, Wan In; Kang, Yong Soo; Kang, Young Soo

2017-07-28

In the present study, a dual-functional smart film combining the effects of wavelength conversion and amplification of the converted wave by the localized surface plasmon resonance has been investigated for a perovskite solar cell. This dual-functional film, composed of Au nanoparticles coated on the surface of Y 2 O 3 :Eu 3+ phosphor (Au@Y 2 O 3 :Eu 3+ ) nanoparticle monolayer, enhances the solar energy conversion efficiency to electrical energy and long-term stability of photovoltaic cells. Coupling between the Y 2 O 3 :Eu 3+ phosphor monolayer and ultraviolet solar light induces the latter to be converted into visible light with a quantum yield above 80%. Concurrently, the Au nanoparticle monolayer on the phosphor nanoparticle monolayer amplifies the converted visible light by up to 170%. This synergy leads to an increased solar light energy conversion efficiency of perovskite solar cells. Simultaneously, the dual-function film suppresses the photodegradation of perovskite by UV light, resulting in long-term stability. Introducing the hybrid smart Au@Y 2 O 3 :Eu 3+ film in perovskite solar cells increases their overall solar-to-electrical energy conversion efficiency to 16.1% and enhances long-term stability, as compared to the value of 15.2% for standard perovskite solar cells. The synergism between the wavelength conversion effect of the phosphor nanoparticle monolayer and the wave amplification by the localized surface plasmon resonance of the Au nanoparticle monolayer in a perovskite solar cell is comparatively investigated, providing a viable strategy of broadening the solar spectrum utilization.
High efficiency GaP power conversion for Betavoltaic applications

NASA Technical Reports Server (NTRS)

Sims, Paul E.; Dinetta, Louis C.; Barnett, Allen M.

1994-01-01

AstroPower is developing a gallium phosphide (GaP) based energy converter optimized for radio luminescent light-based power supplies. A 'two-step' or 'indirect' process is used where a phosphor is excited by radioactive decay products to produce light that is then converted to electricity by a photovoltaic energy converter. This indirect conversion of beta-radiation to electrical energy can be realized by applying recent developments in tritium based radio luminescent (RL) light sources in combination with the high conversion efficiencies that can be achieved under low illumination with low leakage, gallium phosphide based devices. This tritium to light approach is inherently safer than battery designs that incorporate high activity radionuclides because the beta particles emitted by tritium are of low average energy and are easily stopped by a thin layer of glass. GaP layers were grown by liquid phase epitaxy and p/n junction devices were fabricated and characterized for low light intensity power conversion. AstroPower has demonstrated the feasibility of the GaP based energy converter with the following key results: 23.54 percent conversion efficiency under 968 muW/sq cm 440 nm blue light, 14.59 percent conversion efficiency for 2.85 muW/sq cm 440 nm blue light, and fabrication of working 5 V array. We have also determined that at least 20 muW/sq cm optical power is available for betavoltaic power systems. Successful developments of this device is an enabling technology for low volume, safe, high voltage, milliwatt power supplies with service lifetimes in excess of 12 years.
A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

PubMed Central

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189
L-dihydroxyphenylserine (Droxidopa): a new therapy for neurogenic orthostatic hypotension: the US experience.

PubMed

Kaufmann, Horacio

2008-03-01

Neurogenic orthostatic hypotension results from failure to release norepinephrine, the neurotransmitter of sympathetic postganglionic neurons, appropriately upon standing. In double blind, cross over, placebo controlled trials, administration of droxidopa, a synthetic amino acid that is decarboxylated to norepinephrine by the enzyme L: -aromatic amino acid decarboxylase increases standing blood pressure, ameliorates symptoms of orthostatic hypotension and improves standing ability in patients with neurogenic orthostatic hypotension due to degenerative autonomic disorders. The pressor effect results from conversion of droxidopa to norepinephrine outside the central nervous system both in neural and non-neural tissue. This mechanism of action makes droxidopa effective in patients with central and peripheral autonomic disorders.
A Neural Network Approach to Intention Modeling for User-Adapted Conversational Agents

PubMed Central

Griol, David

2016-01-01

Spoken dialogue systems have been proposed to enable a more natural and intuitive interaction with the environment and human-computer interfaces. In this contribution, we present a framework based on neural networks that allows modeling of the user's intention during the dialogue and uses this prediction to dynamically adapt the dialogue model of the system taking into consideration the user's needs and preferences. We have evaluated our proposal to develop a user-adapted spoken dialogue system that facilitates tourist information and services and provide a detailed discussion of the positive influence of our proposal in the success of the interaction, the information and services provided, and the quality perceived by the users. PMID:26819592
General Conversion for Obtaining Strongly Existentially Unforgeable Signatures

NASA Astrophysics Data System (ADS)

Teranishi, Isamu; Oyama, Takuro; Ogata, Wakaha

We say that a signature scheme is strongly existentially unforgeable (SEU) if no adversary, given message/signature pairs adaptively, can generate a signature on a new message or a new signature on a previously signed message. We propose a general and efficient conversion in the standard model that transforms a secure signature scheme to SEU signature scheme. In order to construct that conversion, we use a chameleon commitment scheme. Here a chameleon commitment scheme is a variant of commitment scheme such that one can change the committed value after publishing the commitment if one knows the secret key. We define the chosen message security notion for the chameleon commitment scheme, and show that the signature scheme transformed by our proposed conversion satisfies the SEU property if the chameleon commitment scheme is chosen message secure. By modifying the proposed conversion, we also give a general and efficient conversion in the random oracle model, that transforms a secure signature scheme into a SEU signature scheme. This second conversion also uses a chameleon commitment scheme but only requires the key only attack security for it.
Conversion of evanescent Lamb waves into propagating waves via a narrow aperture edge.

PubMed

Yan, Xiang; Yuan, Fuh-Gwo

2015-06-01

This paper presents a quantitative study of conversion of evanescent Lamb waves into propagating in isotropic plates. The conversion is substantiated by prescribing time-harmonic Lamb displacements/tractions through a narrow aperture at an edge of a semi-infinite plate. Complex-valued dispersion and group velocity curves are employed to characterize the conversion process. The amplitude coefficient of the propagating Lamb modes converted from evanescent is quantified based on the complex reciprocity theorem via a finite element analysis. The power flow generated into the plate can be separated into radiative and reactive parts made on the basis of propagating and evanescent Lamb waves, where propagating Lamb waves are theoretically proved to radiate pure real power flow, and evanescent Lamb waves carry reactive pure imaginary power flow. The propagating power conversion efficiency is then defined to quantitatively describe the conversion. The conversion efficiency is strongly frequency dependent and can be significant. With the converted propagating waves from evanescent, sensors at far-field can recapture some localized damage information that is generally possessed in evanescent waves and may have potential application in structural health monitoring.
Enhanced Power Conversion Efficiency of Perovskite Solar Cells with an Up-Conversion Material of Er3+-Yb3+-Li+ Tri-doped TiO2

NASA Astrophysics Data System (ADS)

Zhang, Zhenlong; Qin, Jianqiang; Shi, Wenjia; Liu, Yanyan; Zhang, Yan; Liu, Yuefeng; Gao, Huiping; Mao, Yanli

2018-05-01

In this paper, Er3+-Yb3+-Li+ tri-doped TiO2 (UC-TiO2) was prepared by an addition of Li+ to Er3+-Yb3+ co-doped TiO2. The UC-TiO2 presented an enhanced up-conversion emission compared with Er3+-Yb3+ co-doped TiO2. The UC-TiO2 was applied to the perovskite solar cells. The power conversion efficiency (PCE) of the solar cells without UC-TiO2 was 14.0%, while the PCE of the solar cells with UC-TiO2 was increased to 16.5%, which presented an increase of 19%. The results suggested that UC-TiO2 is an effective up-conversion material. And this study provided a route to expand the spectral absorption of perovskite solar cells from visible light to near-infrared using up-conversion materials.
Statistical thermodynamics foundation for photovoltaic and photothermal conversion. II. Application to photovoltaic conversion

NASA Astrophysics Data System (ADS)

Badescu, Viorel; Landsberg, Peter T.

1995-08-01

The general theory developed in part I was applied to build up two models of photovoltaic conversion. To this end two different systems were analyzed. The first system consists of the whole absorber (converter), for which the balance equations for energy and entropy are written and then used to derive an upper bound for solar energy conversion. The second system covers a part of the absorber (converter), namely the valence and conduction electronic bands. The balance of energy is used in this case to derive, under additional assumptions, another upper limit for the conversion efficiency. This second system deals with the real location where the power is generated. Both models take into consideration the radiation polarization and reflection, and the effects of concentration. The second model yields a more accurate upper bound for the conversion efficiency. A generalized solar cell equation is derived. It is proved that other previous theories are particular cases of the present more general formalism.
Enhanced Power Conversion Efficiency of Perovskite Solar Cells with an Up-Conversion Material of Er3+-Yb3+-Li+ Tri-doped TiO2.

PubMed

Zhang, Zhenlong; Qin, Jianqiang; Shi, Wenjia; Liu, Yanyan; Zhang, Yan; Liu, Yuefeng; Gao, Huiping; Mao, Yanli

2018-05-11

In this paper, Er 3+ -Yb 3+ -Li + tri-doped TiO 2 (UC-TiO 2 ) was prepared by an addition of Li + to Er 3+ -Yb 3+ co-doped TiO 2 . The UC-TiO 2 presented an enhanced up-conversion emission compared with Er 3+ -Yb 3+ co-doped TiO 2 . The UC-TiO 2 was applied to the perovskite solar cells. The power conversion efficiency (PCE) of the solar cells without UC-TiO 2 was 14.0%, while the PCE of the solar cells with UC-TiO 2 was increased to 16.5%, which presented an increase of 19%. The results suggested that UC-TiO 2 is an effective up-conversion material. And this study provided a route to expand the spectral absorption of perovskite solar cells from visible light to near-infrared using up-conversion materials.
The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex

PubMed Central

Petroni, Agustin; Langer, Nicolas; Milham, Michael P.

2018-01-01

Abstract Neural development is generally marked by an increase in the efficiency and diversity of neural processes. In a large sample (n = 114) of human children and adults with ages ranging from 5 to 44 yr, we investigated the neural responses to naturalistic video stimuli. Videos from both real-life classroom settings and Hollywood feature films were used to probe different aspects of attention and engagement. For all stimuli, older ages were marked by more variable neural responses. Variability was assessed by the intersubject correlation of evoked electroencephalographic responses. Young males also had less-variable responses than young females. These results were replicated in an independent cohort (n = 303). When interpreted in the context of neural maturation, we conclude that neural function becomes more variable with maturity, at least during the passive viewing of real-world stimuli. PMID:29379880
Application of an enthalpy balance model of the relation between growth and respiration to temperature acclimation of Eucalyptus globulus seedlings.

PubMed Central

Macfarlane, Craig; Adams, Mark A; Hansen, Lee D

2002-01-01

The enthalpy balance model of growth uses measurements of the rates of heat and CO(2) production to quantify rates of decarboxylation, oxidative phosphorylation and net anabolism. Enthalpy conversion efficiency (eta(H)) and the net rate of conservation of enthalpy in reduced biosynthetic products (R(SG)DeltaH(B)) can be calculated from metabolic heat rate (q) and CO(2) rate (R(CO2)). eta(H) is closely related to carbon conversion efficiency and the efficiency of conservation of available electrons in biosynthetic products. R(SG)DeltaH(B) and eta(H) can be used, together with biomass composition, to describe the rate and efficiency of growth of plant tissues. q is directly related to the rate of O(2) consumption and the ratio q:R(CO2) is inversely related to the respiratory quotient. We grew seedlings of Eucalyptus globulus at 16 and 28 degrees C for four to six weeks, then measured q and R(CO2) using isothermal calorimetry. Respiratory rate at a given temperature was increased by a lower growth temperature but eta(H) was unaffected. Enthalpy conversion efficiency - and, therefore, carbon conversion efficiency - decreased with increasing temperature from 15 to 35 degrees C. The ratio of oxidative phosphorylation to oxygen consumption (P/O ratio) was inferred in vivo from eta(H) and by assuming a constant ratio of growth to maintenance respiration with changing temperature. The P/O ratio decreased from 2.1 at 10-15 degrees C to less than 0.3 at 35 degrees C, suggesting that decreased efficiency was not only due to activity of the alternative oxidase pathway. In agreement with predictions from non-equilibrium thermodynamics, growth rate was maximal near 25 degrees C, where the calculated P/O ratio was about half maximum. We propose that less efficient pathways, such as the alternative oxidase pathway, are necessary to satisfy the condition of conductance matching whilst maintaining a near constant phosphorylation potential. These conditions minimize entropy production and maximize the efficiency of mitochondrial energy conversions as growing conditions change, while maintaining adequate finite rates of energy processing. PMID:12137581
Review of two-phase flow liquid metal MHD and turbine energy conversion concepts for space applications

NASA Technical Reports Server (NTRS)

Fabris, Gracio

1992-01-01

Two-phase energy conversion systems could be liquid metal magnetohydrodynamic (LMMHD) with no moving parts or two-phase turbines. Both of them are inherently simple and reliable devices which can operate in a wide range of temperatures. Their thermal efficiency is significantly higher than for conventional cycles due to reheat of vapor by liquid phase during the energy converting expansion. Often they can be more easily coupled to heat sources. These features make two-phase systems particularly promising for space application. Insufficient research has been done in the past. So far achieved LMMHD generator and two-phase turbine efficiencies are in the 40 to 45 percent range. However if certain fluid dynamic and design problems are resolved these efficiencies could be brought into the range of 70 percent. This would make two-phase systems extremely competitive as compared to present or other proposed conversion system for space. Accordingly, well directed research effort on potential space applications of two-phase conversion systems would be a wise investment.
High-Efficiency Photovoltaic Energy Conversion using Surface Acoustic Waves in Piezoelectric Semiconductors

NASA Astrophysics Data System (ADS)

Yakovenko, Victor

2010-03-01

We propose a radically new design for photovoltaic energy conversion using surface acoustic waves (SAWs) in piezoelectric semiconductors. The periodically modulated electric field from SAW spatially separates photogenerated electrons and holes to the maxima and minima of SAW, thus preventing their recombination. The segregated electrons and holes are transported by the moving SAW to the collecting electrodes of two types, which produce dc electric output. Recent experiments [1] using SAWs in GaAs have demonstrated the photon to current conversion efficiency of 85%. These experiments were designed for photon counting, but we propose to adapt these techniques for highly efficient photovoltaic energy conversion. The advantages are that the electron-hole segregation takes place in the whole volume where SAW is present, and the electrons and holes are transported in the organized, collective manner at high speed, as opposed to random diffusion in conventional devices.[4pt] [1] S. J. Jiao, P. D. Batista, K. Biermann, R. Hey, and P. V. Santos, J. Appl. Phys. 106, 053708 (2009).
Solvent and Intermediate Phase as Boosters for the Perovskite Transformation and Solar Cell Performance

PubMed Central

Kim, Jinhyun; Hwang, Taehyun; Lee, Sangheon; Lee, Byungho; Kim, Jaewon; Jang, Gil Su; Nam, Seunghoon; Park, Byungwoo

2016-01-01

High power conversion efficiency and device stabilization are two major challenges for CH3NH3PbI3 (MAPbI3) perovskite solar cells to be commercialized. Herein, we demonstrate a diffusion-engineered perovskite synthesis method using MAI/ethanol dipping, and compared it to the conventional synthesis method from MAI/iso-propanol. Diffusion of MAI/C2H5OH into the PbCl2 film was observed to be more favorable than that of MAI/C3H7OH. Facile perovskite conversion from ethanol and highly-crystalline MAPbI3 with minimized impurities boosted the efficiency from 5.86% to 9.51%. Additionally, we further identified the intermediates and thereby the reaction mechanisms of PbCl2 converting into MAPbI3. Through straightforward engineering to enhance the surface morphology as well as the crystallinity of the perovskite with even faster conversion, an initial power conversion efficiency of 11.23% was obtained, in addition to superior stability after 30 days under an ambient condition. PMID:27156481
Plasma-assisted CO2 conversion: optimizing performance via microwave power modulation

NASA Astrophysics Data System (ADS)

Britun, Nikolay; Silva, Tiago; Chen, Guoxing; Godfroid, Thomas; van der Mullen, Joost; Snyders, Rony

2018-04-01

Significant improvement in the energy efficiency of plasma-assisted CO2 conversion is achieved with applied power modulation in a surfaguide microwave discharge. The obtained values of CO2 conversion and energy efficiency are, respectively, 0.23 and 0.33 for a 0.95 CO2 + 0.05 N2 gas mixture. Analysis of the energy relaxation mechanisms shows that power modulation can potentially affect the vibrational-translational energy exchange in plasma. In our case, however, this mechanism does not play a major role, likely due to the low degree of plasma non-equilibrium in the considered pressure range. Instead, the gas residence time in the discharge active zone together with plasma pulse duration are found to be the main factors affecting the CO2 conversion efficiency at low plasma pulse repetition rates. This effect is confirmed experimentally by the in situ time-resolved two-photon absorption laser-induced fluorescence measurements of CO molecular density produced in the discharge as a result of CO2 decomposition.
Can quantum coherent solar cells break detailed balance?

NASA Astrophysics Data System (ADS)

Kirk, Alexander P.

2015-07-01

Carefully engineered coherent quantum states have been proposed as a design attribute that is hypothesized to enable solar photovoltaic cells to break the detailed balance (or radiative) limit of power conversion efficiency by possibly causing radiative recombination to be suppressed. However, in full compliance with the principles of statistical mechanics and the laws of thermodynamics, specially prepared coherent quantum states do not allow a solar photovoltaic cell—a quantum threshold energy conversion device—to exceed the detailed balance limit of power conversion efficiency. At the condition given by steady-state open circuit operation with zero nonradiative recombination, the photon absorption rate (or carrier photogeneration rate) must balance the photon emission rate (or carrier radiative recombination rate) thus ensuring that detailed balance prevails. Quantum state transitions, entropy-generating hot carrier relaxation, and photon absorption and emission rate balancing are employed holistically and self-consistently along with calculations of current density, voltage, and power conversion efficiency to explain why detailed balance may not be violated in solar photovoltaic cells.
From by-product to valuable components: Efficient enzymatic conversion of lactose in whey using β-galactosidase from Streptococcus thermophilus.

PubMed

Geiger, Barbara; Nguyen, Hoang-Minh; Wenig, Stefanie; Nguyen, Hoang Anh; Lorenz, Cindy; Kittl, Roman; Mathiesen, Geir; Eijsink, Vincent G H; Haltrich, Dietmar; Nguyen, Thu-Ha

2016-12-15

β-Galactosidase from Streptococcus thermophilus was overexpressed in a food-grade organism, Lactobacillus plantarum WCFS1. Laboratory cultivations yielded 11,000 U of β-galactosidase activity per liter of culture corresponding to approximately 170 mg of enzyme. Crude cell-free enzyme extracts obtained by cell disruption and subsequent removal of cell debris showed high stability and were used for conversion of lactose in whey permeate. The enzyme showed high transgalactosylation activity. When using an initial concentration of whey permeate corresponding to 205 g L -1 lactose, the maximum yield of galacto-oligosaccharides (GOS) obtained at 50°C reached approximately 50% of total sugar at 90% lactose conversion, meaning that efficient valorization of the whey lactose was obtained. GOS are of great interest for both human and animal nutrition; thus, efficient conversion of lactose in whey into GOS using an enzymatic approach will not only decrease the environmental impact of whey disposal, but also create additional value.

A review on solar cells from Si-single crystals to porous materials and quantum dots

PubMed Central

Badawy, Waheed A.

2013-01-01

Solar energy conversion to electricity through photovoltaics or to useful fuel through photoelectrochemical cells was still a main task for research groups and developments sectors. In this article we are reviewing the development of the different generations of solar cells. The fabrication of solar cells has passed through a large number of improvement steps considering the technological and economic aspects. The first generation solar cells were based on Si wafers, mainly single crystals. Permanent researches on cost reduction and improved solar cell efficiency have led to the marketing of solar modules having 12–16% solar conversion efficiency. Application of polycrystalline Si and other forms of Si have reduced the cost but on the expense of the solar conversion efficiency. The second generation solar cells were based on thin film technology. Thin films of amorphous Si, CIS (copper–indium–selenide) and t-Si were employed. Solar conversion efficiencies of about 12% have been achieved with a remarkable cost reduction. The third generation solar cells are based on nano-crystals and nano-porous materials. An advanced photovoltaic cell, originally developed for satellites with solar conversion efficiency of 37.3%, based on concentration of the solar spectrum up to 400 suns was developed. It is based on extremely thin concentration cells. New sensitizer or semiconductor systems are necessary to broaden the photo-response in solar spectrum. Hybrids of solar and conventional devices may provide an interim benefit in seeking economically valuable devices. New quantum dot solar cells based on CdSe–TiO2 architecture have been developed. PMID:25750746
A review on solar cells from Si-single crystals to porous materials and quantum dots.

PubMed

Badawy, Waheed A

2015-03-01

Solar energy conversion to electricity through photovoltaics or to useful fuel through photoelectrochemical cells was still a main task for research groups and developments sectors. In this article we are reviewing the development of the different generations of solar cells. The fabrication of solar cells has passed through a large number of improvement steps considering the technological and economic aspects. The first generation solar cells were based on Si wafers, mainly single crystals. Permanent researches on cost reduction and improved solar cell efficiency have led to the marketing of solar modules having 12-16% solar conversion efficiency. Application of polycrystalline Si and other forms of Si have reduced the cost but on the expense of the solar conversion efficiency. The second generation solar cells were based on thin film technology. Thin films of amorphous Si, CIS (copper-indium-selenide) and t-Si were employed. Solar conversion efficiencies of about 12% have been achieved with a remarkable cost reduction. The third generation solar cells are based on nano-crystals and nano-porous materials. An advanced photovoltaic cell, originally developed for satellites with solar conversion efficiency of 37.3%, based on concentration of the solar spectrum up to 400 suns was developed. It is based on extremely thin concentration cells. New sensitizer or semiconductor systems are necessary to broaden the photo-response in solar spectrum. Hybrids of solar and conventional devices may provide an interim benefit in seeking economically valuable devices. New quantum dot solar cells based on CdSe-TiO2 architecture have been developed.
Memory for conversation and the development of common ground.

PubMed

McKinley, Geoffrey L; Brown-Schmidt, Sarah; Benjamin, Aaron S

2017-11-01

Efficient conversation is guided by the mutual knowledge, or common ground, that interlocutors form as a conversation progresses. Characterized from the perspective of commonly used measures of memory, efficient conversation should be closely associated with item memory-what was said-and context memory-who said what to whom. However, few studies have explicitly probed memory to evaluate what type of information is maintained following a communicative exchange. The current study examined how item and context memory relate to the development of common ground over the course of a conversation, and how these forms of memory vary as a function of one's role in a conversation as speaker or listener. The process of developing common ground was positively related to both item and context memory. In addition, content that was spoken was remembered better than content that was heard. Our findings illustrate how memory assessments can complement language measures by revealing the impact that basic conversational processes have on memory for what has been discussed. By taking this approach, we show that not only does the process of forming common ground facilitate communication in the present, but it also promotes an enduring record of that event, facilitating conversation into the future.
Using Upper Layer Weights to Efficiently Construct and Train Feedforward Neural Networks Executing Backpropagation

DTIC Science & Technology

2011-03-01

algorithm is utilized by Belue, Steppe, & Bauer and Kocur , et al. (Belue, Steppe, & Bauer, April 1996) ( Kocur , et al., 1996). Bacauskiene and...Society. Cardiff, UK. Kocur , C., Roger, S., Myers, L., Burns, T., Hoffmeister, J., Bauer, K., et al. (1996). Using neural networks to select
Using input feature information to improve ultraviolet retrieval in neural networks

NASA Astrophysics Data System (ADS)

Sun, Zhibin; Chang, Ni-Bin; Gao, Wei; Chen, Maosi; Zempila, Melina

2017-09-01

In neural networks, the training/predicting accuracy and algorithm efficiency can be improved significantly via accurate input feature extraction. In this study, some spatial features of several important factors in retrieving surface ultraviolet (UV) are extracted. An extreme learning machine (ELM) is used to retrieve the surface UV of 2014 in the continental United States, using the extracted features. The results conclude that more input weights can improve the learning capacities of neural networks.
An efficient annealing in Boltzmann machine in Hopfield neural network

NASA Astrophysics Data System (ADS)

Kin, Teoh Yeong; Hasan, Suzanawati Abu; Bulot, Norhisam; Ismail, Mohammad Hafiz

2012-09-01

This paper proposes and implements Boltzmann machine in Hopfield neural network doing logic programming based on the energy minimization system. The temperature scheduling in Boltzmann machine enhancing the performance of doing logic programming in Hopfield neural network. The finest temperature is determined by observing the ratio of global solution and final hamming distance using computer simulations. The study shows that Boltzmann Machine model is more stable and competent in term of representing and solving difficult combinatory problems.
Temporal plasticity in auditory cortex improves neural discrimination of speech sounds

PubMed Central

Engineer, Crystal T.; Shetake, Jai A.; Engineer, Navzer D.; Vrana, Will A.; Wolf, Jordan T.; Kilgard, Michael P.

2017-01-01

Background Many individuals with language learning impairments exhibit temporal processing deficits and degraded neural responses to speech sounds. Auditory training can improve both the neural and behavioral deficits, though significant deficits remain. Recent evidence suggests that vagus nerve stimulation (VNS) paired with rehabilitative therapies enhances both cortical plasticity and recovery of normal function. Objective/Hypothesis We predicted that pairing VNS with rapid tone trains would enhance the primary auditory cortex (A1) response to unpaired novel speech sounds. Methods VNS was paired with tone trains 300 times per day for 20 days in adult rats. Responses to isolated speech sounds, compressed speech sounds, word sequences, and compressed word sequences were recorded in A1 following the completion of VNS-tone train pairing. Results Pairing VNS with rapid tone trains resulted in stronger, faster, and more discriminable A1 responses to speech sounds presented at conversational rates. Conclusion This study extends previous findings by documenting that VNS paired with rapid tone trains altered the neural response to novel unpaired speech sounds. Future studies are necessary to determine whether pairing VNS with appropriate auditory stimuli could potentially be used to improve both neural responses to speech sounds and speech perception in individuals with receptive language disorders. PMID:28131520
Highly-efficient capillary photoelectrochemical water splitting using cellulose nanofiber-templated TiO 2 photoanodes

Treesearch

Zhaodong Li; Chunhua Yao; Yanhao Yu; Zhiyong Cai; Xudong Wang

2014-01-01

Among current endeavors to explore renewable energy technologies, photoelectrochemical (PEC) water splitting holds great promise for conversion of solar energy to chemical energy. [ 1â4 ] Light absorption, charge separation, and appropriate interfacial redox reactions are three key aspects that lead to highly efficient solar energy conversion. [ 5â10 ] Therefore,...
The effect of an infinite plane-wave approximation on calculations for second-harmonic generation in a one-dimensional nonlinear crystal

NASA Astrophysics Data System (ADS)

Zhao, Jing; Zhao, Li-Ming

2012-05-01

In this paper, the second-harmonic generation (SHG) in a one-dimensional nonlinear crystal that is embedded in air is investigated. Previously, the identical configuration was studied in Li Z. Y. et al., Phys. Rev. B, 60 (1999) 10644, without the use of the slowly varying amplitude approximation (SVAA), but by adopting the infinite plane-wave approximation (PWA), despite the fact that this approximation is not quite applicable to such a system. We calculate the SHG conversion efficiency without a PWA, and compare the results with those from the quoted reference. The investigation reveals that conversion efficiencies of SHG as calculated by the two methods appear to exhibit significant differences, and that the SHG may be modulated by the field of a fundamental wave (FW). The ratio between SHG conversion efficiencies as produced by the two methods shows a periodic variation, and this oscillatory behavior is fully consistent with the variation in transmittance of the FW. Quasi-phase matching (QPM) is also studied, and we find that the location of the peak for SHG conversion efficiency deviates from Δd=0, which differs from the conventional QPM results.
Large impact of reorganization energy on photovoltaic conversion due to interfacial charge-transfer transitions.

PubMed

Fujisawa, Jun-ichi

2015-05-14

Interfacial charge-transfer (ICT) transitions are expected to be a novel charge-separation mechanism for efficient photovoltaic conversion featuring one-step charge separation without energy loss. Photovoltaic conversion due to ICT transitions has been investigated using several TiO2-organic hybrid materials that show organic-to-inorganic ICT transitions in the visible region. In applications of ICT transitions to photovoltaic conversion, there is a significant problem that rapid carrier recombination is caused by organic-inorganic electronic coupling that is necessary for the ICT transitions. In order to solve this problem, in this work, I have theoretically studied light-to-current conversions due to the ICT transitions on the basis of the Marcus theory with density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations. An apparent correlation between the reported incident photon-to-current conversion efficiencies (IPCE) and calculated reorganization energies was clearly found, in which the IPCE increases with decreasing the reorganization energy consistent with the Marcus theory in the inverted region. This activation-energy dependence was systematically explained by the equation formulated by the Marcus theory based on a simple excited-state kinetic scheme. This result indicates that the reduction of the reorganization energy can suppress the carrier recombination and enhance the IPCE. The reorganization energy is predominantly governed by the structural change in the chemical-adsorption moiety between the ground and ICT excited states. This work provides crucial knowledge for efficient photovoltaic conversion due to ICT transitions.
Full-spectrum volumetric solar thermal conversion via photonic nanofluids.

PubMed

Liu, Xianglei; Xuan, Yimin

2017-10-12

Volumetric solar thermal conversion is an emerging technique for a plethora of applications such as solar thermal power generation, desalination, and solar water splitting. However, achieving broadband solar thermal absorption via dilute nanofluids is still a daunting challenge. In this work, full-spectrum volumetric solar thermal conversion is demonstrated over a thin layer of the proposed 'photonic nanofluids'. The underlying mechanism is found to be the photonic superposition of core resonances, shell plasmons, and core-shell resonances at different wavelengths, whose coexistence is enabled by the broken symmetry of specially designed composite nanoparticles, i.e., Janus nanoparticles. The solar thermal conversion efficiency can be improved by 10.8% compared with core-shell nanofluids. The extinction coefficient of Janus dimers with various configurations is also investigated to unveil the effects of particle couplings. This work provides the possibility to achieve full-spectrum volumetric solar thermal conversion, and may have potential applications in efficient solar energy harvesting and utilization.
Sub-Band Gap Turn-On Near-Infrared-to-Visible Up-Conversion Device Enabled by an Organic-Inorganic Hybrid Perovskite Photovoltaic Absorber.

PubMed

Yu, By Hyeonggeun; Cheng, Yuanhang; Li, Menglin; Tsang, Sai-Wing; So, Franky

2018-05-09

Direct integration of an infrared (IR) photodetector with an organic light-emitting diode (OLED) enables low-cost, pixel-free IR imaging. However, the operation voltage of the resulting IR-to-visible up-conversion is large because of the series device architecture. Here, we report a low-voltage near-IR (NIR)-to-visible up-conversion device using formamidinium lead iodide as a NIR absorber integrated with a phosphorescent OLED. Because of the efficient photocarrier injection from the hybrid perovskite layer to the OLED, we observed a sub-band gap turn-on of the OLED under NIR illumination. The device showed a NIR-to-visible up-conversion efficiency of 3% and a luminance on/off ratio of 10 3 at only 5 V. Finally, we demonstrate pixel-free NIR imaging using the up-conversion device.
Implicit motor learning promotes neural efficiency during laparoscopy.

PubMed

Zhu, Frank F; Poolton, Jamie M; Wilson, Mark R; Hu, Yong; Maxwell, Jon P; Masters, Rich S W

2011-09-01

An understanding of differences in expert and novice neural behavior can inform surgical skills training. Outside the surgical domain, electroencephalographic (EEG) coherence analyses have shown that during motor performance, experts display less coactivation between the verbal-analytic and motor planning regions than their less skilled counterparts. Reduced involvement of verbal-analytic processes suggests greater neural efficiency. The authors tested the utility of an implicit motor learning intervention specifically devised to promote neural efficiency by reducing verbal-analytic involvement in laparoscopic performance. In this study, 18 novices practiced a movement pattern on a laparoscopic trainer with either conscious awareness of the movement pattern (explicit motor learning) or suppressed awareness of the movement pattern (implicit motor learning). In a retention test, movement accuracy was compared between the conditions, and coactivation (EEG coherence) was assessed between the motor planning (Fz) region and both the verbal-analytic (T3) and the visuospatial (T4) cortical regions (T3-Fz and T4-Fz, respectively). Movement accuracy in the conditions was not different in a retention test (P = 0.231). Findings showed that the EEG coherence scores for the T3-Fz regions were lower for the implicit learners than for the explicit learners (P = 0.027), but no differences were apparent for the T4-Fz regions (P = 0.882). Implicit motor learning reduced EEG coactivation between verbal-analytic and motor planning regions, suggesting that verbal-analytic processes were less involved in laparoscopic performance. The findings imply that training techniques that discourage nonessential coactivation during motor performance may provide surgeons with more neural resources with which to manage other aspects of surgery.
The alkali metal thermoelectric converter /AMTEC/ - A new direct energy conversion technology for aerospace power

NASA Technical Reports Server (NTRS)

Bankston, C. P.; Cole, T.; Jones, R.; Ewell, R.

1982-01-01

A thermally regenerative electrochemical device for the direct conversion of heat to electrical energy, the alkali metal thermoelectric converter (AMTEC), is characterized by potential efficiencies on the order of 15-40% and possesses no moving parts, making it a candidate for space power system applications. Device conversion efficiency is projected on the basis of experimental voltage vs current curves exhibiting power densities of 0.7 W/sq cm and measured electrode efficiencies of up to 40%. Preliminary radiative heat transfer measurements presented may be used in an investigation of methods for the reduction of AMTEC parasitic radiation losses. AMTEC assumes heat input and rejection temperatures of 900-1300 K and 400-800 K, respectively. The working fluid is liquid sodium, and the porous electrode employed is of molybdenum.
High conversion efficiency distributed feedback laser from a dye-doped holographic transmission grating

NASA Astrophysics Data System (ADS)

Liu, Lijuan; Zhang, Guiyang; Kong, Xiaobo; Liu, Yonggang; Xuan, Li

2018-01-01

A high conversion efficiency distributed feedback (DFB) laser from a dye-doped holographic polymer dispersed liquid crystal (HPDLC) transmission grating structure was reported. The alignment polyimide (PI) films were used to control the orientation of the phase separated liquid crystals (LCs) to increase the refractive index difference between the LC and the polymer, so it can provide better light feedback. The lasing wavelength located at 645.8 nm near the maximum of the amplified spontaneous emission (ASE) spectrum with the lowest threshold 0.97 μ J/pulse and the highest conversion efficiency 1.6% was obtained. The laser performance under electric field were also investigated and illustrated. The simple configuration, one-step fabrication organic dye laser shows the potential to realize ultra-low cost plastic lasers.
Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder.

PubMed

Hassa, Thomas; Sebastian, Alexandra; Liepert, Joachim; Weiller, Cornelius; Schmidt, Roger; Tüscher, Oliver

2017-01-01

Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI) was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-)supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.
Gold-silver@TiO2 nanocomposite-modified plasmonic photoanodes for higher efficiency dye-sensitized solar cells.

PubMed

Lim, Su Pei; Lim, Yee Seng; Pandikumar, Alagarsamy; Lim, Hong Ngee; Ng, Yun Hau; Ramaraj, Ramasamy; Bien, Daniel Chia Sheng; Abou-Zied, Osama K; Huang, Nay Ming

2017-01-04

In the present investigation, gold-silver@titania (Au-Ag@TiO 2 ) plasmonic nanocomposite materials with different Au and Ag compositions were prepared using a simple one-step chemical reduction method and used as photoanodes in high-efficiency dye-sensitized solar cells (DSSCs). The Au-Ag incorporated TiO 2 photoanode demonstrated an enhanced solar-to-electrical energy conversion efficiency of 7.33%, which is ∼230% higher than the unmodified TiO 2 photoanode (2.22%) under full sunlight illumination (100 mW cm -2 , AM 1.5G). This superior solar energy conversion efficiency was mainly due to the synergistic effect between the Au and Ag, and their surface plasmon resonance effect, which improved the optical absorption and interfacial charge transfer by minimizing the charge recombination process. The influence of the Au-Ag composition on the overall energy conversion efficiency was also explored, and the optimized composition with TiO 2 was found to be Au 75 -Ag 25 . This was reflected in the femtosecond transient absorption dynamics in which the electron-phonon interaction in the Au nanoparticles was measured to be 6.14 ps in TiO 2 /Au 75 :Ag 25 , compared to 2.38 ps for free Au and 4.02 ps for TiO 2 /Au 100 :Ag 0 . The slower dynamics indicates a more efficient electron-hole separation in TiO 2 /Au 75 :Ag 25 that is attributed to the formation of a Schottky barrier at the interface between TiO 2 and the noble metal(s) that acts as an electron sink. The significant boost in the solar energy conversion efficiency with the Au-Ag@TiO 2 plasmonic nanocomposite showed its potential as a photoanode for high-efficiency DSSCs.
Artificial neural network modeling and optimization of ultrahigh pressure extraction of green tea polyphenols.

PubMed

Xi, Jun; Xue, Yujing; Xu, Yinxiang; Shen, Yuhong

2013-11-01

In this study, the ultrahigh pressure extraction of green tea polyphenols was modeled and optimized by a three-layer artificial neural network. A feed-forward neural network trained with an error back-propagation algorithm was used to evaluate the effects of pressure, liquid/solid ratio and ethanol concentration on the total phenolic content of green tea extracts. The neural network coupled with genetic algorithms was also used to optimize the conditions needed to obtain the highest yield of tea polyphenols. The obtained optimal architecture of artificial neural network model involved a feed-forward neural network with three input neurons, one hidden layer with eight neurons and one output layer including single neuron. The trained network gave the minimum value in the MSE of 0.03 and the maximum value in the R(2) of 0.9571, which implied a good agreement between the predicted value and the actual value, and confirmed a good generalization of the network. Based on the combination of neural network and genetic algorithms, the optimum extraction conditions for the highest yield of green tea polyphenols were determined as follows: 498.8 MPa for pressure, 20.8 mL/g for liquid/solid ratio and 53.6% for ethanol concentration. The total phenolic content of the actual measurement under the optimum predicated extraction conditions was 582.4 ± 0.63 mg/g DW, which was well matched with the predicted value (597.2mg/g DW). This suggests that the artificial neural network model described in this work is an efficient quantitative tool to predict the extraction efficiency of green tea polyphenols. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.
Is "efficiency" a useful concept in cognitive neuroscience?

PubMed

Poldrack, Russell A

2015-02-01

It is common in the cognitive neuroscience literature to explain differences in activation in terms of differences in the "efficiency" of neural function. I argue here that this usage of the concept of efficiency is empty and simply redescribes activation differences rather than providing a useful explanation of them. I examine a number of possible explanations for differential activation in terms of task performance, neuronal computation, neuronal energetics, and network organization. While the concept of "efficiency" is vacuous as it is commonly employed in the neuroimaging literature, an examination of brain development in the context of neural coding, neuroenergetics, and network structure provides a roadmap for future investigation, which is fundamental to an improved understanding of developmental effects and group differences in neuroimaging signals. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.
Advances in graphene-based semiconductor photocatalysts for solar energy conversion: fundamentals and materials engineering.

PubMed

Xie, Xiuqiang; Kretschmer, Katja; Wang, Guoxiu

2015-08-28

Graphene-based semiconductor photocatalysis has been regarded as a promising technology for solar energy storage and conversion. In this review, we summarized recent developments of graphene-based photocatalysts, including preparation of graphene-based photocatalysts, typical key advances in the understanding of graphene functions for photocatalytic activity enhancement and methodologies to regulate the electron transfer efficiency in graphene-based composite photocatalysts, by which we hope to offer enriched information to harvest the utmost fascinating properties of graphene as a platform to construct efficient graphene-based composite photocatalysts for solar-to-energy conversion.

Raman conversion in intense femtosecond Bessel beams in air

NASA Astrophysics Data System (ADS)

Scheller, Maik; Chen, Xi; Ariunbold, Gombojav O.; Born, Norman; Moloney, Jerome; Kolesik, Miroslav; Polynkin, Pavel

2014-05-01

We demonstrate experimentally that bright and nearly collimated radiation can be efficiently generated in air pumped by an intense femtosecond Bessel beam. We show that this nonlinear conversion process is driven by the rotational Raman response of air molecules. Under optimum conditions, the conversion efficiency from the Bessel pump into the on-axis propagating beam exceeds 15% and is limited by the onset of intensity clamping and plasma refraction on the beam axis. Our experimental findings are in excellent agreement with numerical simulations based on the standard model for the ultrafast nonlinear response of air.
Neural and hybrid modeling: an alternative route to efficiently predict the behavior of biotechnological processes aimed at biofuels obtainment.

PubMed

Curcio, Stefano; Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

2014-01-01

The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.
Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

PubMed Central

Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

2014-01-01

The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved. PMID:24516363
Research on optimization of combustion efficiency of thermal power unit based on genetic algorithm

NASA Astrophysics Data System (ADS)

Zhou, Qiongyang

2018-04-01

In order to improve the economic performance and reduce pollutant emissions of thermal power units, the characteristics of neural network in establishing boiler combustion model are analyzed based on the analysis of the main factors affecting boiler efficiency by using orthogonal method. In addition, on the basis of this model, the genetic algorithm is used to find the best control amount of the furnace combustion in a certain working condition. Through the genetic algorithm based on real number encoding and roulette selection is concluded: the best control quantity at a condition of furnace combustion can be combined with the boiler combustion system model for neural network training. The precision of the neural network model is further improved, and the basic work is laid for the research of the whole boiler combustion optimization system.
Neural computation of arithmetic functions

NASA Technical Reports Server (NTRS)

Siu, Kai-Yeung; Bruck, Jehoshua

1990-01-01

An area of application of neural networks is considered. A neuron is modeled as a linear threshold gate, and the network architecture considered is the layered feedforward network. It is shown how common arithmetic functions such as multiplication and sorting can be efficiently computed in a shallow neural network. Some known results are improved by showing that the product of two n-bit numbers and sorting of n n-bit numbers can be computed by a polynomial-size neural network using only four and five unit delays, respectively. Moreover, the weights of each threshold element in the neural networks require O(log n)-bit (instead of n-bit) accuracy. These results can be extended to more complicated functions such as multiple products, division, rational functions, and approximation of analytic functions.
Neural Networks for Rapid Design and Analysis

NASA Technical Reports Server (NTRS)

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

1998-01-01

Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.
Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses.

PubMed

Zhang, Wei; Huang, Tingwen; He, Xing; Li, Chuandong

2017-11-01

In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neural networks and memristor. Impulses with and without delays are considered when modeling the inertial neural networks simultaneously, which are of great practical significance in the current study. Some sufficient conditions are derived under the framework of the Lyapunov stability method, as well as an extended Halanay differential inequality and a new delay impulsive differential inequality, which depend on impulses with and without delays, in order to guarantee the global exponential stability of the inertial memristor-based neural networks. Finally, two numerical examples are provided to illustrate the efficiency of the proposed methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Designing an artificial neural network using radial basis function to model exergetic efficiency of nanofluids in mini double pipe heat exchanger

NASA Astrophysics Data System (ADS)

Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar

2018-06-01

The present study aims at predicting and optimizing exergetic efficiency of TiO2-Al2O3/water nanofluid at different Reynolds numbers, volume fractions and twisted ratios using Artificial Neural Networks (ANN) and experimental data. Central Composite Design (CCD) and cascade Radial Basis Function (RBF) were used to display the significant levels of the analyzed factors on the exergetic efficiency. The size of TiO2-Al2O3/water nanocomposite was 20-70 nm. The parameters of ANN model were adapted by a training algorithm of radial basis function (RBF) with a wide range of experimental data set. Total mean square error and correlation coefficient were used to evaluate the results which the best result was obtained from double layer perceptron neural network with 30 neurons in which total Mean Square Error(MSE) and correlation coefficient (R2) were equal to 0.002 and 0.999, respectively. This indicated successful prediction of the network. Moreover, the proposed equation for predicting exergetic efficiency was extremely successful. According to the optimal curves, the optimum designing parameters of double pipe heat exchanger with inner twisted tape and nanofluid under the constrains of exergetic efficiency 0.937 are found to be Reynolds number 2500, twisted ratio 2.5 and volume fraction( v/v%) 0.05.
Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network

PubMed Central

Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

2018-01-01

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. Summary We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding. PMID:29773979
Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network.

PubMed

Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

2018-01-01

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding.
An FGF3-BMP Signaling Axis Regulates Caudal Neural Tube Closure, Neural Crest Specification and Anterior-Posterior Axis Extension

PubMed Central

Anderson, Matthew J.; Schimmang, Thomas; Lewandoski, Mark

2016-01-01

During vertebrate axis extension, adjacent tissue layers undergo profound morphological changes: within the neuroepithelium, neural tube closure and neural crest formation are occurring, while within the paraxial mesoderm somites are segmenting from the presomitic mesoderm (PSM). Little is known about the signals between these tissues that regulate their coordinated morphogenesis. Here, we analyze the posterior axis truncation of mouse Fgf3 null homozygotes and demonstrate that the earliest role of PSM-derived FGF3 is to regulate BMP signals in the adjacent neuroepithelium. FGF3 loss causes elevated BMP signals leading to increased neuroepithelium proliferation, delay in neural tube closure and premature neural crest specification. We demonstrate that elevated BMP4 depletes PSM progenitors in vitro, phenocopying the Fgf3 mutant, suggesting that excessive BMP signals cause the Fgf3 axis defect. To test this in vivo we increased BMP signaling in Fgf3 mutants by removing one copy of Noggin, which encodes a BMP antagonist. In such mutants, all parameters of the Fgf3 phenotype were exacerbated: neural tube closure delay, premature neural crest specification, and premature axis termination. Conversely, genetically decreasing BMP signaling in Fgf3 mutants, via loss of BMP receptor activity, alleviates morphological defects. Aberrant apoptosis is observed in the Fgf3 mutant tailbud. However, we demonstrate that cell death does not cause the Fgf3 phenotype: blocking apoptosis via deletion of pro-apoptotic genes surprisingly increases all Fgf3 defects including causing spina bifida. We demonstrate that this counterintuitive consequence of blocking apoptosis is caused by the increased survival of BMP-producing cells in the neuroepithelium. Thus, we show that FGF3 in the caudal vertebrate embryo regulates BMP signaling in the neuroepithelium, which in turn regulates neural tube closure, neural crest specification and axis termination. Uncovering this FGF3-BMP signaling axis is a major advance toward understanding how these tissue layers interact during axis extension with important implications in human disease. PMID:27144312
Thin-thick quadrature frequency conversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eimerl, D.

1985-02-07

The quadrature conversion scheme is a method of generating the second harmonic. The scheme, which uses two crystals in series, has several advantages over single-crystal or other two crystal schemes. The most important is that it is capable of high conversion efficiency over a large dynamic range of drive intensity and detuning angle.
40 CFR 98.253 - Calculating GHG emissions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (metric tons/year). 0.98 = Assumed combustion efficiency of a flare. 0.001 = Unit conversion factor... measurement values within the day to calculate a daily average. MVC = Molar volume conversion factor (849.5....001 = Unit conversion factor (metric tons per kilogram, mt/kg). n = Number of measurement periods. The...
Impact parameter determination in experimental analysis using a neural network

NASA Astrophysics Data System (ADS)

Haddad, F.; Hagel, K.; Li, J.; Mdeiwayeh, N.; Natowitz, J. B.; Wada, R.; Xiao, B.; David, C.; Freslier, M.; Aichelin, J.

1997-03-01

A neural network is used to determine the impact parameter in 40Ca+40Ca reactions. The effect of the detection efficiency as well as the model dependence of the training procedure has been studied carefully. An overall improvement of the impact parameter determination of 25% is obtained using this technique. The analysis of Amphora 40Ca+40Ca data at 35 MeV per nucleon using a neural network shows two well-separated classes of events among the selected ``complete'' events.
Inversion of quasi-3D DC resistivity imaging data using artificial neural networks

NASA Astrophysics Data System (ADS)

Neyamadpour, Ahmad; Wan Abdullah, W. A. T.; Taib, Samsudin

2010-02-01

The objective of this paper is to investigate the applicability of artificial neural networks in inverting quasi-3D DC resistivity imaging data. An electrical resistivity imaging survey was carried out along seven parallel lines using a dipole-dipole array to confirm the validation of the results of an inversion using an artificial neural network technique. The model used to produce synthetic data to train the artificial neural network was a homogeneous medium of 100Ωm resistivity with an embedded anomalous body of 1000Ωm resistivity. The network was trained using 21 datasets (comprising 12159 data points) and tested on another 11 synthetic datasets (comprising 6369 data points) and on real field data. Another 24 test datasets (comprising 13896 data points) consisting of different resistivities for the background and the anomalous bodies were used in order to test the interpolation and extrapolation of network properties. Different learning paradigms were tried in the training process of the neural network, with the resilient propagation paradigm being the most efficient. The number of nodes, hidden layers, and efficient values for learning rate and momentum coefficient have been studied. Although a significant correlation between results of the neural network and the conventional robust inversion technique was found, the ANN results show more details of the subsurface structure, and the RMS misfits for the results of the neural network are less than seen with conventional methods. The interpreted results show that the trained network was able to invert quasi-3D electrical resistivity imaging data obtained by dipole-dipole configuration both rapidly and accurately.
Selective and Efficient Neural Coding of Communication Signals Depends on Early Acoustic and Social Environment

PubMed Central

Amin, Noopur; Gastpar, Michael; Theunissen, Frédéric E.

2013-01-01

Previous research has shown that postnatal exposure to simple, synthetic sounds can affect the sound representation in the auditory cortex as reflected by changes in the tonotopic map or other relatively simple tuning properties, such as AM tuning. However, their functional implications for neural processing in the generation of ethologically-based perception remain unexplored. Here we examined the effects of noise-rearing and social isolation on the neural processing of communication sounds such as species-specific song, in the primary auditory cortex analog of adult zebra finches. Our electrophysiological recordings reveal that neural tuning to simple frequency-based synthetic sounds is initially established in all the laminae independent of patterned acoustic experience; however, we provide the first evidence that early exposure to patterned sound statistics, such as those found in native sounds, is required for the subsequent emergence of neural selectivity for complex vocalizations and for shaping neural spiking precision in superficial and deep cortical laminae, and for creating efficient neural representations of song and a less redundant ensemble code in all the laminae. Our study also provides the first causal evidence for ‘sparse coding’, such that when the statistics of the stimuli were changed during rearing, as in noise-rearing, that the sparse or optimal representation for species-specific vocalizations disappeared. Taken together, these results imply that a layer-specific differential development of the auditory cortex requires patterned acoustic input, and a specialized and robust sensory representation of complex communication sounds in the auditory cortex requires a rich acoustic and social environment. PMID:23630587
Model of brain activation predicts the neural collective influence map of the brain

PubMed Central

Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.

2017-01-01

Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973
On-Chip Neural Data Compression Based On Compressed Sensing With Sparse Sensing Matrices.

PubMed

Zhao, Wenfeng; Sun, Biao; Wu, Tong; Yang, Zhi

2018-02-01

On-chip neural data compression is an enabling technique for wireless neural interfaces that suffer from insufficient bandwidth and power budgets to transmit the raw data. The data compression algorithm and its implementation should be power and area efficient and functionally reliable over different datasets. Compressed sensing is an emerging technique that has been applied to compress various neurophysiological data. However, the state-of-the-art compressed sensing (CS) encoders leverage random but dense binary measurement matrices, which incur substantial implementation costs on both power and area that could offset the benefits from the reduced wireless data rate. In this paper, we propose two CS encoder designs based on sparse measurement matrices that could lead to efficient hardware implementation. Specifically, two different approaches for the construction of sparse measurement matrices, i.e., the deterministic quasi-cyclic array code (QCAC) matrix and -sparse random binary matrix [-SRBM] are exploited. We demonstrate that the proposed CS encoders lead to comparable recovery performance. And efficient VLSI architecture designs are proposed for QCAC-CS and -SRBM encoders with reduced area and total power consumption.
High Performance Artificial Muscles Using Nanofiber and Hybrid Yarns

DTIC Science & Technology

2015-07-14

provide 3.2% energy conversion efficiency (twice that of our CNT fiber muscles and 10X that of conducting polymer muscles ). They maintain stroke without...rubber dielectric muscle layer in twisted fiber drives torsional actuation. (2) One hundred times higher torsional stroke per muscle length...artificial muscles that provide giant stroke, fast response, high force generation, and long cycle life while optimizing energy conversion efficiencies
A new rectenna circuit using a bow-tie antenna for the conversion of microwave power to dc power

NASA Technical Reports Server (NTRS)

Tran, Michael; Nguyen, Cam

1993-01-01

The novel rectenna circuit presented, which integrated a bowtie antenna with a diode, is capable of broadband, high-efficiency operation, and is insensitive to incident field angle. The device is noted, moreover, to behave as a lowpass filter for dc output. For 2.45 GHz operation, a 79-percent conversion efficiency has been demonstrated.

CARBON DIOXIDE FIXATION.

DOE Office of Scientific and Technical Information (OSTI.GOV)

FUJITA,E.

2000-01-12

Solar carbon dioxide fixation offers the possibility of a renewable source of chemicals and fuels in the future. Its realization rests on future advances in the efficiency of solar energy collection and development of suitable catalysts for CO{sub 2} conversion. Recent achievements in the efficiency of solar energy conversion and in catalysis suggest that this approach holds a great deal of promise for contributing to future needs for fuels and chemicals.
Intermittent fasting induces hypothalamic modifications resulting in low feeding efficiency, low body mass and overeating.

PubMed

Chausse, Bruno; Solon, Carina; Caldeira da Silva, Camille C; Masselli Dos Reis, Ivan G; Manchado-Gobatto, Fúlvia B; Gobatto, Claudio A; Velloso, Licio A; Kowaltowski, Alicia J

2014-07-01

Intermittent fasting (IF) is an often-used intervention to decrease body mass. In male Sprague-Dawley rats, 24 hour cycles of IF result in light caloric restriction, reduced body mass gain, and significant decreases in the efficiency of energy conversion. Here, we study the metabolic effects of IF in order to uncover mechanisms involved in this lower energy conversion efficiency. After 3 weeks, IF animals displayed overeating during fed periods and lower body mass, accompanied by alterations in energy-related tissue mass. The lower efficiency of energy use was not due to uncoupling of muscle mitochondria. Enhanced lipid oxidation was observed during fasting days, whereas fed days were accompanied by higher metabolic rates. Furthermore, an increased expression of orexigenic neurotransmitters AGRP and NPY in the hypothalamus of IF animals was found, even on feeding days, which could explain the overeating pattern. Together, these effects provide a mechanistic explanation for the lower efficiency of energy conversion observed. Overall, we find that IF promotes changes in hypothalamic function that explain differences in body mass and caloric intake.
Efficiency enhancement using voltage biasing for ferroelectric polarization in dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Kim, Sangmo; Song, Myoung Geun; Bark, Chung Wung

2018-01-01

Dye-sensitized solar cells (DSSCs) are one of the most promising third generation solar cells that have been extensively researched over the past decade as alternative to silicon-based solar cells, due to their low production cost and high energy-conversion efficiency. In general, a DSSC consists of a transparent electrode, a counter electrode, and an electrolyte such as dye. To achieve high power-conversion efficiency in cells, many research groups have focused their efforts on developing efficient dyes for liquid electrolytes. In this work, we report on the photovoltaic properties of DSSCs fabricated using a mixture of TiO2 with nanosized Fe-doped bismuth lanthanum titanate (nFe-BLT) powder). Firstly, nFe-BLT powders were prepared using a high-energy ball milling process and then, TiO2 and nFe-BLT powders were stoichiometrically blended. Direct current (DC) bias of 20 MV/m was applied to lab-made DSSCs. With the optimal concentration of nFe-BLT doped in the electrode, their light-to-electricity conversion efficiency could be improved by ∼64% compared with DSSCs where no DC bias was applied.
High-Performance Polymer Solar Cells Based on a Wide-Bandgap Polymer Containing Pyrrolo[3,4- f ]benzotriazole-5,7-dione with a Power Conversion Efficiency of 8.63%

DOE PAGES

Lan, Liuyuan; Chen, Zhiming; Hu, Qin; ...

2016-04-25

In article 1600032, an efficient new wide-bandgap polymer based on a novel moiety of pyrrolo[3,4-f]benzotriazole-5,7-dione (TZBI) is developed by Lei Ying, Feng Lui, Thomas P. Russel, Fei Huang, and co-workers. The new chemistry enables fine electronic structure tuning and solution-processed single-junction polymer solar cells provided a remarkable power conversion efficiency of 8.63%. Full electrical and structural characterization reveales that TZBI is a promising building block for the application in highly efficient organic photovoltaics.
The ultimate efficiency of photosensitive systems

NASA Technical Reports Server (NTRS)

Buoncristiani, A. M.; Byvik, C. E.; Smith, B. T.

1981-01-01

These systems have in common two important but not independent features: they can produce a storable fuel, and they are sensitive only to radiant energy with a characteristic absorption spectrum. General analyses of the conversion efficiencies were made using the operational characteristics of each particular system. An efficiency analysis of a generalized system consisting of a blackbody source, a radiant energy converter having a threshold energy and operating temperature, and a reservoir is reported. This analysis is based upon the first and second laws of thermodynamics, and leads to a determination of the limiting or ultimate efficiency for an energy conversion system having a characteristic threshold.
Aqueous phase preparation of ultrasmall MoSe2 nanodots for efficient photothermal therapy of cancer cells

NASA Astrophysics Data System (ADS)

Yuwen, Lihui; Zhou, Jiajia; Zhang, Yuqian; Zhang, Qi; Shan, Jingyang; Luo, Zhimin; Weng, Lixing; Teng, Zhaogang; Wang, Lianhui

2016-01-01

Photothermal therapy (PTT) is a promising cancer treatment with both high effectiveness and fewer side effects. However, an ideal PTT agent not only needs strong absorption of near-infrared (NIR) light and high photothermal conversion efficiency, but also needs good biocompatibility, stability, and small size, which makes the design and preparation of a novel PTT agent a great challenge. In this work, we developed an ultrasonication-assisted liquid exfoliation method for the direct preparation of ultrasmall (2-3 nm) MoSe2 nanodots (NDs) in aqueous solution and demonstrated their superior properties as a PTT agent. The as-prepared MoSe2 NDs have strong absorption of NIR light and high photothermal conversion efficiency of about 46.5%. In vitro cellular experiments demonstrate that MoSe2 NDs have negligible cytotoxicity and can efficiently kill HeLa cells (human cervical cell line) under NIR laser (785 nm) irradiation.Photothermal therapy (PTT) is a promising cancer treatment with both high effectiveness and fewer side effects. However, an ideal PTT agent not only needs strong absorption of near-infrared (NIR) light and high photothermal conversion efficiency, but also needs good biocompatibility, stability, and small size, which makes the design and preparation of a novel PTT agent a great challenge. In this work, we developed an ultrasonication-assisted liquid exfoliation method for the direct preparation of ultrasmall (2-3 nm) MoSe2 nanodots (NDs) in aqueous solution and demonstrated their superior properties as a PTT agent. The as-prepared MoSe2 NDs have strong absorption of NIR light and high photothermal conversion efficiency of about 46.5%. In vitro cellular experiments demonstrate that MoSe2 NDs have negligible cytotoxicity and can efficiently kill HeLa cells (human cervical cell line) under NIR laser (785 nm) irradiation. Electronic supplementary information (ESI) available: Characterization, size distribution and EDS spectrum of MoSe2 NDs, calculation of the extinction coefficient and photothermal conversion efficiency of MoSe2 NDs. See DOI: 10.1039/c5nr08166a
A polymer tandem solar cell with 10.6% power conversion efficiency.

PubMed

You, Jingbi; Dou, Letian; Yoshimura, Ken; Kato, Takehito; Ohya, Kenichiro; Moriarty, Tom; Emery, Keith; Chen, Chun-Chao; Gao, Jing; Li, Gang; Yang, Yang

2013-01-01

An effective way to improve polymer solar cell efficiency is to use a tandem structure, as a broader part of the spectrum of solar radiation is used and the thermalization loss of photon energy is minimized. In the past, the lack of high-performance low-bandgap polymers was the major limiting factor for achieving high-performance tandem solar cell. Here we report the development of a high-performance low bandgap polymer (bandgap <1.4 eV), poly[2,7-(5,5-bis-(3,7-dimethyloctyl)-5H-dithieno[3,2-b:2',3'-d]pyran)-alt-4,7-(5,6-difluoro-2,1,3-benzothia diazole)] with a bandgap of 1.38 eV, high mobility, deep highest occupied molecular orbital. As a result, a single-junction device shows high external quantum efficiency of >60% and spectral response that extends to 900 nm, with a power conversion efficiency of 7.9%. The polymer enables a solution processed tandem solar cell with certified 10.6% power conversion efficiency under standard reporting conditions (25 °C, 1,000 Wm(-2), IEC 60904-3 global), which is the first certified polymer solar cell efficiency over 10%.
A polymer tandem solar cell with 10.6% power conversion efficiency

PubMed Central

You, Jingbi; Dou, Letian; Yoshimura, Ken; Kato, Takehito; Ohya, Kenichiro; Moriarty, Tom; Emery, Keith; Chen, Chun-Chao; Gao, Jing; Li, Gang; Yang, Yang

2013-01-01

An effective way to improve polymer solar cell efficiency is to use a tandem structure, as a broader part of the spectrum of solar radiation is used and the thermalization loss of photon energy is minimized. In the past, the lack of high-performance low-bandgap polymers was the major limiting factor for achieving high-performance tandem solar cell. Here we report the development of a high-performance low bandgap polymer (bandgap <1.4 eV), poly[2,7-(5,5-bis-(3,7-dimethyloctyl)-5H-dithieno[3,2-b:2′,3′-d]pyran)-alt-4,7-(5,6-difluoro-2,1,3-benzothia diazole)] with a bandgap of 1.38 eV, high mobility, deep highest occupied molecular orbital. As a result, a single-junction device shows high external quantum efficiency of >60% and spectral response that extends to 900 nm, with a power conversion efficiency of 7.9%. The polymer enables a solution processed tandem solar cell with certified 10.6% power conversion efficiency under standard reporting conditions (25 °C, 1,000 Wm−2, IEC 60904-3 global), which is the first certified polymer solar cell efficiency over 10%. PMID:23385590
Analysis of the reflective multibandgap solar cell concept

NASA Technical Reports Server (NTRS)

Stern, T. G.

1983-01-01

A new and unique approach to improving photovoltaic conversion efficiency, the reflective multiband gap solar cell concept, was examined. This concept uses back surface reflectors and light trapping with several physically separated cells of different bandgaps to make more effective use of energy from different portions of the solar spectrum. Preliminary tests performed under General Dynamics Independent Research and Development (IRAD) funding have demonstrated the capability for achieving in excess of 20% conversion efficiency with aluminum gallium arsenide and silicon. This study analyzed the ultimate potential for high conversion efficiency with 2, 3, 4, and 5 different bandgap materials, determined the appropriate bandgaps needed to achieve this optimized efficiency, and identified potential problems or constraints. The analysis indicated that an improvement in efficiency of better than 40% could be attained in this multibandgap approach, compared to a single bandgap converter under the same assumptions. Increased absorption loss on the back surface reflector was found to incur a minimal penalty on efficiency for two and three bandgap systems. Current models for bulk absorption losses in 3-5 materials were found to be inadequate for explaining laboratory observed transmission losses. Recommendations included the continued development of high bandgap back surface reflector cells and basic research on semiconductor absorption mechanisms.
Efficiency Analysis of Waveform Shape for Electrical Excitation of Nerve Fibers

PubMed Central

Wongsarnpigoon, Amorn; Woock, John P.; Grill, Warren M.

2011-01-01

Stimulation efficiency is an important consideration in the stimulation parameters of implantable neural stimulators. The objective of this study was to analyze the effects of waveform shape and duration on the charge, power, and energy efficiency of neural stimulation. Using a population model of mammalian axons and in vivo experiments on cat sciatic nerve, we analyzed the stimulation efficiency of four waveform shapes: square, rising exponential, decaying exponential, and rising ramp. No waveform was simultaneously energy-, charge-, and power-optimal, and differences in efficiency among waveform shapes varied with pulse width (PW) For short PWs (≤ 0.1 ms), square waveforms were no less energy-efficient than exponential waveforms, and the most charge-efficient shape was the ramp. For long PWs (≥0.5 ms), the square was the least energy-efficient and charge-efficient shape, but across most PWs, the square was the most power-efficient shape. Rising exponentials provided no practical gains in efficiency over the other shapes, and our results refute previous claims that the rising exponential is the energy-optimal shape. An improved understanding of how stimulation parameters affect stimulation efficiency will help improve the design and programming of implantable stimulators to minimize tissue damage and extend battery life. PMID:20388602
Energy efficient neural stimulation: coupling circuit design and membrane biophysics.

PubMed

Foutz, Thomas J; Ackermann, D Michael; Kilgore, Kevin L; McIntyre, Cameron C

2012-01-01

The delivery of therapeutic levels of electrical current to neural tissue is a well-established treatment for numerous indications such as Parkinson's disease and chronic pain. While the neuromodulation medical device industry has experienced steady clinical growth over the last two decades, much of the core technology underlying implanted pulse generators remain unchanged. In this study we propose some new methods for achieving increased energy-efficiency during neural stimulation. The first method exploits the biophysical features of excitable tissue through the use of a centered-triangular stimulation waveform. Neural activation with this waveform is achieved with a statistically significant reduction in energy compared to traditional rectangular waveforms. The second method demonstrates energy savings that could be achieved by advanced circuitry design. We show that the traditional practice of using a fixed compliance voltage for constant-current stimulation results in substantial energy loss. A portion of this energy can be recuperated by adjusting the compliance voltage to real-time requirements. Lastly, we demonstrate the potential impact of axon fiber diameter on defining the energy-optimal pulse-width for stimulation. When designing implantable pulse generators for energy efficiency, we propose that the future combination of a variable compliance system, a centered-triangular stimulus waveform, and an axon diameter specific stimulation pulse-width has great potential to reduce energy consumption and prolong battery life in neuromodulation devices.
Reconstruction of magnetic configurations in W7-X using artificial neural networks

NASA Astrophysics Data System (ADS)

Böckenhoff, Daniel; Blatzheim, Marko; Hölbe, Hauke; Niemann, Holger; Pisano, Fabio; Labahn, Roger; Pedersen, Thomas Sunn; The W7-X Team

2018-05-01

It is demonstrated that artificial neural networks can be used to accurately and efficiently predict details of the magnetic topology at the plasma edge of the Wendelstein 7-X stellarator, based on simulated as well as measured heat load patterns onto plasma-facing components observed with infrared cameras. The connection between heat load patterns and the magnetic topology is a challenging regression problem, but one that suits artificial neural networks well. The use of a neural network makes it feasible to analyze and control the plasma exhaust in real-time, an important goal for Wendelstein 7-X, and for magnetic confinement fusion research in general.
The optimization of force inputs for active structural acoustic control using a neural network

NASA Technical Reports Server (NTRS)

Cabell, R. H.; Lester, H. C.; Silcox, R. J.

1992-01-01

This paper investigates the use of a neural network to determine which force actuators, of a multi-actuator array, are best activated in order to achieve structural-acoustic control. The concept is demonstrated using a cylinder/cavity model on which the control forces, produced by piezoelectric actuators, are applied with the objective of reducing the interior noise. A two-layer neural network is employed and the back propagation solution is compared with the results calculated by a conventional, least-squares optimization analysis. The ability of the neural network to accurately and efficiently control actuator activation for interior noise reduction is demonstrated.
Efficiency enhancement of slow-wave electron-cyclotron maser by a second-order shaping of the magnetic field in the low-gain limit

NASA Astrophysics Data System (ADS)

Liu, Si-Jia; Zhang, Yu-Fei; Wang, Kang; Li, Yong-Ming; Jing, Jian

2017-03-01

Based on the anomalous Doppler effect, we put forward a proposal to enhance the conversion efficiency of the slow-wave electron cyclotron masers (ECM) under the resonance condition. Compared with previous studies, we add a second-order shaping term in the guild magnetic field. Theoretical analyses and numerical calculations show that it can enhance the conversion efficiency in the low-gain limit. The case of the initial velocity spread of electrons satisfying the Gaussian distribution is also analysed numerically.
Efficiency enhancement of slow-wave electron-cyclotron maser by a second-order shaping of the magnetic field in the low-gain limit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Si-Jia; Zhang, Yu-Fei; Wang, Kang

Based on the anomalous Doppler effect, we put forward a proposal to enhance the conversion efficiency of the slow-wave electron cyclotron masers (ECM) under the resonance condition. Compared with previous studies, we add a second-order shaping term in the guild magnetic field. Theoretical analyses and numerical calculations show that it can enhance the conversion efficiency in the low-gain limit. The case of the initial velocity spread of electrons satisfying the Gaussian distribution is also analysed numerically.
High-Performance Semitransparent Perovskite Solar Cells with 10% Power Conversion Efficiency and 25% Average Visible Transmittance Based on Transparent CuSCN as the Hole-Transporting Material

DOE PAGES

Jung, Jae Woong; Chueh, Chu-Chen; Jen, Alex K. -Y.

2015-07-06

High-performance planar heterojunction perovskite (CH3NH3PbI3) solar cell (PVSC) is demonstrated by utilizing CuSCN as a hole-transporting layer. Efficient hole-transport and hole-extraction at the CuSCN/CH3NH3PbI3 interface facilitate the PVSCs to reach 16% power conversion efficiency (PCE). In addition, excellent transparency of CuSCN enables high-performance semitransparent PVSC (10% PCE and 25% average visible transmittance) to be realized.
Polymer-Polymer Förster Resonance Energy Transfer Significantly Boosts the Power Conversion Efficiency of Bulk-Heterojunction Solar Cells.

PubMed

Gupta, Vinay; Bharti, Vishal; Kumar, Mahesh; Chand, Suresh; Heeger, Alan J

2015-08-01

Optically resonant donor polymers can exploit a wider range of the solar spectrum effectively without a complicated tandem design in an organic solar cell. Ultrafast Förster resonance energy transfer (FRET) in a polymer-polymer system that significantly improves the power conversion efficiency in bulk heterojunction polymer solar cells from 6.8% to 8.9% is demonstrated, thus paving the way to achieving 15% efficient solar cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
2D constant-loss taper for mode conversion

NASA Astrophysics Data System (ADS)

Horth, Alexandre; Kashyap, Raman; Quitoriano, Nathaniel J.

2015-03-01

Proposed in this manuscript is a novel taper geometry, the constant-loss taper (CLT). This geometry is derived with 1D slabs of silicon embedded in silicon dioxide using coupled-mode theory (CMT). The efficiency of the CLT is compared to both linear and parabolic tapers using CMT and 2D finite-difference time-domain simulations. It is shown that over a short 2D, 4.45 μm long taper the CLT's mode conversion efficiency is ~90% which is 10% and 18% more efficient than a 2D parabolic or linear taper, respectively.
Tandem filters using frequency selective surfaces for enhanced conversion efficiency in a thermophotovoltaic energy conversion system

DOEpatents

Dziendziel, Randolph J [Middle Grove, NY; DePoy, David Moore [Clifton Park, NY; Baldasaro, Paul Francis [Clifton Park, NY

2007-01-23

This invention relates to the field of thermophotovoltaic (TPV) direct energy conversion. In particular, TPV systems use filters to minimize parasitic absorption of below bandgap energy. This invention constitutes a novel combination of front surface filters to increase TPV conversion efficiency by reflecting useless below bandgap energy while transmitting a very high percentage of the useful above bandgap energy. In particular, a frequency selective surface is used in combination with an interference filter. The frequency selective surface provides high transmission of above bandgap energy and high reflection of long wavelength below bandgap energy. The interference filter maintains high transmission of above bandgap energy and provides high reflection of short wavelength below bandgap energy and a sharp transition from high transmission to high reflection.
Tandem filters using frequency selective surfaces for enhanced conversion efficiency in a thermophotovoltaic energy conversion system

DOEpatents

Dziendziel, Randolph J [Middle Grove, NY; Baldasaro, Paul F [Clifton Park, NY; DePoy, David M [Clifton Park, NY

2010-09-07

This invention relates to the field of thermophotovoltaic (TPV) direct energy conversion. In particular, TPV systems use filters to minimize parasitic absorption of below bandgap energy. This invention constitutes a novel combination of front surface filters to increase TPV conversion efficiency by reflecting useless below bandgap energy while transmitting a very high percentage of the useful above bandgap energy. In particular, a frequency selective surface is used in combination with an interference filter. The frequency selective surface provides high transmission of above bandgap energy and high reflection of long wavelength below bandgap energy. The interference filter maintains high transmission of above bandgap energy and provides high reflection of short wavelength below bandgap energy and a sharp transition from high transmission to high reflection.

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