A linear circuit analysis program with stiff systems capability

NASA Technical Reports Server (NTRS)

Cook, C. H.; Bavuso, S. J.

1973-01-01

Several existing network analysis programs have been modified and combined to employ a variable topological approach to circuit translation. Efficient numerical integration techniques are used for transient analysis.

Slow Computing Simulation of Bio-plausible Control

DTIC Science & Technology

2012-03-01

information networks, neuromorphic chips would become necessary. Small unstable flying platforms currently require RTK, GPS, or Vicon closed-circuit...Visual, and IR Sensing FPGA ASIC Neuromorphic Chip Simulation Quad Rotor Robotic Insect Uniform Independent Network Single Modality Neural Network... neuromorphic Processing across parallel computational elements =0.54 N u m b e r o f c o m p u ta tio n s - No info 14 integrated circuit

Basic dynamics from a pulse-coupled network of autonomous integrate-and-fire chaotic circuits.

PubMed

Nakano, H; Saito, T

2002-01-01

This paper studies basic dynamics from a novel pulse-coupled network (PCN). The unit element of the PCN is an integrate-and-fire circuit (IFC) that exhibits chaos. We an give an iff condition for the chaos generation. Using two IFC, we construct a master-slave PCN. It exhibits interesting chaos synchronous phenomena and their breakdown phenomena. We give basic classification of the phenomena and their existence regions can be elucidated in the parameter space. We then construct a ring-type PCN and elucidate that the PCN exhibits interesting grouping phenomena based on the chaos synchronization patterns. Using a simple test circuit, some of typical phenomena can be verified in the laboratory.

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

Hamlet, Jason; Pierson, Lyndon; Bauer, Todd

Supply chain security to detect, deter, and prevent the counterfeiting of networked and stand-alone integrated circuits (ICs) is critical to cyber security. Sandia National Laboratory researchers have developed IC ID to leverage Physically Unclonable Functions (PUFs) and strong cryptographic authentication to create a unique fingerprint for each integrated circuit. IC ID assures the authenticity of ICs to prevent tampering or malicious substitution.

Integration of multi-interface conversion channel using FPGA for modular photonic network

NASA Astrophysics Data System (ADS)

Janicki, Tomasz; Pozniak, Krzysztof T.; Romaniuk, Ryszard S.

2010-09-01

The article discusses the integration of different types of interfaces with FPGA circuits using a reconfigurable communication platform. The solution has been implemented in practice in a single node of a distributed measurement system. Construction of communication platform has been presented with its selected hardware modules, described in VHDL and implemented in FPGA circuits. The graphical user interface (GUI) has been described that allows a user to control the operation of the system. In the final part of the article selected practical solutions have been introduced. The whole measurement system resides on multi-gigabit optical network. The optical network construction is highly modular, reconfigurable and scalable.

Energy-efficient STDP-based learning circuits with memristor synapses

NASA Astrophysics Data System (ADS)

Wu, Xinyu; Saxena, Vishal; Campbell, Kristy A.

2014-05-01

It is now accepted that the traditional von Neumann architecture, with processor and memory separation, is ill suited to process parallel data streams which a mammalian brain can efficiently handle. Moreover, researchers now envision computing architectures which enable cognitive processing of massive amounts of data by identifying spatio-temporal relationships in real-time and solving complex pattern recognition problems. Memristor cross-point arrays, integrated with standard CMOS technology, are expected to result in massively parallel and low-power Neuromorphic computing architectures. Recently, significant progress has been made in spiking neural networks (SNN) which emulate data processing in the cortical brain. These architectures comprise of a dense network of neurons and the synapses formed between the axons and dendrites. Further, unsupervised or supervised competitive learning schemes are being investigated for global training of the network. In contrast to a software implementation, hardware realization of these networks requires massive circuit overhead for addressing and individually updating network weights. Instead, we employ bio-inspired learning rules such as the spike-timing-dependent plasticity (STDP) to efficiently update the network weights locally. To realize SNNs on a chip, we propose to use densely integrating mixed-signal integrate-andfire neurons (IFNs) and cross-point arrays of memristors in back-end-of-the-line (BEOL) of CMOS chips. Novel IFN circuits have been designed to drive memristive synapses in parallel while maintaining overall power efficiency (<1 pJ/spike/synapse), even at spike rate greater than 10 MHz. We present circuit design details and simulation results of the IFN with memristor synapses, its response to incoming spike trains and STDP learning characterization.

Adaptive Topological Configuration of an Integrated Circuit/Packet-Switched Computer Network.

DTIC Science & Technology

1984-01-01

Gitman et al. [45] state that there are basically two approaches to the integrated network design problem: (1) solve the link/capacity problem for...1972), 1385-1397. 33. Frank, H., and Gitman , I. Economic analysis of integrated voice and data networks: a case study. Proc. of IEEE 66 , 11 (Nov. 1978...1974), 1074-1079. 45. Gitman , I., Hsieh, W., and Occhiogrosso, B. J. Analysis and design of hybrid switching networks. IEEE Trans. on Comm. Com-29

Using a Conflict Map as an Instructional Tool To Change Student Conceptions in Simple Series Electric-Circuits.

ERIC Educational Resources Information Center

Tsai, Chin-Chung

2003-01-01

Examines the effects of using a conflict map on 8th grade students' conceptual change and ideational networks about simple series electric circuits. Analyzes student interview data through a flow map method. Shows that the use of conflict maps could help students construct greater, richer, and more integrated ideational networks about electric…

Analysis and synthesis of distributed-lumped-active networks by digital computer

NASA Technical Reports Server (NTRS)

1973-01-01

The use of digital computational techniques in the analysis and synthesis of DLA (distributed lumped active) networks is considered. This class of networks consists of three distinct types of elements, namely, distributed elements (modeled by partial differential equations), lumped elements (modeled by algebraic relations and ordinary differential equations), and active elements (modeled by algebraic relations). Such a characterization is applicable to a broad class of circuits, especially including those usually referred to as linear integrated circuits, since the fabrication techniques for such circuits readily produce elements which may be modeled as distributed, as well as the more conventional lumped and active ones.

CMOS image sensor with contour enhancement

NASA Astrophysics Data System (ADS)

Meng, Liya; Lai, Xiaofeng; Chen, Kun; Yuan, Xianghui

2010-10-01

Imitating the signal acquisition and processing of vertebrate retina, a CMOS image sensor with bionic pre-processing circuit is designed. Integration of signal-process circuit on-chip can reduce the requirement of bandwidth and precision of the subsequent interface circuit, and simplify the design of the computer-vision system. This signal pre-processing circuit consists of adaptive photoreceptor, spatial filtering resistive network and Op-Amp calculation circuit. The adaptive photoreceptor unit with a dynamic range of approximately 100 dB has a good self-adaptability for the transient changes in light intensity instead of intensity level itself. Spatial low-pass filtering resistive network used to mimic the function of horizontal cell, is composed of the horizontal resistor (HRES) circuit and OTA (Operational Transconductance Amplifier) circuit. HRES circuit, imitating dendrite of the neuron cell, comprises of two series MOS transistors operated in weak inversion region. Appending two diode-connected n-channel transistors to a simple transconductance amplifier forms the OTA Op-Amp circuit, which provides stable bias voltage for the gate of MOS transistors in HRES circuit, while serves as an OTA voltage follower to provide input voltage for the network nodes. The Op-Amp calculation circuit with a simple two-stage Op-Amp achieves the image contour enhancing. By adjusting the bias voltage of the resistive network, the smoothing effect can be tuned to change the effect of image's contour enhancement. Simulations of cell circuit and 16×16 2D circuit array are implemented using CSMC 0.5μm DPTM CMOS process.

R&D100: IC ID

ScienceCinema

Hamlet, Jason; Pierson, Lyndon; Bauer, Todd

2018-06-25

Supply chain security to detect, deter, and prevent the counterfeiting of networked and stand-alone integrated circuits (ICs) is critical to cyber security. Sandia National Laboratory researchers have developed IC ID to leverage Physically Unclonable Functions (PUFs) and strong cryptographic authentication to create a unique fingerprint for each integrated circuit. IC ID assures the authenticity of ICs to prevent tampering or malicious substitution.

On the Synchronization of EEG Spindle Waves

NASA Astrophysics Data System (ADS)

Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong

2000-06-01

Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.

A 40 GHz fully integrated circuit with a vector network analyzer and a coplanar-line-based detection area for circulating tumor cell analysis using 65 nm CMOS technology

NASA Astrophysics Data System (ADS)

Nakanishi, Taiki; Matsunaga, Maya; Kobayashi, Atsuki; Nakazato, Kazuo; Niitsu, Kiichi

2018-03-01

A 40-GHz fully integrated CMOS-based circuit for circulating tumor cells (CTC) analysis, consisting of an on-chip vector network analyzer (VNA) and a highly sensitive coplanar-line-based detection area is presented in this paper. In this work, we introduce a fully integrated architecture that eliminates unwanted parasitic effects. The proposed analyzer was designed using 65 nm CMOS technology, and SPICE and MWS simulations were used to validate its operation. The simulation confirmed that the proposed circuit can measure S-parameter shifts resulting from the addition of various types of tumor cells to the detection area, the data of which are provided in a previous study: the |S 21| values for HepG2, A549, and HEC-1-A cells are -0.683, -0.580, and -0.623 dB, respectively. Additionally, the measurement demonstrated an S-parameters reduction of -25.7% when a silicone resin was put on the circuit. Hence, the proposed system is expected to contribute to cancer diagnosis.

Advances in integrated photonic circuits for packet-switched interconnection

NASA Astrophysics Data System (ADS)

Williams, Kevin A.; Stabile, Ripalta

2014-03-01

Sustained increases in capacity and connectivity are needed to overcome congestion in a range of broadband communication network nodes. Packet routing and switching in the electronic domain are leading to unsustainable energy- and bandwidth-densities, motivating research into hybrid solutions: optical switching engines are introduced for massive-bandwidth data transport while the electronic domain is clocked at more modest GHz rates to manage routing. Commercially-deployed optical switching engines using MEMS technologies are unwieldy and too slow to reconfigure for future packet-based networking. Optoelectronic packet-compliant switch technologies have been demonstrated as laboratory prototypes, but they have so far mostly used discretely pigtailed components, which are impractical for control plane development and product assembly. Integrated photonics has long held the promise of reduced hardware complexity and may be the critical step towards packet-compliant optical switching engines. Recently a number of laboratories world-wide have prototyped optical switching circuits using monolithic integration technology with up to several hundreds of integrated optical components per chip. Our own work has focused on multi-input to multi-output switching matrices. Recently we have demonstrated 8×8×8λ space and wavelength selective switches using gated cyclic routers and 16×16 broadband switching chips using monolithic multi-stage networks. We now operate these advanced circuits with custom control planes implemented with FPGAs to explore real time packet routing in multi-wavelength, multi-port test-beds. We review our contributions in the context of state of the art photonic integrated circuit technology and packet optical switching hardware demonstrations.

Integrated Circuit For Simulation Of Neural Network

NASA Technical Reports Server (NTRS)

Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

1988-01-01

Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

Optimization Methods for Spiking Neurons and Networks

PubMed Central

Russell, Alexander; Orchard, Garrick; Dong, Yi; Mihalaş, Ştefan; Niebur, Ernst; Tapson, Jonathan; Etienne-Cummings, Ralph

2011-01-01

Spiking neurons and spiking neural circuits are finding uses in a multitude of tasks such as robotic locomotion control, neuroprosthetics, visual sensory processing, and audition. The desired neural output is achieved through the use of complex neuron models, or by combining multiple simple neurons into a network. In either case, a means for configuring the neuron or neural circuit is required. Manual manipulation of parameters is both time consuming and non-intuitive due to the nonlinear relationship between parameters and the neuron’s output. The complexity rises even further as the neurons are networked and the systems often become mathematically intractable. In large circuits, the desired behavior and timing of action potential trains may be known but the timing of the individual action potentials is unknown and unimportant, whereas in single neuron systems the timing of individual action potentials is critical. In this paper, we automate the process of finding parameters. To configure a single neuron we derive a maximum likelihood method for configuring a neuron model, specifically the Mihalas–Niebur Neuron. Similarly, to configure neural circuits, we show how we use genetic algorithms (GAs) to configure parameters for a network of simple integrate and fire with adaptation neurons. The GA approach is demonstrated both in software simulation and hardware implementation on a reconfigurable custom very large scale integration chip. PMID:20959265

UHF front-end feeding RFID-based body sensor networks by exploiting the reader signal

NASA Astrophysics Data System (ADS)

Pasca, M.; Colella, R.; Catarinucci, L.; Tarricone, L.; D'Amico, S.; Baschirotto, A.

2016-05-01

This paper presents an integrated, high-sensitivity UHF radio frequency identification (RFID) power management circuit for body sensor network applications. The circuit consists of a two-stage RF-DC Dickson's rectifier followed by an integrated five-stage DC-DC Pelliconi's charge pump driven by an ultralow start-up voltage LC oscillator. The DC-DC charge pump interposed between the RF-DC rectifier and the output load provides the RF to load isolation avoiding losses due to the diodes reverse saturation current. The RF-DC rectifier has been realized on FR4 substrate, while the charge pump and the oscillator have been realized in 180 nm complementary metal oxide semiconductor (CMOS) technology. Outdoor measurements demonstrate the ability of the power management circuit to provide 400 mV output voltage at 14 m distance from the UHF reader, in correspondence of -25 dBm input signal power. As demonstrated in the literature, such output voltage level is suitable to supply body sensor network nodes.

SDN architecture for optical packet and circuit integrated networks

NASA Astrophysics Data System (ADS)

Furukawa, Hideaki; Miyazawa, Takaya

2016-02-01

We have been developing an optical packet and circuit integrated (OPCI) network, which realizes dynamic optical path, high-density packet multiplexing, and flexible wavelength resource allocation. In the OPCI networks, a best-effort service and a QoS-guaranteed service are provided by employing optical packet switching (OPS) and optical circuit switching (OCS) respectively, and users can select these services. Different wavelength resources are assigned for OPS and OCS links, and the amount of their wavelength resources are dynamically changed in accordance with the service usage conditions. To apply OPCI networks into wide-area (core/metro) networks, we have developed an OPCI node with a distributed control mechanism. Moreover, our OPCI node works with a centralized control mechanism as well as a distributed one. It is therefore possible to realize SDN-based OPCI networks, where resource requests and a centralized configuration are carried out. In this paper, we show our SDN architecture for an OPS system that configures mapping tables between IP addresses and optical packet addresses and switching tables according to the requests from multiple users via a web interface. While OpenFlow-based centralized control protocol is coming into widespread use especially for single-administrative, small-area (LAN/data-center) networks. Here, we also show an interworking mechanism between OpenFlow-based networks (OFNs) and the OPCI network for constructing a wide-area network, and a control method of wavelength resource selection to automatically transfer diversified flows from OFNs to the OPCI network.

Transforming Ordinary Buildings into Smart Buildings via Low-Cost, Self-Powering Wireless Sensors & Sensor Networks

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

Feng, Philip

The research objective of this project is to design and demonstrate a low-cost, compact, easy-to-deploy, maintenance-free sensor node technology, and a network of such sensors, which enable the monitoring of multiphysical parameters and can transform today’s ordinary buildings into smart buildings with environmental awareness. We develop the sensor node and network via engineering and integration of existing technologies, including high-efficiency mechanical energy harvesting, and ultralow-power integrated circuits (ICs) for sensing and wireless communication. Through integration and innovative power management via specifically designed low-power control circuits for wireless sensing applications, and tailoring energy-harvesting components to indoor applications, the target products willmore » have smaller volume, higher efficiency, and much lower cost (in both manufacturing and maintenance) than the baseline technology. Our development and commercialization objective is to create prototypes for our target products under the CWRU-Intwine collaboration.« less

Low-sensitivity, frequency-selective amplifier circuits for hybrid and bipolar fabrication.

NASA Technical Reports Server (NTRS)

Pi, C.; Dunn, W. R., Jr.

1972-01-01

A network is described which is suitable for realizing a low-sensitivity high-Q second-order frequency-selective amplifier for high-frequency operation. Circuits are obtained from this network which are well suited for realizing monolithic integrated circuits and which do not require any process steps more critical than those used for conventional monolithic operational and video amplifiers. A single chip version using compatible thin-film techniques for the frequency determination elements is then feasible. Center frequency and bandwidth can be set independently by trimming two resistors. The frequency selective circuits have a low sensitivity to the process variables, and the sensitivity of the center frequency and bandwidth to changes in temperature is very low.

Integrating DNA strand-displacement circuitry with DNA tile self-assembly

PubMed Central

Zhang, David Yu; Hariadi, Rizal F.; Choi, Harry M.T.; Winfree, Erik

2013-01-01

DNA nanotechnology has emerged as a reliable and programmable way of controlling matter at the nanoscale through the specificity of Watson–Crick base pairing, allowing both complex self-assembled structures with nanometer precision and complex reaction networks implementing digital and analog behaviors. Here we show how two well-developed frameworks, DNA tile self-assembly and DNA strand-displacement circuits, can be systematically integrated to provide programmable kinetic control of self-assembly. We demonstrate the triggered and catalytic isothermal self-assembly of DNA nanotubes over 10 μm long from precursor DNA double-crossover tiles activated by an upstream DNA catalyst network. Integrating more sophisticated control circuits and tile systems could enable precise spatial and temporal organization of dynamic molecular structures. PMID:23756381

An Efficient Hardware Circuit for Spike Sorting Based on Competitive Learning Networks.

PubMed

Chen, Huan-Yuan; Chen, Chih-Chang; Hwang, Wen-Jyi

2017-09-28

This study aims to present an effective VLSI circuit for multi-channel spike sorting. The circuit supports the spike detection, feature extraction and classification operations. The detection circuit is implemented in accordance with the nonlinear energy operator algorithm. Both the peak detection and area computation operations are adopted for the realization of the hardware architecture for feature extraction. The resulting feature vectors are classified by a circuit for competitive learning (CL) neural networks. The CL circuit supports both online training and classification. In the proposed architecture, all the channels share the same detection, feature extraction, learning and classification circuits for a low area cost hardware implementation. The clock-gating technique is also employed for reducing the power dissipation. To evaluate the performance of the architecture, an application-specific integrated circuit (ASIC) implementation is presented. Experimental results demonstrate that the proposed circuit exhibits the advantages of a low chip area, a low power dissipation and a high classification success rate for spike sorting.

An Efficient Hardware Circuit for Spike Sorting Based on Competitive Learning Networks

PubMed Central

Chen, Huan-Yuan; Chen, Chih-Chang

2017-01-01

This study aims to present an effective VLSI circuit for multi-channel spike sorting. The circuit supports the spike detection, feature extraction and classification operations. The detection circuit is implemented in accordance with the nonlinear energy operator algorithm. Both the peak detection and area computation operations are adopted for the realization of the hardware architecture for feature extraction. The resulting feature vectors are classified by a circuit for competitive learning (CL) neural networks. The CL circuit supports both online training and classification. In the proposed architecture, all the channels share the same detection, feature extraction, learning and classification circuits for a low area cost hardware implementation. The clock-gating technique is also employed for reducing the power dissipation. To evaluate the performance of the architecture, an application-specific integrated circuit (ASIC) implementation is presented. Experimental results demonstrate that the proposed circuit exhibits the advantages of a low chip area, a low power dissipation and a high classification success rate for spike sorting. PMID:28956859

I/O impedance controller

DOEpatents

Ruesch, Rodney; Jenkins, Philip N.; Ma, Nan

2004-03-09

There is disclosed apparatus and apparatus for impedance control to provide for controlling the impedance of a communication circuit using an all-digital impedance control circuit wherein one or more control bits are used to tune the output impedance. In one example embodiment, the impedance control circuit is fabricated using circuit components found in a standard macro library of a computer aided design system. According to another example embodiment, there is provided a control for an output driver on an integrated circuit ("IC") device to provide for forming a resistor divider network with the output driver and a resistor off the IC device so that the divider network produces an output voltage, comparing the output voltage of the divider network with a reference voltage, and adjusting the output impedance of the output driver to attempt to match the output voltage of the divider network and the reference voltage. Also disclosed is over-sampling the divider network voltage, storing the results of the over sampling, repeating the over-sampling and storing, averaging the results of multiple over sampling operations, controlling the impedance with a plurality of bits forming a word, and updating the value of the word by only one least significant bit at a time.

Fiber-Optic Distribution Of Pulsed Power To Multiple Sensors

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1996-01-01

Optoelectronic systems designed according to time-sharing scheme distribute optical power to multiple integrated-circuit-based sensors in fiber-optic networks. Networks combine flexibility of electronic sensing circuits with advantage of electrical isolation afforded by use of optical fibers instead of electrical conductors to transmit both signals and power. Fiber optics resist corrosion and immune to electromagnetic interference. Sensor networks of this type useful in variety of applications; for example, in monitoring strains in aircraft, buildings, and bridges, and in monitoring and controlling shapes of flexible structures.

LEOPACK The integrated services communications system based on LEO satellites

NASA Astrophysics Data System (ADS)

Negoda, A.; Bunin, S.; Bushuev, E.; Dranovsky, V.

LEOPACK is yet another LEO satellite project which provides global integrated services for 'business' communications. It utilizes packet rather then circuit switching in both terrestrial and satellite chains as well as cellular approach for frequencies use. Original multiple access protocols and decentralized network control make it possible to organize regionally or logically independent and world-wide networks. Relatively small number of satellites (28) provides virtually global network coverage.

STICAP: A linear circuit analysis program with stiff systems capability. Volume 1: Theory manual. [network analysis

NASA Technical Reports Server (NTRS)

Cooke, C. H.

1975-01-01

STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.

The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing

PubMed Central

Chang, Po-Yen; Su, Ta-Shun; Shih, Chi-Tin; Lo, Chung-Chuan

2017-01-01

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of “atypical” neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the “typical” neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex. PMID:28443014

Reconfigurable SDM Switching Using Novel Silicon Photonic Integrated Circuit.

PubMed

Ding, Yunhong; Kamchevska, Valerija; Dalgaard, Kjeld; Ye, Feihong; Asif, Rameez; Gross, Simon; Withford, Michael J; Galili, Michael; Morioka, Toshio; Oxenløwe, Leif Katsuo

2016-12-21

Space division multiplexing using multicore fibers is becoming a more and more promising technology. In space-division multiplexing fiber network, the reconfigurable switch is one of the most critical components in network nodes. In this paper we for the first time demonstrate reconfigurable space-division multiplexing switching using silicon photonic integrated circuit, which is fabricated on a novel silicon-on-insulator platform with buried Al mirror. The silicon photonic integrated circuit is composed of a 7 × 7 switch and low loss grating coupler array based multicore fiber couplers. Thanks to the Al mirror, grating couplers with ultra-low coupling loss with optical multicore fibers is achieved. The lowest total insertion loss of the silicon integrated circuit is as low as 4.5 dB, with low crosstalk lower than -30 dB. Excellent performances in terms of low insertion loss and low crosstalk are obtained for the whole C-band. 1 Tb/s/core transmission over a 2-km 7-core fiber and space-division multiplexing switching is demonstrated successfully. Bit error rate performance below 10 -9 is obtained for all spatial channels with low power penalty. The proposed design can be easily upgraded to reconfigurable optical add/drop multiplexer capable of switching several multicore fibers.

Reconfigurable SDM Switching Using Novel Silicon Photonic Integrated Circuit

NASA Astrophysics Data System (ADS)

Ding, Yunhong; Kamchevska, Valerija; Dalgaard, Kjeld; Ye, Feihong; Asif, Rameez; Gross, Simon; Withford, Michael J.; Galili, Michael; Morioka, Toshio; Oxenløwe, Leif Katsuo

2016-12-01

Space division multiplexing using multicore fibers is becoming a more and more promising technology. In space-division multiplexing fiber network, the reconfigurable switch is one of the most critical components in network nodes. In this paper we for the first time demonstrate reconfigurable space-division multiplexing switching using silicon photonic integrated circuit, which is fabricated on a novel silicon-on-insulator platform with buried Al mirror. The silicon photonic integrated circuit is composed of a 7 × 7 switch and low loss grating coupler array based multicore fiber couplers. Thanks to the Al mirror, grating couplers with ultra-low coupling loss with optical multicore fibers is achieved. The lowest total insertion loss of the silicon integrated circuit is as low as 4.5 dB, with low crosstalk lower than -30 dB. Excellent performances in terms of low insertion loss and low crosstalk are obtained for the whole C-band. 1 Tb/s/core transmission over a 2-km 7-core fiber and space-division multiplexing switching is demonstrated successfully. Bit error rate performance below 10-9 is obtained for all spatial channels with low power penalty. The proposed design can be easily upgraded to reconfigurable optical add/drop multiplexer capable of switching several multicore fibers.

Reconfigurable SDM Switching Using Novel Silicon Photonic Integrated Circuit

PubMed Central

Ding, Yunhong; Kamchevska, Valerija; Dalgaard, Kjeld; Ye, Feihong; Asif, Rameez; Gross, Simon; Withford, Michael J.; Galili, Michael; Morioka, Toshio; Oxenløwe, Leif Katsuo

2016-01-01

Space division multiplexing using multicore fibers is becoming a more and more promising technology. In space-division multiplexing fiber network, the reconfigurable switch is one of the most critical components in network nodes. In this paper we for the first time demonstrate reconfigurable space-division multiplexing switching using silicon photonic integrated circuit, which is fabricated on a novel silicon-on-insulator platform with buried Al mirror. The silicon photonic integrated circuit is composed of a 7 × 7 switch and low loss grating coupler array based multicore fiber couplers. Thanks to the Al mirror, grating couplers with ultra-low coupling loss with optical multicore fibers is achieved. The lowest total insertion loss of the silicon integrated circuit is as low as 4.5 dB, with low crosstalk lower than −30 dB. Excellent performances in terms of low insertion loss and low crosstalk are obtained for the whole C-band. 1 Tb/s/core transmission over a 2-km 7-core fiber and space-division multiplexing switching is demonstrated successfully. Bit error rate performance below 10−9 is obtained for all spatial channels with low power penalty. The proposed design can be easily upgraded to reconfigurable optical add/drop multiplexer capable of switching several multicore fibers. PMID:28000735

Integrated neuron circuit for implementing neuromorphic system with synaptic device

NASA Astrophysics Data System (ADS)

Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

2018-02-01

In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

Temporal coding in a silicon network of integrate-and-fire neurons.

PubMed

Liu, Shih-Chii; Douglas, Rodney

2004-09-01

Spatio-temporal processing of spike trains by neuronal networks depends on a variety of mechanisms distributed across synapses, dendrites, and somata. In natural systems, the spike trains and the processing mechanisms cohere though their common physical instantiation. This coherence is lost when the natural system is encoded for simulation on a general purpose computer. By contrast, analog VLSI circuits are, like neurons, inherently related by their real-time physics, and so, could provide a useful substrate for exploring neuronlike event-based processing. Here, we describe a hybrid analog-digital VLSI chip comprising a set of integrate-and-fire neurons and short-term dynamical synapses that can be configured into simple network architectures with some properties of neocortical neuronal circuits. We show that, despite considerable fabrication variance in the properties of individual neurons, the chip offers a viable substrate for exploring real-time spike-based processing in networks of neurons.

A binary-decision-diagram-based two-bit arithmetic logic unit on a GaAs-based regular nanowire network with hexagonal topology.

PubMed

Zhao, Hong-Quan; Kasai, Seiya; Shiratori, Yuta; Hashizume, Tamotsu

2009-06-17

A two-bit arithmetic logic unit (ALU) was successfully fabricated on a GaAs-based regular nanowire network with hexagonal topology. This fundamental building block of central processing units can be implemented on a regular nanowire network structure with simple circuit architecture based on graphical representation of logic functions using a binary decision diagram and topology control of the graph. The four-instruction ALU was designed by integrating subgraphs representing each instruction, and the circuitry was implemented by transferring the logical graph structure to a GaAs-based nanowire network formed by electron beam lithography and wet chemical etching. A path switching function was implemented in nodes by Schottky wrap gate control of nanowires. The fabricated circuit integrating 32 node devices exhibits the correct output waveforms at room temperature allowing for threshold voltage variation.

High-Performance Complementary Transistors and Medium-Scale Integrated Circuits Based on Carbon Nanotube Thin Films.

PubMed

Yang, Yingjun; Ding, Li; Han, Jie; Zhang, Zhiyong; Peng, Lian-Mao

2017-04-25

Solution-derived carbon nanotube (CNT) network films with high semiconducting purity are suitable materials for the wafer-scale fabrication of field-effect transistors (FETs) and integrated circuits (ICs). However, it is challenging to realize high-performance complementary metal-oxide semiconductor (CMOS) FETs with high yield and stability on such CNT network films, and this difficulty hinders the development of CNT-film-based ICs. In this work, we developed a doping-free process for the fabrication of CMOS FETs based on solution-processed CNT network films, in which the polarity of the FETs was controlled using Sc or Pd as the source/drain contacts to selectively inject carriers into the channels. The fabricated top-gated CMOS FETs showed high symmetry between the characteristics of n- and p-type devices and exhibited high-performance uniformity and excellent scalability down to a gate length of 1 μm. Many common types of CMOS ICs, including typical logic gates, sequential circuits, and arithmetic units, were constructed based on CNT films, and the fabricated ICs exhibited rail-to-rail outputs because of the high noise margin of CMOS circuits. In particular, 4-bit full adders consisting of 132 CMOS FETs were realized with 100% yield, thereby demonstrating that this CMOS technology shows the potential to advance the development of medium-scale CNT-network-film-based ICs.

Op-amp gyrator simulates high Q inductor

NASA Technical Reports Server (NTRS)

Sutherland, W. C.

1977-01-01

Gyrator circuit consisting of dual operational amplifier and four resistors inverts impedance of capacitor to simulate inductor. Synthetic inductor has high Q factor, good stability, wide bandwidth, and easily determined value of inductance that is independent of frequency. It readily lends itself to integrated-circuit applications, including filter networks.

An analog silicon retina with multichip configuration.

PubMed

Kameda, Seiji; Yagi, Tetsuya

2006-01-01

The neuromorphic silicon retina is a novel analog very large scale integrated circuit that emulates the structure and the function of the retinal neuronal circuit. We fabricated a neuromorphic silicon retina, in which sample/hold circuits were embedded to generate fluctuation-suppressed outputs in the previous study [1]. The applications of this silicon retina, however, are limited because of a low spatial resolution and computational variability. In this paper, we have fabricated a multichip silicon retina in which the functional network circuits are divided into two chips: the photoreceptor network chip (P chip) and the horizontal cell network chip (H chip). The output images of the P chip are transferred to the H chip with analog voltages through the line-parallel transfer bus. The sample/hold circuits embedded in the P and H chips compensate for the pattern noise generated on the circuits, including the analog communication pathway. Using the multichip silicon retina together with an off-chip differential amplifier, spatial filtering of the image with an odd- and an even-symmetric orientation selective receptive fields was carried out in real time. The analog data transfer method in the present multichip silicon retina is useful to design analog neuromorphic multichip systems that mimic the hierarchical structure of neuronal networks in the visual system.

Two-Dimensional Metal-Free Organic Multiferroic Material for Design of Multifunctional Integrated Circuits.

PubMed

Tu, Zhengyuan; Wu, Menghao; Zeng, Xiao Cheng

2017-05-04

Coexistence of ferromagnetism and ferroelectricity in a single 2D material is highly desirable for integration of multifunctional units in 2D material-based circuits. We report theoretical evidence of C 6 N 8 H organic network as being the first 2D organic multiferroic material with coexisting ferromagnetic and ferroelectric properties. The ferroelectricity stems from multimode proton-transfer within the 2D C 6 N 8 H network, in which a long-range proton-transfer mode is enabled by the facilitation of oxygen molecule when the network is exposed to the air. Such oxygen-assisted ferroelectricity also leads to a high Curie temperature and coupling between ferroelectricity and ferromagnetism. We also find that hydrogenation and carbon doping can transform the 2D g-C 3 N 4 network from an insulator to an n-type/p-type magnetic semiconductor with modest bandgap. Akin to the dopant induced n/p channels in silicon wafer, a variety of dopant created functional units can be integrated into the g-C 3 N 4 wafer by design for nanoelectronic applications.

Flow control using audio tones in resonant microfluidic networks: towards cell-phone controlled lab-on-a-chip devices.

PubMed

Phillips, Reid H; Jain, Rahil; Browning, Yoni; Shah, Rachana; Kauffman, Peter; Dinh, Doan; Lutz, Barry R

2016-08-16

Fluid control remains a challenge in development of portable lab-on-a-chip devices. Here, we show that microfluidic networks driven by single-frequency audio tones create resonant oscillating flow that is predicted by equivalent electrical circuit models. We fabricated microfluidic devices with fluidic resistors (R), inductors (L), and capacitors (C) to create RLC networks with band-pass resonance in the audible frequency range available on portable audio devices. Microfluidic devices were fabricated from laser-cut adhesive plastic, and a "buzzer" was glued to a diaphragm (capacitor) to integrate the actuator on the device. The AC flowrate magnitude was measured by imaging oscillation of bead tracers to allow direct comparison to the RLC circuit model across the frequency range. We present a systematic build-up from single-channel systems to multi-channel (3-channel) networks, and show that RLC circuit models predict complex frequency-dependent interactions within multi-channel networks. Finally, we show that adding flow rectifying valves to the network creates pumps that can be driven by amplified and non-amplified audio tones from common audio devices (iPod and iPhone). This work shows that RLC circuit models predict resonant flow responses in multi-channel fluidic networks as a step towards microfluidic devices controlled by audio tones.

Controllability of structural brain networks

NASA Astrophysics Data System (ADS)

Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

2015-10-01

Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.

Functional neural networks underlying response inhibition in adolescents and adults.

PubMed

Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2007-07-19

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

Functional neural networks underlying response inhibition in adolescents and adults

PubMed Central

Stevens, Michael C.; Kiehl, Kent A.; Pearlson, Godfrey D.; Calhoun, Vince D.

2008-01-01

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally-integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by frontostriatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development. PMID:17467816

Highly Uniform Carbon Nanotube Field-Effect Transistors and Medium Scale Integrated Circuits.

PubMed

Chen, Bingyan; Zhang, Panpan; Ding, Li; Han, Jie; Qiu, Song; Li, Qingwen; Zhang, Zhiyong; Peng, Lian-Mao

2016-08-10

Top-gated p-type field-effect transistors (FETs) have been fabricated in batch based on carbon nanotube (CNT) network thin films prepared from CNT solution and present high yield and highly uniform performance with small threshold voltage distribution with standard deviation of 34 mV. According to the property of FETs, various logical and arithmetical gates, shifters, and d-latch circuits were designed and demonstrated with rail-to-rail output. In particular, a 4-bit adder consisting of 140 p-type CNT FETs was demonstrated with higher packing density and lower supply voltage than other published integrated circuits based on CNT films, which indicates that CNT based integrated circuits can reach to medium scale. In addition, a 2-bit multiplier has been realized for the first time. Benefitted from the high uniformity and suitable threshold voltage of CNT FETs, all of the fabricated circuits based on CNT FETs can be driven by a single voltage as small as 2 V.

Gain Modulation by an Urgency Signal Controls the Speed–Accuracy Trade-Off in a Network Model of a Cortical Decision Circuit

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2011-01-01

The speed–accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time. PMID:21415911

Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

PubMed

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

2011-01-01

The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

Tumor Immunotherapy by Gene-circuit Recruited Immunomodulatory Systems (TIGRIS) for Prostate Cancer

DTIC Science & Technology

2017-09-01

Fu, X., Huang, W., and Cai, Z. (2014). Syn- thesizing AND gate genetic circuits based on CRISPR -Cas9 for identification of bladder cancer cells. Nat...and Lu, T.K. (2014). Multi- plexed and programmable regulation of gene networks with an integrated RNA and CRISPR /Cas toolkit in human cells. Mol

Wiring Together Synthetic Bacterial Consortia to Create a Biological Integrated Circuit.

PubMed

Perry, Nicolas; Nelson, Edward M; Timp, Gregory

2016-12-16

The promise of adapting biology to information processing will not be realized until engineered gene circuits, operating in different cell populations, can be wired together to express a predictable function. Here, elementary biological integrated circuits (BICs), consisting of two sets of transmitter and receiver gene circuit modules with embedded memory placed in separate cell populations, were meticulously assembled using live cell lithography and wired together by the mass transport of quorum-sensing (QS) signal molecules to form two isolated communication links (comlinks). The comlink dynamics were tested by broadcasting "clock" pulses of inducers into the networks and measuring the responses of functionally linked fluorescent reporters, and then modeled through simulations that realistically captured the protein production and molecular transport. These results show that the comlinks were isolated and each mimicked aspects of the synchronous, sequential networks used in digital computing. The observations about the flow conditions, derived from numerical simulations, and the biofilm architectures that foster or silence cell-to-cell communications have implications for everything from decontamination of drinking water to bacterial virulence.

Artificial immune system algorithm in VLSI circuit configuration

NASA Astrophysics Data System (ADS)

Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

2017-08-01

In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

Testing Fixture For Microwave Integrated Circuits

NASA Technical Reports Server (NTRS)

Romanofsky, Robert; Shalkhauser, Kurt

1989-01-01

Testing fixture facilitates radio-frequency characterization of microwave and millimeter-wave integrated circuits. Includes base onto which two cosine-tapered ridge waveguide-to-microstrip transitions fastened. Length and profile of taper determined analytically to provide maximum bandwidth and minimum insertion loss. Each cosine taper provides transformation from high impedance of waveguide to characteristic impedance of microstrip. Used in conjunction with automatic network analyzer to provide user with deembedded scattering parameters of device under test. Operates from 26.5 to 40.0 GHz, but operation extends to much higher frequencies.

Neuropeptide Signaling Networks and Brain Circuit Plasticity.

PubMed

McClard, Cynthia K; Arenkiel, Benjamin R

2018-01-01

The brain is a remarkable network of circuits dedicated to sensory integration, perception, and response. The computational power of the brain is estimated to dwarf that of most modern supercomputers, but perhaps its most fascinating capability is to structurally refine itself in response to experience. In the language of computers, the brain is loaded with programs that encode when and how to alter its own hardware. This programmed "plasticity" is a critical mechanism by which the brain shapes behavior to adapt to changing environments. The expansive array of molecular commands that help execute this programming is beginning to emerge. Notably, several neuropeptide transmitters, previously best characterized for their roles in hypothalamic endocrine regulation, have increasingly been recognized for mediating activity-dependent refinement of local brain circuits. Here, we discuss recent discoveries that reveal how local signaling by corticotropin-releasing hormone reshapes mouse olfactory bulb circuits in response to activity and further explore how other local neuropeptide networks may function toward similar ends.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells.

PubMed

Angelici, Bartolomeo; Mailand, Erik; Haefliger, Benjamin; Benenson, Yaakov

2016-08-30

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Pulse-firing winner-take-all networks

NASA Technical Reports Server (NTRS)

Meador, Jack L.

1991-01-01

Winner-take-all (WTA) neural networks using pulse-firing processing elements are introduced. In the pulse-firing WTA (PWTA) networks described, input and activation signal shunting is controlled by one shared lateral inhibition signal. This organization yields an O(n) area complexity that is convenient for integrated circuit implementation. Appropriately specified network parameters allow for the accurate continuous evaluation of inputs using a signal representation compatible with established pulse-firing neural network implementations.

Genetic programs constructed from layered logic gates in single cells

PubMed Central

Moon, Tae Seok; Lou, Chunbo; Tamsir, Alvin; Stanton, Brynne C.; Voigt, Christopher A.

2014-01-01

Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics1. These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits2–6, and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits1,7. Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli. Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator–chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells. PMID:23041931

Peak holding circuit for extremely narrow pulses

NASA Technical Reports Server (NTRS)

Oneill, R. W. (Inventor)

1975-01-01

An improved pulse stretching circuit comprising: a high speed wide-band amplifier connected in a fast charge integrator configuration; a holding circuit including a capacitor connected in parallel with a discharging network which employs a resistor and an FET; and an output buffer amplifier. Input pulses of very short duration are applied to the integrator charging the capacitor to a value proportional to the input pulse amplitude. After a predetermined period of time, conventional circuitry generates a dump pulse which is applied to the gate of the FET making a low resistance path to ground which discharges the capacitor. When the dump pulse terminates, the circuit is ready to accept another pulse to be stretched. The very short input pulses are thus stretched in width so that they may be analyzed by conventional pulse height analyzers.

A high-efficiency low-voltage class-E PA for IoT applications in sub-1 GHz frequency range

NASA Astrophysics Data System (ADS)

Zhou, Chenyi; Lu, Zhenghao; Gu, Jiangmin; Yu, Xiaopeng

2017-10-01

We present and propose a complete and iterative integrated-circuit and electro-magnetic (EM) co-design methodology and procedure for a low-voltage sub-1 GHz class-E PA. The presented class-E PA consists of the on-chip power transistor, the on-chip gate driving circuits, the off-chip tunable LC load network and the off-chip LC ladder low pass filter. The design methodology includes an explicit design equation based circuit components values' analysis and numerical derivation, output power targeted transistor size and low pass filter design, and power efficiency oriented design optimization. The proposed design procedure includes the power efficiency oriented LC network tuning, the detailed circuit/EM co-simulation plan on integrated circuit level, package level and PCB level to ensure an accurate simulation to measurement match and first pass design success. The proposed PA is targeted to achieve more than 15 dBm output power delivery and 40% power efficiency at 433 MHz frequency band with 1.5 V low voltage supply. The LC load network is designed to be off-chip for the purpose of easy tuning and optimization. The same circuit can be extended to all sub-1 GHz applications with the same tuning and optimization on the load network at different frequencies. The amplifier is implemented in 0.13 μm CMOS technology with a core area occupation of 400 μm by 300 μm. Measurement results showed that it provided power delivery of 16.42 dBm at antenna with efficiency of 40.6%. A harmonics suppression of 44 dBc is achieved, making it suitable for massive deployment of IoT devices. Project supported by the National Natural Science Foundation of China (No. 61574125) and the Industry Innovation Project of Suzhou City of China (No. SYG201641).

Biosensor system-on-a-chip including CMOS-based signal processing circuits and 64 carbon nanotube-based sensors for the detection of a neurotransmitter.

PubMed

Lee, Byung Yang; Seo, Sung Min; Lee, Dong Joon; Lee, Minbaek; Lee, Joohyung; Cheon, Jun-Ho; Cho, Eunju; Lee, Hyunjoong; Chung, In-Young; Park, Young June; Kim, Suhwan; Hong, Seunghun

2010-04-07

We developed a carbon nanotube (CNT)-based biosensor system-on-a-chip (SoC) for the detection of a neurotransmitter. Here, 64 CNT-based sensors were integrated with silicon-based signal processing circuits in a single chip, which was made possible by combining several technological breakthroughs such as efficient signal processing, uniform CNT networks, and biocompatible functionalization of CNT-based sensors. The chip was utilized to detect glutamate, a neurotransmitter, where ammonia, a byproduct of the enzymatic reaction of glutamate and glutamate oxidase on CNT-based sensors, modulated the conductance signals to the CNT-based sensors. This is a major technological advancement in the integration of CNT-based sensors with microelectronics, and this chip can be readily integrated with larger scale lab-on-a-chip (LoC) systems for various applications such as LoC systems for neural networks.

Adaptation disrupts motion integration in the primate dorsal stream

PubMed Central

Patterson, Carlyn A.; Wissig, Stephanie C.; Kohn, Adam

2014-01-01

Summary Sensory systems adjust continuously to the environment. The effects of recent sensory experience—or adaptation—are typically assayed by recording in a relevant subcortical or cortical network. However, adaptation effects cannot be localized to a single, local network. Adjustments in one circuit or area will alter the input provided to others, with unclear consequences for computations implemented in the downstream circuit. Here we show that prolonged adaptation with drifting gratings, which alters responses in the early visual system, impedes the ability of area MT neurons to integrate motion signals in plaid stimuli. Perceptual experiments reveal a corresponding loss of plaid coherence. A simple computational model shows how the altered representation of motion signals in early cortex can derail integration in MT. Our results suggest that the effects of adaptation cascade through the visual system, derailing the downstream representation of distinct stimulus attributes. PMID:24507198

Final Report for the project titled "Enabling Supernova Computations by Integrated Transport and Provisioning Methods Optimized for Dedicated Channels"

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

Malathi Veeraraghavan

2007-10-31

A high-speed optical circuit network is one that offers users rate-guaranteed connectivity between two endpoints, unlike today’s IP-routed Internet in which the rate available to a pair of users fluctuates based on the volume of competing traffic. This particular research project advanced our understanding of circuit networks in two ways. First, transport protocols were developed for circuit networks. In a circuit network, since bandwidth resources are reserved for each circuit on an end-to-end basis (much like how a person reserves a seat on every leg of a multi-segment flight), and the sender is limited to send at the rate ofmore » the circuit, there is no possibility of congestion during data transfer. Therefore, no congestion control functions are necessary in a transport protocol designed for circuits. However, error control and flow control are still required because bits can become errored due to noise and interference even on highly reliable optical links, and receivers can, due to multitasking or other reasons, not deplete the receive buffer fast enough to keep up with the sending rate (e.g., if the receiving host is multitasking between receiving a file transfer and some other computation). In this work, we developed two transport protocols for circuits, both of which are described below. Second, this project developed techniques for internetworking different types of connection-oriented networks, which are of two types: circuit-switched or packet-switched. In circuit-switched networks, multiplexing on links is “position based,” where “position” refers to the frequency, time slot, and port (fiber), while connection-oriented packet-switched networks use packet header information to demultiplex packets and switch them from node to node. The latter are commonly referred to as virtual circuit networks. Examples of circuit networks are time-division multiplexed Synchronous Optical Network/Synchronous Digital Hierarchy (SONET/SDH) and Wavelength Division Multiplexing (WDM) networks, while examples of virtual-circuit networks are MultiProtocol Label Switched (MPLS) networks and Ethernet Virtual Local Area Network (VLAN) networks. A series of new technologies have been developed to carry Ethernet VLAN tagged frames on SONET/SDH and WDM networks, such as Generic Framing Procedure (GFP) and ITU G.709, respectively. These technologies form the basis of our solution for connection-oriented internetworking. The benefit of developing such an architecture is that it allows different providers to choose different connection-oriented networking technologies for their networks, and yet be able to allow their customers to connect to those of other providers. As Metcalfe, the inventor of Ethernet, noted, the value of a network service grows exponentially with the number of endpoints to which any single endpoint can connect. Therefore internetworking solutions are key to commercial success. The technical effectiveness of our solutions was measured with proof-of-concept prototypes and experiments. These solutions were shown to be highly effective. Economic feasibility requires business case analyses that were beyond the scope of this project. The project results are beneficial to the public as they demonstrate the viability of simultaneously supporting different types of networks and data communication services much like the variety of services available for the transportation of people and goods. For example, Fedex service offers a deadline based delivery while the USPS offers basic package delivery service. Similarly, a circuit network can offer a deadline based delivery of a data file while the IP-routed network offers only basic delivery service with no guarantees. Two project Web sites, 13 publications, 7 software programs, 21 presentations resulted from this work. This report provides the complete list of publications, software programs and presentations. As for student education and training (human resources), this DOE project, along with an NSF project, jointly supported two postdoctoral fellowships, three PhDs, three Masters, and two undergraduate students. Specifically, two of the Masters students were directly funded on this DOE project.« less

Current-mode subthreshold MOS implementation of the Herault-Jutten autoadaptive network

NASA Astrophysics Data System (ADS)

Cohen, Marc H.; Andreou, Andreas G.

1992-05-01

The translinear circuits in subthreshold MOS technology and current-mode design techniques for the implementation of neuromorphic analog network processing are investigated. The architecture, also known as the Herault-Jutten network, performs an independent component analysis and is essentially a continuous-time recursive linear adaptive filter. Analog I/O interface, weight coefficients, and adaptation blocks are all integrated on the chip. A small network with six neurons and 30 synapses was fabricated in a 2-microns n-well double-polysilicon, double-metal CMOS process. Circuit designs at the transistor level yield area-efficient implementations for neurons, synapses, and the adaptation blocks. The design methodology and constraints as well as test results from the fabricated chips are discussed.

Inverter Circuits Using ZnO Nanoparticle Based Thin-Film Transistors for Flexible Electronic Applications

PubMed Central

Vidor, Fábio F.; Meyers, Thorsten; Hilleringmann, Ulrich

2016-01-01

Innovative systems exploring the flexibility and the transparency of modern semiconducting materials are being widely researched by the scientific community and by several companies. For a low-cost production and large surface area applications, thin-film transistors (TFTs) are the key elements driving the system currents. In order to maintain a cost efficient integration process, solution based materials are used as they show an outstanding tradeoff between cost and system complexity. In this paper, we discuss the integration process of ZnO nanoparticle TFTs using a high-k resin as gate dielectric. The performance in dependence on the transistor structure has been investigated, and inverted staggered setups depict an improved performance over the coplanar device increasing both the field-effect mobility and the ION/IOFF ratio. Aiming at the evaluation of the TFT characteristics for digital circuit applications, inverter circuits using a load TFT in the pull-up network and an active TFT in the pull-down network were integrated. The inverters show reasonable switching characteristics and V/V gains. Conjointly, the influence of the geometry ratio and the supply voltage on the devices have been analyzed. Moreover, as all integration steps are suitable to polymeric templates, the fabrication process is fully compatible to flexible substrates. PMID:28335282

Inverter Circuits Using ZnO Nanoparticle Based Thin-Film Transistors for Flexible Electronic Applications.

PubMed

Vidor, Fábio F; Meyers, Thorsten; Hilleringmann, Ulrich

2016-08-23

Innovative systems exploring the flexibility and the transparency of modern semiconducting materials are being widely researched by the scientific community and by several companies. For a low-cost production and large surface area applications, thin-film transistors (TFTs) are the key elements driving the system currents. In order to maintain a cost efficient integration process, solution based materials are used as they show an outstanding tradeoff between cost and system complexity. In this paper, we discuss the integration process of ZnO nanoparticle TFTs using a high- k resin as gate dielectric. The performance in dependence on the transistor structure has been investigated, and inverted staggered setups depict an improved performance over the coplanar device increasing both the field-effect mobility and the I ON / I OFF ratio. Aiming at the evaluation of the TFT characteristics for digital circuit applications, inverter circuits using a load TFT in the pull-up network and an active TFT in the pull-down network were integrated. The inverters show reasonable switching characteristics and V / V gains. Conjointly, the influence of the geometry ratio and the supply voltage on the devices have been analyzed. Moreover, as all integration steps are suitable to polymeric templates, the fabrication process is fully compatible to flexible substrates.

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

The Global Communication Infrastructure of the International Monitoring System

NASA Astrophysics Data System (ADS)

Lastowka, L.; Gray, A.; Anichenko, A.

2007-05-01

The Global Communications Infrastructure (GCI) employs 6 satellites in various frequency bands distributed around the globe. Communications with the PTS (Provisional Technical Secretariat) in Vienna, Austria are achieved through VSAT technologies, international leased data circuits and Virtual Private Network (VPN) connections over the Internet. To date, 210 independent VSAT circuits have been connected to Vienna as well as special circuits connecting to the Antarctic and to independent sub-networks. Data volumes from all technologies currently reach 8 Gigabytes per day. The first level of support and a 24/7 help desk remains with the GCI contractor, but performance is monitored actively by the PTS/GCI operations team. GCI operations are being progressively introduced into the PTS operations centre. An Operations centre fully integrated with the GCI segment of the IMS network will ensure a more focused response to incidents and will maximize the availability of the IMS network. Existing trouble tickets systems are being merged to ensure the commission manages GCI incidents in the context of the IMS as a whole. A focus on a single source of data for GCI network performance has enabled reporting systems to be developed which allow for improved and automated reports. The contracted availability for each individual virtual circuit is 99.5% and this performance is regularly reviewed on a monthly basis

A design concept for an MMIC (Monolithic Microwave Integrated Circuit) microstrip phased array

NASA Technical Reports Server (NTRS)

Lee, Richard Q.; Smetana, Jerry; Acosta, Roberto

1987-01-01

A conceptual design for a microstrip phased array with monolithic microwave integrated circuit (MMIC) amplitude and phase controls is described. The MMIC devices used are 20 GHz variable power amplifiers and variable phase shifters recently developed by NASA contractors for applications in future Ka proposed design, which concept is for a general NxN element array of rectangular lattice geometry. Subarray excitation is incorporated in the MMIC phased array design to reduce the complexity of the beam forming network and the number of MMIC components required.

PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

PubMed Central

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2008-01-01

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations. PMID:19543450

Design of high-speed burst mode clock and data recovery IC for passive optical network

NASA Astrophysics Data System (ADS)

Yan, Minhui; Hong, Xiaobin; Huang, Wei-Ping; Hong, Jin

2005-09-01

Design of a high bit rate burst mode clock and data recovery (BMCDR) circuit for gigabit passive optical networks (GPON) is described. A top-down design flow is established and some of the key issues related to the behavioural level modeling are addressed in consideration for the complexity of the BMCDR integrated circuit (IC). Precise implementation of Simulink behavioural model accounting for the saturation of frequency control voltage is therefore developed for the BMCDR, and the parameters of the circuit blocks can be readily adjusted and optimized based on the behavioural model. The newly designed BMCDR utilizes the 0.18um standard CMOS technology and is shown to be capable of operating at bit rate of 2.5Gbps, as well as the recovery time of one bit period in our simulation. The developed behaviour model is verified by comparing with the detailed circuit simulation.

Nonreciprocal signal routing in an active quantum network

NASA Astrophysics Data System (ADS)

Metelmann, A.; Türeci, H. E.

2018-04-01

As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. Here, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

PubMed

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

PubMed Central

Wang, Xiao-Jing

2016-01-01

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. PMID:26928718

Neural CMOS-integrated circuit and its application to data classification.

PubMed

Göknar, Izzet Cem; Yildiz, Merih; Minaei, Shahram; Deniz, Engin

2012-05-01

Implementation and new applications of a tunable complementary metal-oxide-semiconductor-integrated circuit (CMOS-IC) of a recently proposed classifier core-cell (CC) are presented and tested with two different datasets. With two algorithms-one based on Fisher's linear discriminant analysis and the other based on perceptron learning, used to obtain CCs' tunable parameters-the Haberman and Iris datasets are classified. The parameters so obtained are used for hard-classification of datasets with a neural network structured circuit. Classification performance and coefficient calculation times for both algorithms are given. The CC has 6-ns response time and 1.8-mW power consumption. The fabrication parameters used for the IC are taken from CMOS AMS 0.35-μm technology.

Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.

PubMed

Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire

2017-08-01

During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.

Polarization-analyzing circuit on InP for integrated Stokes vector receiver.

PubMed

Ghosh, Samir; Kawabata, Yuto; Tanemura, Takuo; Nakano, Yoshiaki

2017-05-29

Stokes vector modulation and direct detection (SVM/DD) has immense potentiality to reduce the cost burden for the next-generation short-reach optical communication networks. In this paper, we propose and demonstrate an InGaAsP/InP waveguide-based polarization-analyzing circuit for an integrated Stokes vector (SV) receiver. By transforming the input state-of-polarization (SOP) and projecting its SV onto three different vectors on the Poincare sphere, we show that the actual SOP can be retrieved by simple calculation. We also reveal that this projection matrix has a flexibility and its deviation due to device imperfectness can be calibrated to a certain degree, so that the proposed device would be fundamentally robust against fabrication errors. A proof-of-concept photonic integrated circuit (PIC) is fabricated on InP by using half-ridge waveguides to successfully demonstrate detection of different SOPs scattered on the Poincare sphere.

Satellite networks in the ISDN era

NASA Astrophysics Data System (ADS)

Amadesi, P.; Haines, P.; Patacchini, A.

1986-12-01

The development of an integrated service digital network (ISDN) capable of supporting a wide range of services using a small set of standard multipurpose user-network interfaces is examined. The ISDN environment is expected to consist of functional elements such as, circuit switching, packet switching, and common channel signaling. The use of satellites or fiber optics in the ISDN is evaluated. The relation between satellites and the ISDN in the short-, medium-, and long-terms is analyzed. The recommendations of the consultative committee, CCIR, concerning the definition of the hypothetical reference digital path and the required quality and availability for ISDN applications, and the proposed plans of Eutelsat and Intelsat for satellite systems compatible with an ISDN are discussed. The application of business satellite networks and packet satellite networks to an ISDN is studied. The long-term objectives for an ISDN is a wideband system that accommodates digital transmission on circuit and packet switched bases.

Deep learning with coherent nanophotonic circuits

NASA Astrophysics Data System (ADS)

Shen, Yichen; Harris, Nicholas C.; Skirlo, Scott; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Sun, Xin; Zhao, Shijie; Larochelle, Hugo; Englund, Dirk; Soljačić, Marin

2017-07-01

Artificial neural networks are computational network models inspired by signal processing in the brain. These models have dramatically improved performance for many machine-learning tasks, including speech and image recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made towards developing electronic architectures tuned to implement artificial neural networks that exhibit improved computational speed and accuracy. Here, we propose a new architecture for a fully optical neural network that, in principle, could offer an enhancement in computational speed and power efficiency over state-of-the-art electronics for conventional inference tasks. We experimentally demonstrate the essential part of the concept using a programmable nanophotonic processor featuring a cascaded array of 56 programmable Mach-Zehnder interferometers in a silicon photonic integrated circuit and show its utility for vowel recognition.

MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

PubMed Central

Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara

2012-01-01

MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880

A simple structure wavelet transform circuit employing function link neural networks and SI filters

NASA Astrophysics Data System (ADS)

Mu, Li; Yigang, He

2016-12-01

Signal processing by means of analog circuits offers advantages from a power consumption viewpoint. Implementing wavelet transform (WT) using analog circuits is of great interest when low-power consumption becomes an important issue. In this article, a novel simple structure WT circuit in analog domain is presented by employing functional link neural network (FLNN) and switched-current (SI) filters. First, the wavelet base is approximated using FLNN algorithms for giving a filter transfer function that is suitable for simple structure WT circuit implementation. Next, the WT circuit is constructed with the wavelet filter bank, whose impulse response is the approximated wavelet and its dilations. The filter design that follows is based on a follow-the-leader feedback (FLF) structure with multiple output bilinear SI integrators and current mirrors as the main building blocks. SI filter is well suited for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the clock frequency of the circuit with the same system architecture. Finally, to illustrate the design procedure, a seventh-order FLNN-approximated Gaussian wavelet is implemented as an example. Simulations have successfully verified that the designed simple structure WT circuit has low sensitivity, low-power consumption and litter effect to the imperfections.

Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

PubMed Central

Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

2015-01-01

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

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.

Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics

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

Jung, Jinwoo; Lee, Jewon; Song, Hanjung

2011-03-15

This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performedmore » simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.« less

Extremely Bendable, High-Performance Integrated Circuits Using Semiconducting Carbon Nanotube Networks for Digital, Analog, and Radio-Frequency Applications

DTIC Science & Technology

2012-02-07

circuits on mechanically flexible substrates for digital, analog and radio frequency applications. The asobtained thin-film transistors ( TFTs ) exhibit... flexible substrates for digital, analog and radio frequency applications. The as- obtained thin-film transistors ( TFTs ) exhibit highly uniform device...LCD) and organic light- emitting diode ( OLED ) displays lack the transparency and flexibility and are thus unsuitable for flexible electronic

Implementation of a Synchronized Oscillator Circuit for Fast Sensing and Labeling of Image Objects

PubMed Central

Kowalski, Jacek; Strzelecki, Michal; Kim, Hyongsuk

2011-01-01

We present an application-specific integrated circuit (ASIC) CMOS chip that implements a synchronized oscillator cellular neural network with a matrix size of 32 × 32 for object sensing and labeling in binary images. Networks of synchronized oscillators are a recently developed tool for image segmentation and analysis. Its parallel network operation is based on a “temporary correlation” theory that attempts to describe scene recognition as if performed by the human brain. The synchronized oscillations of neuron groups attract a person’s attention if he or she is focused on a coherent stimulus (image object). For more than one perceived stimulus, these synchronized patterns switch in time between different neuron groups, thus forming temporal maps that code several features of the analyzed scene. In this paper, a new oscillator circuit based on a mathematical model is proposed, and the network architecture and chip functional blocks are presented and discussed. The proposed chip is implemented in AMIS 0.35 μm C035M-D 5M/1P technology. An application of the proposed network chip for the segmentation of insulin-producing pancreatic islets in magnetic resonance liver images is presented. PMID:22163803

Imbalance aware lithography hotspot detection: a deep learning approach

NASA Astrophysics Data System (ADS)

Yang, Haoyu; Luo, Luyang; Su, Jing; Lin, Chenxi; Yu, Bei

2017-07-01

With the advancement of very large scale integrated circuits (VLSI) technology nodes, lithographic hotspots become a serious problem that affects manufacture yield. Lithography hotspot detection at the post-OPC stage is imperative to check potential circuit failures when transferring designed patterns onto silicon wafers. Although conventional lithography hotspot detection methods, such as machine learning, have gained satisfactory performance, with the extreme scaling of transistor feature size and layout patterns growing in complexity, conventional methodologies may suffer from performance degradation. For example, manual or ad hoc feature extraction in a machine learning framework may lose important information when predicting potential errors in ultra-large-scale integrated circuit masks. We present a deep convolutional neural network (CNN) that targets representative feature learning in lithography hotspot detection. We carefully analyze the impact and effectiveness of different CNN hyperparameters, through which a hotspot-detection-oriented neural network model is established. Because hotspot patterns are always in the minority in VLSI mask design, the training dataset is highly imbalanced. In this situation, a neural network is no longer reliable, because a trained model with high classification accuracy may still suffer from a high number of false negative results (missing hotspots), which is fatal in hotspot detection problems. To address the imbalance problem, we further apply hotspot upsampling and random-mirror flipping before training the network. Experimental results show that our proposed neural network model achieves comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

A Short Open Calibration (SOC) Technique to Calculate the Propagation Characteristics of Substrate Integrated Waveguide

DTIC Science & Technology

2015-07-01

integrated with the commercial electromagnetic software for accurate extraction of propagation constant of substrate integrated waveguide ( SIW ) with...respectively. After three distinctive equivalent circuit networks are described for SOC de-embedding procedure. The propagation constants of SIW with...final, the phase and attenuation constants of SIW are derived to demonstrate the propagation and leakage characteristics of SIW . Index Terms

Synthetic analog and digital circuits for cellular computation and memory.

PubMed

Purcell, Oliver; Lu, Timothy K

2014-10-01

Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene networks that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Customizing cell signaling using engineered genetic logic circuits.

PubMed

Wang, Baojun; Buck, Martin

2012-08-01

Cells live in an ever-changing environment and continuously sense, process and react to environmental signals using their inherent signaling and gene regulatory networks. Recently, there have been great advances on rewiring the native cell signaling and gene networks to program cells to sense multiple noncognate signals and integrate them in a logical manner before initiating a desired response. Here, we summarize the current state-of-the-art of engineering synthetic genetic logic circuits to customize cellular signaling behaviors, and discuss their promising applications in biocomputing, environmental, biotechnological and biomedical areas as well as the remaining challenges in this growing field. Copyright © 2012 Elsevier Ltd. All rights reserved.

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

Mathematical model for calculation of the heat-hydraulic modes of heating points of heat-supplying systems

NASA Astrophysics Data System (ADS)

Shalaginova, Z. I.

2016-03-01

The mathematical model and calculation method of the thermal-hydraulic modes of heat points, based on the theory of hydraulic circuits, being developed at the Melentiev Energy Systems Institute are presented. The redundant circuit of the heat point was developed, in which all possible connecting circuits (CC) of the heat engineering equipment and the places of possible installation of control valve were inserted. It allows simulating the operating modes both at central heat points (CHP) and individual heat points (IHP). The configuration of the desired circuit is carried out automatically by removing the unnecessary links. The following circuits connecting the heating systems (HS) are considered: the dependent circuit (direct and through mixing elevator) and independent one (through the heater). The following connecting circuits of the load of hot water supply (HWS) were considered: open CC (direct water pumping from pipelines of heat networks) and a closed CC with connecting the HWS heaters on single-level (serial and parallel) and two-level (sequential and combined) circuits. The following connecting circuits of the ventilation systems (VS) were also considered: dependent circuit and independent one through a common heat exchanger with HS load. In the heat points, water temperature regulators for the hot water supply and ventilation and flow regulators for the heating system, as well as to the inlet as a whole, are possible. According to the accepted decomposition, the model of the heat point is an integral part of the overall heat-hydraulic model of the heat-supplying system having intermediate control stages (CHP and IHP), which allows to consider the operating modes of the heat networks of different levels connected with each other through CHP as well as connected through IHP of consumers with various connecting circuits of local systems of heat consumption: heating, ventilation and hot water supply. The model is implemented in the Angara data-processing complex. An example of the multilevel calculation of the heat-hydraulic modes of main heat networks and those connected to them through central heat point distribution networks in Petropavlovsk-Kamchatskii is examined.

Engineering integrated digital circuits with allosteric ribozymes for scaling up molecular computation and diagnostics.

PubMed

Penchovsky, Robert

2012-10-19

Here we describe molecular implementations of integrated digital circuits, including a three-input AND logic gate, a two-input multiplexer, and 1-to-2 decoder using allosteric ribozymes. Furthermore, we demonstrate a multiplexer-decoder circuit. The ribozymes are designed to seek-and-destroy specific RNAs with a certain length by a fully computerized procedure. The algorithm can accurately predict one base substitution that alters the ribozyme's logic function. The ability to sense the length of RNA molecules enables single ribozymes to be used as platforms for multiple interactions. These ribozymes can work as integrated circuits with the functionality of up to five logic gates. The ribozyme design is universal since the allosteric and substrate domains can be altered to sense different RNAs. In addition, the ribozymes can specifically cleave RNA molecules with triplet-repeat expansions observed in genetic disorders such as oculopharyngeal muscular dystrophy. Therefore, the designer ribozymes can be employed for scaling up computing and diagnostic networks in the fields of molecular computing and diagnostics and RNA synthetic biology.

Multi-petascale highly efficient parallel supercomputer

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

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

Biolithography: Slime mould patterning of polyaniline

NASA Astrophysics Data System (ADS)

Berzina, Tatiana; Dimonte, Alice; Adamatzky, Andrew; Erokhin, Victor; Iannotta, Salvatore

2018-03-01

Slime mould Physarum polycephalum develops intricate patterns of protoplasmic networks when foraging on a non-nutrient substrates. The networks are optimised for spanning larger spaces with minimum body mass and for quick transfer of nutrients and metabolites inside the slime mould's body. We hybridise the slime mould's networks with conductive polymer polyaniline and thus produce micro-patterns of conductive networks. This unconventional lithographic method opens new perspectives in development of living technology devices, biocompatible non-silicon hardware for applications in integrated circuits, bioelectronics, and biosensing.

On-board processing satellite network architectures for broadband ISDN

NASA Technical Reports Server (NTRS)

Inukai, Thomas; Faris, Faris; Shyy, Dong-Jye

1992-01-01

Onboard baseband processing architectures for future satellite broadband integrated services digital networks (B-ISDN's) are addressed. To assess the feasibility of implementing satellite B-ISDN services, critical design issues, such as B-ISDN traffic characteristics, transmission link design, and a trade-off between onboard circuit and fast packet switching, are analyzed. Examples of the two types of switching mechanisms and potential onboard network control functions are presented. A sample network architecture is also included to illustrate a potential onboard processing system.

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

Compact earth stations, hubs for energy industry expanding

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

Shimabukuro, T.

1992-02-01

That paper reports that advances in gallium arsenide (GaAs) technology, monolithic microwave integrated circuits (MMIC) and large scale integrated (VLSF) circuits, have contributed to the mass production of very reliable small aperture terminals (VSATs). Less publicized, but equally important to multinational energy organizations, are recent developments in compact earth station design and solid-state hubs for VSAT networks made possible by the new technology. Many applications are suited for the energy industry that involve compact earth station terminals and hubs. The first group of applications describes the use of GTE's ACES earth station for the Zaire Gulf Oil Co. in Zairemore » and for AMOCO in Trinidad. The second group of applications describes the compact hub for VSAT networks, which could potentially have a number of data communication uses in the energy industry, such as, IBM/SNA, X.25, or supervisory control an data acquisition (SCADA) applications.« less

Deep Brain Stimulation

PubMed Central

Lyketsos, Constantine G.; Pendergrass, Jo Cara; Lozano, Andres M.

2012-01-01

Recent studies have identified an association between memory deficits and defects of the integrated neuronal cortical areas known collectively as the default mode network. It is conceivable that the amyloid deposition or other molecular abnormalities seen in patients with Alzheimer’s disease may interfere with this network and disrupt neuronal circuits beyond the localized brain areas. Therefore, Alzheimer’s disease may be both a degenerative disease and a broader system-level disorder affecting integrated neuronal pathways involved in memory. In this paper, we describe the rationale and provide some evidence to support the study of deep brain stimulation of the hippocampal fornix as a novel treatment to improve neuronal circuitry within these integrated networks and thereby sustain memory function in early Alzheimer’s disease. PMID:23346514

IIIV/Si Nanoscale Lasers and Their Integration with Silicon Photonics

NASA Astrophysics Data System (ADS)

Bondarenko, Olesya

The rapidly evolving global information infrastructure requires ever faster data transfer within computer networks and stations. Integrated chip scale photonics can pave the way to accelerated signal manipulation and boost bandwidth capacity of optical interconnects in a compact and ergonomic arrangement. A key building block for integrated photonic circuits is an on-chip laser. In this dissertation we explore ways to reduce the physical footprint of semiconductor lasers and make them suitable for high density integration on silicon, a standard material platform for today's integrated circuits. We demonstrated the first room temperature metalo-dielectric nanolaser, sub-wavelength in all three dimensions. Next, we demonstrated a nanolaser on silicon, showing the feasibility of its integration with this platform. We also designed and realized an ultracompact feedback laser with edge-emitting structure, amenable for in-plane coupling with a standard silicon waveguide. Finally, we discuss the challenges and propose solutions for improvement of the device performance and practicality.

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

PubMed

Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

System Impact Study of the Eastern Grid of Sumba Island, Indonesia: Steady-State and Dynamic System Modeling for the Integration of One and Two 850-kW Wind Turbine Generators

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

Oswal, R.; Jain, P.; Muljadi, Eduard

2016-01-01

The goal of this project was to study the impact of integrating one and two 850-kW wind turbine generators into the eastern power system network of Sumba Island, Indonesia. A model was created for the 20-kV distribution network as it existed in the first quarter of 2015 with a peak load of 5.682 MW. Detailed data were collected for each element of the network. Load flow, short-circuit, and transient analyses were performed using DIgSILENT PowerFactory 15.2.1.

Pass-transistor very large scale integration

NASA Technical Reports Server (NTRS)

Maki, Gary K. (Inventor); Bhatia, Prakash R. (Inventor)

2004-01-01

Logic elements are provided that permit reductions in layout size and avoidance of hazards. Such logic elements may be included in libraries of logic cells. A logical function to be implemented by the logic element is decomposed about logical variables to identify factors corresponding to combinations of the logical variables and their complements. A pass transistor network is provided for implementing the pass network function in accordance with this decomposition. The pass transistor network includes ordered arrangements of pass transistors that correspond to the combinations of variables and complements resulting from the logical decomposition. The logic elements may act as selection circuits and be integrated with memory and buffer elements.

VLSI circuits implementing computational models of neocortical circuits.

PubMed

Wijekoon, Jayawan H B; Dudek, Piotr

2012-09-15

This paper overviews the design and implementation of three neuromorphic integrated circuits developed for the COLAMN ("Novel Computing Architecture for Cognitive Systems based on the Laminar Microcircuitry of the Neocortex") project. The circuits are implemented in a standard 0.35 μm CMOS technology and include spiking and bursting neuron models, and synapses with short-term (facilitating/depressing) and long-term (STDP and dopamine-modulated STDP) dynamics. They enable execution of complex nonlinear models in accelerated-time, as compared with biology, and with low power consumption. The neural dynamics are implemented using analogue circuit techniques, with digital asynchronous event-based input and output. The circuits provide configurable hardware blocks that can be used to simulate a variety of neural networks. The paper presents experimental results obtained from the fabricated devices, and discusses the advantages and disadvantages of the analogue circuit approach to computational neural modelling. Copyright © 2012 Elsevier B.V. All rights reserved.

Cascade Back-Propagation Learning in Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2003-01-01

The cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.

Integrated-optics heralded controlled-NOT gate for polarization-encoded qubits

NASA Astrophysics Data System (ADS)

Zeuner, Jonas; Sharma, Aditya N.; Tillmann, Max; Heilmann, René; Gräfe, Markus; Moqanaki, Amir; Szameit, Alexander; Walther, Philip

2018-03-01

Recent progress in integrated-optics technology has made photonics a promising platform for quantum networks and quantum computation protocols. Integrated optical circuits are characterized by small device footprints and unrivalled intrinsic interferometric stability. Here, we take advantage of femtosecond-laser-written waveguides' ability to process polarization-encoded qubits and present an implementation of a heralded controlled-NOT gate on chip. We evaluate the gate performance in the computational basis and a superposition basis, showing that the gate can create polarization entanglement between two photons. Transmission through the integrated device is optimized using thermally expanded core fibers and adiabatically reduced mode-field diameters at the waveguide facets. This demonstration underlines the feasibility of integrated quantum gates for all-optical quantum networks and quantum repeaters.

Memristor-CMOS hybrid integrated circuits for reconfigurable logic.

PubMed

Xia, Qiangfei; Robinett, Warren; Cumbie, Michael W; Banerjee, Neel; Cardinali, Thomas J; Yang, J Joshua; Wu, Wei; Li, Xuema; Tong, William M; Strukov, Dmitri B; Snider, Gregory S; Medeiros-Ribeiro, Gilberto; Williams, R Stanley

2009-10-01

Hybrid reconfigurable logic circuits were fabricated by integrating memristor-based crossbars onto a foundry-built CMOS (complementary metal-oxide-semiconductor) platform using nanoimprint lithography, as well as materials and processes that were compatible with the CMOS. Titanium dioxide thin-film memristors served as the configuration bits and switches in a data routing network and were connected to gate-level CMOS components that acted as logic elements, in a manner similar to a field programmable gate array. We analyzed the chips using a purpose-built testing system, and demonstrated the ability to configure individual devices, use them to wire up various logic gates and a flip-flop, and then reconfigure devices.

Optically controlled phased array antenna concepts using GaAs monolithic microwave integrated circuits

NASA Technical Reports Server (NTRS)

Kunath, R. R.; Bhasin, K. B.

1986-01-01

The desire for rapid beam reconfigurability and steering has led to the exploration of new techniques. Optical techniques have been suggested as potential candidates for implementing these needs. Candidates generally fall into one of two areas: those using fiber optic Beam Forming Networks (BFNs) and those using optically processed BFNs. Both techniques utilize GaAs Monolithic Microwave Integrated Circuits (MMICs) in the BFN, but the role of the MMIC for providing phase and amplitude variations is largely eliminated by some new optical processing techniques. This paper discusses these two types of optical BFN designs and provides conceptual designs of both systems.

InP-based three-dimensional photonic integrated circuits

NASA Astrophysics Data System (ADS)

Tsou, Diana; Zaytsev, Sergey; Pauchard, Alexandre; Hummel, Steve; Lo, Yu-Hwa

2001-10-01

Fast-growing internet traffic volumes require high data communication bandwidth over longer distances than short wavelength (850 nm) multi-mode fiber systems can provide. Access network bottlenecks put pressure on short-range (SR) telecommunication systems. To effectively address these datacom and telecom market needs, low cost, high-speed laser modules at 1310 and 1550 nm wavelengths are required. The great success of GaAs 850 nm VCSELs for Gb/s Ethernet has motivated efforts to extend VCSEL technology to longer wavelengths in the 1310 and 1550 nm regimes. However, the technological challenges associated with available intrinsic materials for long wavelength VCSELs are tremendous. Even with recent advances in this area, it is believed that significant additional development is necessary before long wavelength VCSELs that meet commercial specifications will be widely available. In addition, the more stringent OC192 and OC768 specifications for single-mode fiber (SMF) datacom may require more than just a long wavelength laser diode, VCSEL or not, to address numerous cost and performance issues. We believe that photonic integrated circuits, which compactly integrate surface-emitting lasers with additional active and passive optical components with extended functionality, will provide the best solutions to today's problems. Photonic integrated circuits (PICs) have been investigated for more than a decade. However, they have produced limited commercial impact to date primarily because the highly complicated fabrication processes produce significant yield and device performance issues. In this presentation, we will discuss a new technology platform for fabricating InP-based photonic integrated circuits compatible with surface-emitting laser technology. Employing InP transparency at 1310 and 1550 nm wavelengths, we have created 3-D photonic integrated circuits (PICs) by utilizing light beams in both surface normal and in-plane directions within the InP-based structure. This additional beam routing flexibility allows significant size reduction and process simplification without sacrificing device performance. This innovative 3-D PIC technology platform can be easily extended to create surface-emitting lasers integrated with power monitoring detectors, micro-lenses, external modulators, amplifiers, and other passive and active components. Such added functionality can produce cost--effective solutions for the highest-end laser transmitters required for datacom and short range telecom networks, as well as fiber channels and other cost and performance sensitive applications. We present results for 1310 nm photonic IC surface-emitting laser transmitters operating at 2.5 Gbps without active thermal electric cooling.

Network speech systems technology program

NASA Astrophysics Data System (ADS)

Weinstein, C. J.

1981-09-01

This report documents work performed during FY 1981 on the DCA-sponsored Network Speech Systems Technology Program. The two areas of work reported are: (1) communication system studies in support of the evolving Defense Switched Network (DSN) and (2) design and implementation of satellite/terrestrial interfaces for the Experimental Integrated Switched Network (EISN). The system studies focus on the development and evaluation of economical and endurable network routing procedures. Satellite/terrestrial interface development includes circuit-switched and packet-switched connections to the experimental wideband satellite network. Efforts in planning and coordination of EISN experiments are reported in detail in a separate EISN Experiment Plan.

Optical interconnections and networks; Proceedings of the Meeting, The Hague, Netherlands, Mar. 14, 15, 1990

NASA Technical Reports Server (NTRS)

Bartelt, Hartmut (Editor)

1990-01-01

The conference presents papers on interconnections, clock distribution, neural networks, and components and materials. Particular attention is given to a comparison of optical and electrical data interconnections at the board and backplane levels, a wafer-level optical interconnection network layout, an analysis and simulation of photonic switch networks, and the integration of picosecond GaAs photoconductive devices with silicon circuits for optical clocking and interconnects. Consideration is also given to the optical implementation of neural networks, invariance in an optoelectronic implementation of neural networks, and the recording of reversible patterns in polymer lightguides.

A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior

PubMed Central

Voloh, Benjamin; Womelsdorf, Thilo

2016-01-01

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior. PMID:27013986

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE PAGES

Shen, Yiwen; Hattink, Maarten; Samadi, Payman; ...

2018-04-13

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

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

Shen, Yiwen; Hattink, Maarten; Samadi, Payman

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2013-01-01

Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967

A visually guided collision warning system with a neuromorphic architecture.

PubMed

Okuno, Hirotsugu; Yagi, Tetsuya

2008-12-01

We have designed a visually guided collision warning system with a neuromorphic architecture, employing an algorithm inspired by the visual nervous system of locusts. The system was implemented with mixed analog-digital integrated circuits consisting of an analog resistive network and field-programmable gate array (FPGA) circuits. The resistive network processes the interaction between the laterally spreading excitatory and inhibitory signals instantaneously, which is essential for real-time computation of collision avoidance with a low power consumption and a compact hardware. The system responded selectively to approaching objects of simulated movie images at close range. The system was, however, confronted with serious noise problems due to the vibratory ego-motion, when it was installed in a mobile miniature car. To overcome this problem, we developed the algorithm, which is also installable in FPGA circuits, in order for the system to respond robustly during the ego-motion.

Multipurpose silicon photonics signal processor core.

PubMed

Pérez, Daniel; Gasulla, Ivana; Crudgington, Lee; Thomson, David J; Khokhar, Ali Z; Li, Ke; Cao, Wei; Mashanovich, Goran Z; Capmany, José

2017-09-21

Integrated photonics changes the scaling laws of information and communication systems offering architectural choices that combine photonics with electronics to optimize performance, power, footprint, and cost. Application-specific photonic integrated circuits, where particular circuits/chips are designed to optimally perform particular functionalities, require a considerable number of design and fabrication iterations leading to long development times. A different approach inspired by electronic Field Programmable Gate Arrays is the programmable photonic processor, where a common hardware implemented by a two-dimensional photonic waveguide mesh realizes different functionalities through programming. Here, we report the demonstration of such reconfigurable waveguide mesh in silicon. We demonstrate over 20 different functionalities with a simple seven hexagonal cell structure, which can be applied to different fields including communications, chemical and biomedical sensing, signal processing, multiprocessor networks, and quantum information systems. Our work is an important step toward this paradigm.Integrated optical circuits today are typically designed for a few special functionalities and require complex design and development procedures. Here, the authors demonstrate a reconfigurable but simple silicon waveguide mesh with different functionalities.

Single-cell axotomy of cultured hippocampal neurons integrated in neuronal circuits.

PubMed

Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank

2014-05-01

An understanding of the molecular mechanisms of axon regeneration after injury is key for the development of potential therapies. Single-cell axotomy of dissociated neurons enables the study of the intrinsic regenerative capacities of injured axons. This protocol describes how to perform single-cell axotomy on dissociated hippocampal neurons containing synapses. Furthermore, to axotomize hippocampal neurons integrated in neuronal circuits, we describe how to set up coculture with a few fluorescently labeled neurons. This approach allows axotomy of single cells in a complex neuronal network and the observation of morphological and molecular changes during axon regeneration. Thus, single-cell axotomy of mature neurons is a valuable tool for gaining insights into cell intrinsic axon regeneration and the plasticity of neuronal polarity of mature neurons. Dissociation of the hippocampus and plating of hippocampal neurons takes ∼2 h. Neurons are then left to grow for 2 weeks, during which time they integrate into neuronal circuits. Subsequent axotomy takes 10 min per neuron and further imaging takes 10 min per neuron.

Integrated plasticity at inhibitory and excitatory synapses in the cerebellar circuit.

PubMed

Mapelli, Lisa; Pagani, Martina; Garrido, Jesus A; D'Angelo, Egidio

2015-01-01

The way long-term potentiation (LTP) and depression (LTD) are integrated within the different synapses of brain neuronal circuits is poorly understood. In order to progress beyond the identification of specific molecular mechanisms, a system in which multiple forms of plasticity can be correlated with large-scale neural processing is required. In this paper we take as an example the cerebellar network, in which extensive investigations have revealed LTP and LTD at several excitatory and inhibitory synapses. Cerebellar LTP and LTD occur in all three main cerebellar subcircuits (granular layer, molecular layer, deep cerebellar nuclei) and correspondingly regulate the function of their three main neurons: granule cells (GrCs), Purkinje cells (PCs) and deep cerebellar nuclear (DCN) cells. All these neurons, in addition to be excited, are reached by feed-forward and feed-back inhibitory connections, in which LTP and LTD may either operate synergistically or homeostatically in order to control information flow through the circuit. Although the investigation of individual synaptic plasticities in vitro is essential to prove their existence and mechanisms, it is insufficient to generate a coherent view of their impact on network functioning in vivo. Recent computational models and cell-specific genetic mutations in mice are shedding light on how plasticity at multiple excitatory and inhibitory synapses might regulate neuronal activities in the cerebellar circuit and contribute to learning and memory and behavioral control.

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility.

PubMed

Bagot, Rosemary C; Cates, Hannah M; Purushothaman, Immanuel; Lorsch, Zachary S; Walker, Deena M; Wang, Junshi; Huang, Xiaojie; Schlüter, Oliver M; Maze, Ian; Peña, Catherine J; Heller, Elizabeth A; Issler, Orna; Wang, Minghui; Song, Won-Min; Stein, Jason L; Liu, Xiaochuan; Doyle, Marie A; Scobie, Kimberly N; Sun, Hao Sheng; Neve, Rachael L; Geschwind, Daniel; Dong, Yan; Shen, Li; Zhang, Bin; Nestler, Eric J

2016-06-01

Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrated biocircuits: engineering functional multicellular circuits and devices.

PubMed

Prox, Jordan; Smith, Tory; Holl, Chad; Chehade, Nick; Guo, Liang

2018-04-01

Implantable neurotechnologies have revolutionized neuromodulatory medicine for treating the dysfunction of diseased neural circuitry. However, challenges with biocompatibility and lack of full control over neural network communication and function limits the potential to create more stable and robust neuromodulation devices. Thus, we propose a platform technology of implantable and programmable cellular systems, namely Integrated Biocircuits, which use only cells as the functional components of the device. We envision the foundational principles for this concept begins with novel in vitro platforms used for the study and reconstruction of cellular circuitry. Additionally, recent advancements in organoid and 3D culture systems account for microenvironment factors of cytoarchitecture to construct multicellular circuits as they are normally formed in the brain. We explore the current state of the art of these platforms to provide knowledge of their advancements in circuit fabrication and identify the current biological principles that could be applied in designing integrated biocircuit devices. We have highlighted the exemplary methodologies and techniques of in vitro circuit fabrication and propose the integration of selected controllable parameters, which would be required in creating suitable biodevices. We provide our perspective and propose new insights into the future of neuromodulaion devices within the scope of living cellular systems that can be applied in designing more reliable and biocompatible stimulation-based neuroprosthetics.

Integrated biocircuits: engineering functional multicellular circuits and devices

NASA Astrophysics Data System (ADS)

Prox, Jordan; Smith, Tory; Holl, Chad; Chehade, Nick; Guo, Liang

2018-04-01

Objective. Implantable neurotechnologies have revolutionized neuromodulatory medicine for treating the dysfunction of diseased neural circuitry. However, challenges with biocompatibility and lack of full control over neural network communication and function limits the potential to create more stable and robust neuromodulation devices. Thus, we propose a platform technology of implantable and programmable cellular systems, namely Integrated Biocircuits, which use only cells as the functional components of the device. Approach. We envision the foundational principles for this concept begins with novel in vitro platforms used for the study and reconstruction of cellular circuitry. Additionally, recent advancements in organoid and 3D culture systems account for microenvironment factors of cytoarchitecture to construct multicellular circuits as they are normally formed in the brain. We explore the current state of the art of these platforms to provide knowledge of their advancements in circuit fabrication and identify the current biological principles that could be applied in designing integrated biocircuit devices. Main results. We have highlighted the exemplary methodologies and techniques of in vitro circuit fabrication and propose the integration of selected controllable parameters, which would be required in creating suitable biodevices. Significance. We provide our perspective and propose new insights into the future of neuromodulaion devices within the scope of living cellular systems that can be applied in designing more reliable and biocompatible stimulation-based neuroprosthetics.

Nonvolatile Array Of Synapses For Neural Network

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1993-01-01

Elements of array programmed with help of ultraviolet light. A 32 x 32 very-large-scale integrated-circuit array of electronic synapses serves as building-block chip for analog neural-network computer. Synaptic weights stored in nonvolatile manner. Makes information content of array invulnerable to loss of power, and, by eliminating need for circuitry to refresh volatile synaptic memory, makes architecture simpler and more compact.

Frank Beach Award Winner: Steroids as Neuromodulators of Brain Circuits and Behavior

PubMed Central

Remage-Healey, Luke

2014-01-01

Neurons communicate primarily via action potentials that transmit information on the timescale of milliseconds. Neurons also integrate information via alterations in gene transcription and protein translation that are sustained for hours to days after initiation. Positioned between these two signaling timescales are the minute-by-minute actions of neuromodulators. Over the course of minutes, the classical neuromodulators (such as serotonin, dopamine, octopamine, and norepinephrine) can alter and/or stabilize neural circuit patterning as well as behavioral states. Neuromodulators allow many flexible outputs from neural circuits and can encode information content into the firing state of neural networks. The idea that steroid molecules can operate as genuine behavioral neuromodulators - synthesized by and acting within brain circuits on a minute-by-minute timescale - has gained traction in recent years. Evidence for brain steroid synthesis at synaptic terminals has converged with evidence for the rapid actions of brain-derived steroids on neural circuits and behavior. The general principle emerging from this work is that the production of steroid hormones within brain circuits can alter their functional connectivity and shift sensory representations by enhancing their information coding. Steroids produced in the brain can therefore change the information content of neuronal networks to rapidly modulate sensory experience and sensorimotor functions. PMID:25110187

Leaky Integrate-and-Fire Neuron Circuit Based on Floating-Gate Integrator

PubMed Central

Kornijcuk, Vladimir; Lim, Hyungkwang; Seok, Jun Yeong; Kim, Guhyun; Kim, Seong Keun; Kim, Inho; Choi, Byung Joon; Jeong, Doo Seok

2016-01-01

The artificial spiking neural network (SNN) is promising and has been brought to the notice of the theoretical neuroscience and neuromorphic engineering research communities. In this light, we propose a new type of artificial spiking neuron based on leaky integrate-and-fire (LIF) behavior. A distinctive feature of the proposed FG-LIF neuron is the use of a floating-gate (FG) integrator rather than a capacitor-based one. The relaxation time of the charge on the FG relies mainly on the tunnel barrier profile, e.g., barrier height and thickness (rather than the area). This opens up the possibility of large-scale integration of neurons. The circuit simulation results offered biologically plausible spiking activity (<100 Hz) with a capacitor of merely 6 fF, which is hosted in an FG metal-oxide-semiconductor field-effect transistor. The FG-LIF neuron also has the advantage of low operation power (<30 pW/spike). Finally, the proposed circuit was subject to possible types of noise, e.g., thermal noise and burst noise. The simulation results indicated remarkable distributional features of interspike intervals that are fitted to Gamma distribution functions, similar to biological neurons in the neocortex. PMID:27242416

On-board processing architectures for satellite B-ISDN services

NASA Technical Reports Server (NTRS)

Inukai, Thomas; Shyy, Dong-Jye; Faris, Faris

1991-01-01

Onboard baseband processing architectures for future satellite broadband integrated services digital networks (B-ISDN's) are addressed. To assess the feasibility of implementing satellite B-ISDN services, critical design issues, such as B-ISDN traffic characteristics, transmission link design, and a trade-off between onboard circuit and fast packet switching, are analyzed. Examples of the two types of switching mechanisms and potential onboard network control functions are presented. A sample network architecture is also included to illustrate a potential onboard processing system.

Low-power wireless ECG acquisition and classification system for body sensor networks.

PubMed

Lee, Shuenn-Yuh; Hong, Jia-Hua; Hsieh, Cheng-Han; Liang, Ming-Chun; Chang Chien, Shih-Yu; Lin, Kuang-Hao

2015-01-01

A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.

[Not Available].

PubMed

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2009-01-01

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

Power Electronics Design of a Solar Powered In-car Wireless Tag for Asset Tracking and Parking Applications

NASA Astrophysics Data System (ADS)

Zhu, D.; Henaut, J.; Beeby, S. P.

2014-11-01

This paper reports the design and testing of a power conditioning circuit for a solar powered in-car wireless tag for asset tracking and parking application. Existing long range asset tracking is based on the GSM/GPRS network, which requires expensive subscriptions. The EU FP7 project CEWITT aims at developing a credit card sized autonomous wireless tag with GNSS geo-positioning capabilities to ensure the integrity and cost effectiveness for parking applications. It was found in previous research that solar cells are the most suitable energy sources for this application. This study focused on the power electronics design for the wireless tag. A suitable solar cell was chosen for its high power density. Charging circuit, hysteresis control circuit and LDO were designed and integrated to meet the system requirement. Test results showed that charging efficiency of 80 % had been achieved.

Spike timing precision of neuronal circuits.

PubMed

Kilinc, Deniz; Demir, Alper

2018-06-01

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

From behavior to neural dynamics: An integrated theory of attention

PubMed Central

Buschman, Timothy J.; Kastner, Sabine

2015-01-01

The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘attention’. Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits and neurons. We then integrate these disparate results into a unified theory of attention. PMID:26447577

Army Medical Imaging System - ARMIS

DTIC Science & Technology

1992-08-08

modems , scanners, hard disk drives, dot matrix printers, erasable-optical disc drives, CD-ROM drives, WORM disc drives and tape drives are fully...can use 56K leased lines, TI links, digital data circuits, or public telephone lines. 3. ISDN The Integrated Services Digital Network, ISDN, is a

Photonics

NASA Technical Reports Server (NTRS)

1991-01-01

Optoelectronic materials and devices are examined. Optoelectronic devices, which generate, detect, modulate, or switch electromagnetic radiation are being developed for a variety of space applications. The program includes spatial light modulators, solid state lasers, optoelectronic integrated circuits, nonlinear optical materials and devices, fiber optics, and optical networking photovoltaic technology and optical processing.

Multi-objective optimization of piezoelectric circuitry network for mode delocalization and suppression of bladed disk

NASA Astrophysics Data System (ADS)

Yoo, David; Tang, J.

2017-04-01

Since weakly-coupled bladed disks are highly sensitive to the presence of uncertainties, they can easily undergo vibration localization. When vibration localization occurs, vibration modes of bladed disk become dramatically different from those under the perfectly periodic condition, and the dynamic response under engine-order excitation is drastically amplified. In previous studies, it is investigated that amplified vibration response can be suppressed by connecting piezoelectric circuitry into individual blades to induce the damped absorber effect, and localized vibration modes can be alleviated by integrating piezoelectric circuitry network. Delocalization of vibration modes and vibration suppression of bladed disk, however, require different optimal set of circuit parameters. In this research, multi-objective optimization approach is developed to enable finding the best circuit parameters, simultaneously achieving both objectives. In this way, the robustness and reliability in bladed disk can be ensured. Gradient-based optimizations are individually developed for mode delocalization and vibration suppression, which are then integrated into multi-objective optimization framework.

Disruptions in Functional Network Connectivity during Alcohol Intoxicated Driving

PubMed Central

Rzepecki-Smith, Catherine I.; Meda, Shashwath A.; Calhoun, Vince D.; Stevens, Michael C.; Jafri, Madiha J.; Astur, Robert S.; Pearlson, Godfrey D.

2009-01-01

Background: Driving while under the influence of alcohol is a major public health problem whose neural basis is not well understood. In a recently published fMRI study (Meda et al, 2009), our group identified five, independent critical driving-associated brain circuits whose inter-regional connectivity was disrupted by alcohol intoxication. However, the functional connectivity between these circuits has not yet been explored in order to determine how these networks communicate with each other during sober and alcohol-intoxicated states. Methods: In the current study, we explored such differences in connections between the above brain circuits and driving behavior, under the influence of alcohol versus placebo. Forty social drinkers who drove regularly underwent fMRI scans during virtual reality driving simulations following two alcohol doses, placebo and an individualized dose producing blood alcohol concentrations (BACs) of 0.10%. Results: At the active dose, we found specific disruptions of functional network connectivity between the frontal-temporal-basal ganglia and the cerebellar circuits. The temporal connectivity between these two circuits was found to be less correlated (p <0.05) when driving under the influence of alcohol. This disconnection was also associated with an abnormal driving behavior (unstable motor vehicle steering). Conclusions: Connections between frontal-temporal-basal ganglia and cerebellum have recently been explored; these may be responsible in part for maintaining normal motor behavior by integrating their overlapping motor control functions. These connections appear to be disrupted by alcohol intoxication, in turn associated with an explicit type of impaired driving behavior. PMID:20028354

QKD-Based Secured Burst Integrity Design for Optical Burst Switched Networks

NASA Astrophysics Data System (ADS)

Balamurugan, A. M.; Sivasubramanian, A.; Parvathavarthini, B.

2016-03-01

The field of optical transmission has undergone numerous advancements and is still being researched mainly due to the fact that optical data transmission can be done at enormous speeds. It is quite evident that people prefer optical communication when it comes to large amount of data involving its transmission. The concept of switching in networks has matured enormously with several researches, architecture to implement and methods starting with Optical circuit switching to Optical Burst Switching. Optical burst switching is regarded as viable solution for switching bursts over networks but has several security vulnerabilities. However, this work exploited the security issues associated with Optical Burst Switching with respect to integrity of burst. This proposed Quantum Key based Secure Hash Algorithm (QKBSHA-512) with enhanced compression function design provides better avalanche effect over the conventional integrity algorithms.

NASCOM network ground communications availability report

NASA Technical Reports Server (NTRS)

1983-01-01

A performance analysis of NASCOM Network circuits is presented. An objective of 99.80 percent availability has been established for all network circuits and an acceptable level of 99.50. A network narrative summary for the current month includes changes in network configurations, current month's totals for modes of service and trouble category losses, a discussion of trends, and significant losses that affected the performance indexes of individual or groups of circuits. A table and narrative summary of those circuits that failed to meet the objective of 99.80% availability for all network circuits and an acceptable level of 99.50. Lost time and interruption tables showing all circuits affected by outages, by trouble category, with their total time and events, scheduled operating hours, and individual availability indexes also are included. Selected circuits whose availabilities have or continue to affect the overall network availability are also analyzed.

Software-Reconfigurable Processors for Spacecraft

NASA Technical Reports Server (NTRS)

Farrington, Allen; Gray, Andrew; Bell, Bryan; Stanton, Valerie; Chong, Yong; Peters, Kenneth; Lee, Clement; Srinivasan, Jeffrey

2005-01-01

A report presents an overview of an architecture for a software-reconfigurable network data processor for a spacecraft engaged in scientific exploration. When executed on suitable electronic hardware, the software performs the functions of a physical layer (in effect, acts as a software radio in that it performs modulation, demodulation, pulse-shaping, error correction, coding, and decoding), a data-link layer, a network layer, a transport layer, and application-layer processing of scientific data. The software-reconfigurable network processor is undergoing development to enable rapid prototyping and rapid implementation of communication, navigation, and scientific signal-processing functions; to provide a long-lived communication infrastructure; and to provide greatly improved scientific-instrumentation and scientific-data-processing functions by enabling science-driven in-flight reconfiguration of computing resources devoted to these functions. This development is an extension of terrestrial radio and network developments (e.g., in the cellular-telephone industry) implemented in software running on such hardware as field-programmable gate arrays, digital signal processors, traditional digital circuits, and mixed-signal application-specific integrated circuits (ASICs).

Laser dynamics: The system dynamics and network theory of optoelectronic integrated circuit design

NASA Astrophysics Data System (ADS)

Tarng, Tom Shinming-T. K.

Laser dynamics is the system dynamics, communication and network theory for the design of opto-electronic integrated circuit (OEIC). Combining the optical network theory and optical communication theory, the system analysis and design for the OEIC fundamental building blocks is considered. These building blocks include the direct current modulation, inject light modulation, wideband filter, super-gain optical amplifier, E/O and O/O optical bistability and current-controlled optical oscillator. Based on the rate equations, the phase diagram and phase portrait analysis is applied to the theoretical studies and numerical simulation. The OEIC system design methodologies are developed for the OEIC design. Stimulating-field-dependent rate equations are used to model the line-width narrowing/broadening mechanism for the CW mode and frequency chirp of semiconductor lasers. The momentary spectra are carrier-density-dependent. Furthermore, the phase portrait analysis and the nonlinear refractive index is used to simulate the single mode frequency chirp. The average spectra of chaos, period doubling, period pulsing, multi-loops and analog modulation are generated and analyzed. The bifurcation-chirp design chart with modulation depth and modulation frequency as parameters is provided for design purpose.

Artificial Neural Network with Hardware Training and Hardware Refresh

NASA Technical Reports Server (NTRS)

Duong, Tuan A. (Inventor)

2003-01-01

A neural network circuit is provided having a plurality of circuits capable of charge storage. Also provided is a plurality of circuits each coupled to at least one of the plurality of charge storage circuits and constructed to generate an output in accordance with a neuron transfer function. Each of a plurality of circuits is coupled to one of the plurality of neuron transfer function circuits and constructed to generate a derivative of the output. A weight update circuit updates the charge storage circuits based upon output from the plurality of transfer function circuits and output from the plurality of derivative circuits. In preferred embodiments, separate training and validation networks share the same set of charge storage circuits and may operate concurrently. The validation network has a separate transfer function circuits each being coupled to the charge storage circuits so as to replicate the training network s coupling of the plurality of charge storage to the plurality of transfer function circuits. The plurality of transfer function circuits may be constructed each having a transconductance amplifier providing differential currents combined to provide an output in accordance with a transfer function. The derivative circuits may have a circuit constructed to generate a biased differential currents combined so as to provide the derivative of the transfer function.

The wiring diagram for plant G signaling

DOE PAGES

Colaneri, Alejandro C.; Jones, Alan M.

2014-10-01

Like electronic circuits, the modular arrangement of cell-signaling networks decides how inputs produce outputs. Animal heterotrimeric guanine nucleotide binding proteins (G-proteins) operate as switches in the circuits that signal between extracellular agonists and intracellular effectors. There still is no biochemical evidence for a receptor or its agonist in the plant G-protein pathways. Plant G-proteins deviate in many important ways from the animal paradigm. This paper covers important discoveries from the last two years that enlighten these differences and ends describing alternative wiring diagrams for the plant signaling circuits regulated by G-proteins. Finally, we propose that plant G-proteins are integrated inmore » the signaling circuits as variable resistor rather than switches, controlling the flux of information in response to the cell's metabolic state.« less

47 CFR 95.1313 - Interconnection prohibited.

Code of Federal Regulations, 2010 CFR

2010-10-01

... points in the wireline or radio network of a public telephone company and persons served by multi-use... licensees or other authorized persons for transmitter control (including dial-up transmitter control circuits) or as an integral part of an authorized, private, internal system of communication or as an...

High on food: the interaction between the neural circuits for feeding and for reward.

PubMed

Liu, Jing-Jing; Mukherjee, Diptendu; Haritan, Doron; Ignatowska-Jankowska, Bogna; Liu, Ji; Citri, Ami; Pang, Zhiping P

2015-04-01

Hunger, mostly initiated by a deficiency in energy, induces food seeking and intake. However, the drive toward food is not only regulated by physiological needs, but is motivated by the pleasure derived from ingestion of food, in particular palatable foods. Therefore, feeding is viewed as an adaptive motivated behavior that involves integrated communication between homeostatic feeding circuits and reward circuits. The initiation and termination of a feeding episode are instructed by a variety of neuronal signals, and maladaptive plasticity in almost any component of the network may lead to the development of pathological eating disorders. In this review we will summarize the latest understanding of how the feeding circuits and reward circuits in the brain interact. We will emphasize communication between the hypothalamus and the mesolimbic dopamine system and highlight complexities, discrepancies, open questions and future directions for the field.

High-Gain AlxGa1-xAs/GaAs Transistors For Neural Networks

NASA Technical Reports Server (NTRS)

Kim, Jae-Hoon; Lin, Steven H.

1991-01-01

High-gain AlxGa1-xAs/GaAs npn double heterojunction bipolar transistors developed for use as phototransistors in optoelectronic integrated circuits, especially in artificial neural networks. Transistors perform both photodetection and saturating-amplification functions of neurons. Good candidates for such application because structurally compatible with laser diodes and light-emitting diodes, detect light, and provide high current gain needed to compensate for losses in holographic optical elements.

Deterministic Integration of Quantum Dots into on-Chip Multimode Interference Beamsplitters Using in Situ Electron Beam Lithography.

PubMed

Schnauber, Peter; Schall, Johannes; Bounouar, Samir; Höhne, Theresa; Park, Suk-In; Ryu, Geun-Hwan; Heindel, Tobias; Burger, Sven; Song, Jin-Dong; Rodt, Sven; Reitzenstein, Stephan

2018-04-11

The development of multinode quantum optical circuits has attracted great attention in recent years. In particular, interfacing quantum-light sources, gates, and detectors on a single chip is highly desirable for the realization of large networks. In this context, fabrication techniques that enable the deterministic integration of preselected quantum-light emitters into nanophotonic elements play a key role when moving forward to circuits containing multiple emitters. Here, we present the deterministic integration of an InAs quantum dot into a 50/50 multimode interference beamsplitter via in situ electron beam lithography. We demonstrate the combined emitter-gate interface functionality by measuring triggered single-photon emission on-chip with g (2) (0) = 0.13 ± 0.02. Due to its high patterning resolution as well as spectral and spatial control, in situ electron beam lithography allows for integration of preselected quantum emitters into complex photonic systems. Being a scalable single-step approach, it paves the way toward multinode, fully integrated quantum photonic chips.

Neural representations of relevant and irrelevant features in perceptual decision making

PubMed Central

Kayser, Andrew S.; Erickson, Drew T.; Buchsbaum, Bradley R.; D'Esposito, Mark

2010-01-01

Although perceptual decision-making activates a network of brain areas involved in sensory, integrative, and motor functions, circuit activity can clearly be modulated by factors beyond the stimulus. Of particular interest is to understand how the network is modulated by top-down factors such as attention. Here we demonstrate in a motion coherence task that selective attention produces marked changes in the BOLD response in a subset of regions within a human perceptual decision-making circuit. Specifically, when motion is attended, the BOLD response decreases with increasing motion coherence in many regions, including the motion-sensitive area MT+, the intraparietal sulcus (IPS), and the inferior frontal sulcus (IFS). However, when motion is ignored, the negative parametric response in a subset of this circuit becomes positive. Through both modeling and connectivity analyses, we demonstrate that this inversion both reflects a top-down influence and segregates attentional from accumulation regions, thereby permitting us to further delineate the contributions of different regions to the perceptual decision. PMID:21106817

Design and Implementation of a High-Power Resonant DC-DC Converter Module for a Reduced-Scale Prototype Integrated Power System

DTIC Science & Technology

2001-09-01

damping RC network . The filter was designed to have a pole pair (~450 Hz) above the 360 Hz ripple of the six-pulse rectified DC supply but well below the...Circuit With Input Filtering Included. The damping network was designed using the guidance provided in reference [24] and its function is to lower the...converter as a linear network and estimated the spectrum envelope by multiplying the Fourier transform of the current waveform by the transfer

Afferent specific role of NMDA receptors for the circuit integration of hippocampal neurogliaform cells.

PubMed

Chittajallu, R; Wester, J C; Craig, M T; Barksdale, E; Yuan, X Q; Akgül, G; Fang, C; Collins, D; Hunt, S; Pelkey, K A; McBain, C J

2017-07-28

Appropriate integration of GABAergic interneurons into nascent cortical circuits is critical for ensuring normal information processing within the brain. Network and cognitive deficits associated with neurological disorders, such as schizophrenia, that result from NMDA receptor-hypofunction have been mainly attributed to dysfunction of parvalbumin-expressing interneurons that paradoxically express low levels of synaptic NMDA receptors. Here, we reveal that throughout postnatal development, thalamic, and entorhinal cortical inputs onto hippocampal neurogliaform cells are characterized by a large NMDA receptor-mediated component. This NMDA receptor-signaling is prerequisite for developmental programs ultimately responsible for the appropriate long-range AMPAR-mediated recruitment of neurogliaform cells. In contrast, AMPAR-mediated input at local Schaffer-collateral synapses on neurogliaform cells remains normal following NMDA receptor-ablation. These afferent specific deficits potentially impact neurogliaform cell mediated inhibition within the hippocampus and our findings reveal circuit loci implicating this relatively understudied interneuron subtype in the etiology of neurodevelopmental disorders characterized by NMDA receptor-hypofunction.Proper brain function depends on the correct assembly of excitatory and inhibitory neurons into neural circuits. Here the authors show that during early postnatal development in mice, NMDAR signaling via activity of long-range synaptic inputs onto neurogliaform cells is required for their appropriate integration into the hippocampal circuitry.

Results on 3D interconnection from AIDA WP3

NASA Astrophysics Data System (ADS)

Moser, Hans-Günther; AIDA-WP3

2016-09-01

From 2010 to 2014 the EU funded AIDA project established in one of its work packages (WP3) a network of groups working collaboratively on advanced 3D integration of electronic circuits and semiconductor sensors for applications in particle physics. The main motivation came from the severe requirements on pixel detectors for tracking and vertexing at future Particle Physics experiments at LHC, super-B factories and linear colliders. To go beyond the state-of-the-art, the main issues were studying low mass, high bandwidth applications, with radiation hardness capabilities, with low power consumption, offering complex functionality, with small pixel size and without dead regions. The interfaces and interconnects of sensors to electronic readout integrated circuits are a key challenge for new detector applications.

Metropolitan Quantum Key Distribution with Silicon Photonics

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

Bunandar, Darius; Lentine, Anthony; Lee, Catherine

Photonic integrated circuits provide a compact and stable platform for quantum photonics. Here we demonstrate a silicon photonics quantum key distribution (QKD) encoder in the first high-speed polarization-based QKD field tests. The systems reach composable secret key rates of 1.039 Mbps in a local test (on a 103.6-m fiber with a total emulated loss of 9.2 dB) and 157 kbps in an intercity metropolitan test (on a 43-km fiber with 16.4 dB loss). Our results represent the highest secret key generation rate for polarization-based QKD experiments at a standard telecom wavelength and demonstrate photonic integrated circuits as a promising, scalablemore » resource for future formation of metropolitan quantum-secure communications networks.« less

Metropolitan Quantum Key Distribution with Silicon Photonics

DOE PAGES

Bunandar, Darius; Lentine, Anthony; Lee, Catherine; ...

2018-04-06

Photonic integrated circuits provide a compact and stable platform for quantum photonics. Here we demonstrate a silicon photonics quantum key distribution (QKD) encoder in the first high-speed polarization-based QKD field tests. The systems reach composable secret key rates of 1.039 Mbps in a local test (on a 103.6-m fiber with a total emulated loss of 9.2 dB) and 157 kbps in an intercity metropolitan test (on a 43-km fiber with 16.4 dB loss). Our results represent the highest secret key generation rate for polarization-based QKD experiments at a standard telecom wavelength and demonstrate photonic integrated circuits as a promising, scalablemore » resource for future formation of metropolitan quantum-secure communications networks.« less

Metropolitan Quantum Key Distribution with Silicon Photonics

NASA Astrophysics Data System (ADS)

Bunandar, Darius; Lentine, Anthony; Lee, Catherine; Cai, Hong; Long, Christopher M.; Boynton, Nicholas; Martinez, Nicholas; DeRose, Christopher; Chen, Changchen; Grein, Matthew; Trotter, Douglas; Starbuck, Andrew; Pomerene, Andrew; Hamilton, Scott; Wong, Franco N. C.; Camacho, Ryan; Davids, Paul; Urayama, Junji; Englund, Dirk

2018-04-01

Photonic integrated circuits provide a compact and stable platform for quantum photonics. Here we demonstrate a silicon photonics quantum key distribution (QKD) encoder in the first high-speed polarization-based QKD field tests. The systems reach composable secret key rates of 1.039 Mbps in a local test (on a 103.6-m fiber with a total emulated loss of 9.2 dB) and 157 kbps in an intercity metropolitan test (on a 43-km fiber with 16.4 dB loss). Our results represent the highest secret key generation rate for polarization-based QKD experiments at a standard telecom wavelength and demonstrate photonic integrated circuits as a promising, scalable resource for future formation of metropolitan quantum-secure communications networks.

Network origin-destination demand estimation using limited link traffic counts : strategic deployment of vehicle detectors through an integrated corridor management framework.

DOT National Transportation Integrated Search

2009-10-15

In typical road traffic corridors, freeway systems are generally well-equipped with traffic surveillance systems such as vehicle detector (VD) and/or closed circuit television (CCTV) systems in order to gather timely traffic information for traffic c...

Unified equivalent circuit model for carbon nanotube-based nanocomposites.

PubMed

Zhao, Chaoyang; Yuan, Weifeng; Zhao, Yangzhou; Hu, Ning; Gu, Bin; Liu, Haidong; Alamusi

2018-07-27

Carbon nanotubes form a complex network in nanocomposites. In the network, the configuration of the nanotubes is various. A carbon nanotube may be curled or straight, and it may be parallel or crossed to another. As a result, carbon nanotube-based composites exhibit integrated characteristics of inductor, capacitor and resistor. In this work, it is hypothesised that carbon nanotube-based composites all adhere to a RLC interior circuit. To verify the hypothesis, three different composites, viz multi-walled carbon nanotube/polyvinylidene fluoride (MWCNT/PVDF), multi-walled carbon nanotube/epoxy (MWCNT/EP), multi-walled carbon nanotube/polydimethylsiloxane (MWCNT/PDMS) were fabricated and tested. The resistances and the dielectric loss tangent (tanδ) of the materials were measured in direct and alternating currents. The measurement shows that the value of tanδ is highly affected by the volume fraction of MWCNT in the composites. The experimental results prove that the proposed RLC equivalent circuit model can fully describe the electrical properties of the MWCNT network in nanocomposites. The RLC model provides a new route to detect the inductance and capacitance of carbon nanotubes. Moreover, the model also indicates that the carbon nanotube-based composite films may be used to develop wireless strain sensors.

Behavioral modeling of VCSELs for high-speed optical interconnects

NASA Astrophysics Data System (ADS)

Szczerba, Krzysztof; Kocot, Chris

2018-02-01

Transition from on-off keying to 4-level pulse amplitude modulation (PAM) in VCSEL based optical interconnects allows for an increase of data rates, at the cost of 4.8 dB sensitivity penalty. The resulting strained link budget creates a need for accurate VCSEL models for driver integrated circuit (IC) design and system level simulations. Rate equation based equivalent circuit models are convenient for the IC design, but system level analysis requires computationally efficient closed form behavioral models based Volterra series and neural networks. In this paper we present and compare these models.

Materials Integration and Doping of Carbon Nanotube-based Logic Circuits

NASA Astrophysics Data System (ADS)

Geier, Michael

Over the last 20 years, extensive research into the structure and properties of single- walled carbon nanotube (SWCNT) has elucidated many of the exceptional qualities possessed by SWCNTs, including record-setting tensile strength, excellent chemical stability, distinctive optoelectronic features, and outstanding electronic transport characteristics. In order to exploit these remarkable qualities, many application-specific hurdles must be overcome before the material can be implemented in commercial products. For electronic applications, recent advances in sorting SWCNTs by electronic type have enabled significant progress towards SWCNT-based integrated circuits. Despite these advances, demonstrations of SWCNT-based devices with suitable characteristics for large-scale integrated circuits have been limited. The processing methodologies, materials integration, and mechanistic understanding of electronic properties developed in this dissertation have enabled unprecedented scales of SWCNT-based transistor fabrication and integrated circuit demonstrations. Innovative materials selection and processing methods are at the core of this work and these advances have led to transistors with the necessary transport properties required for modern circuit integration. First, extensive collaborations with other research groups allowed for the exploration of SWCNT thin-film transistors (TFTs) using a wide variety of materials and processing methods such as new dielectric materials, hybrid semiconductor materials systems, and solution-based printing of SWCNT TFTs. These materials were integrated into circuit demonstrations such as NOR and NAND logic gates, voltage-controlled ring oscillators, and D-flip-flops using both rigid and flexible substrates. This dissertation explores strategies for implementing complementary SWCNT-based circuits, which were developed by using local metal gate structures that achieve enhancement-mode p-type and n-type SWCNT TFTs with widely separated and symmetric threshold voltages. Additionally, a novel n-type doping procedure for SWCNT TFTs was also developed utilizing a solution-processed organometallic small molecule to demonstrate the first network top-gated n-type SWCNT TFTs. Lastly, new doping and encapsulation layers were incorporated to stabilize both p-type and n-type SWCNT TFT electronic properties, which enabled the fabrication of large-scale memory circuits. Employing these materials and processing advances has addressed many application specific barriers to commercialization. For instance, the first thin-film SWCNT complementary metal-oxide-semi-conductor (CMOS) logic devices are demonstrated with sub-nanowatt static power consumption and full rail-to-rail voltage transfer characteristics. With the introduction of a new n-type Rh-based molecular dopant, the first SWCNT TFTs are fabricated in top-gate geometries over large areas with high yield. Then by utilizing robust encapsulation methods, stable and uniform electronic performance of both p-type and n-type SWCNT TFTs has been achieved. Based on these complementary SWCNT TFTs, it is possible to simulate, design, and fabricate arrays of low-power static random access memory (SRAM) circuits, achieving large-scale integration for the first time based on solution-processed semiconductors. Together, this work provides a direct pathway for solution processable, large scale, power-efficient advanced integrated logic circuits and systems.

Integrated modelling for the evaluation of infiltration effects.

PubMed

Schulz, N; Baur, R; Krebs, P

2005-01-01

The objective of the present study is the estimation of the potential benefits of sewer pipe rehabilitation for the performance of the drainage system and the wastewater treatment plant (WWTP) as well as for the receiving water quality. The relation of sewer system status and the infiltration rate is assessed based on statistical analysis of 470 km of CCTV (Closed Circuit Television) inspected sewers of the city of Dresden. The potential reduction of infiltration rates and the consequent performance improvements of the urban wastewater system are simulated as a function of rehabilitation activities in the network. The integrated model is applied to an artificial system with input from a real sewer network. In this paper, the general design of the integrated model and its data requirements are presented. For an exemplary study, the consequences of the simulations are discussed with respect to the prioritisation of rehabilitation activities in the network.

Video data compression using artificial neural network differential vector quantization

NASA Technical Reports Server (NTRS)

Krishnamurthy, Ashok K.; Bibyk, Steven B.; Ahalt, Stanley C.

1991-01-01

An artificial neural network vector quantizer is developed for use in data compression applications such as Digital Video. Differential Vector Quantization is used to preserve edge features, and a new adaptive algorithm, known as Frequency-Sensitive Competitive Learning, is used to develop the vector quantizer codebook. To develop real time performance, a custom Very Large Scale Integration Application Specific Integrated Circuit (VLSI ASIC) is being developed to realize the associative memory functions needed in the vector quantization algorithm. By using vector quantization, the need for Huffman coding can be eliminated, resulting in superior performance against channel bit errors than methods that use variable length codes.

The DYNES Instrument: A Description and Overview

NASA Astrophysics Data System (ADS)

Zurawski, Jason; Ball, Robert; Barczyk, Artur; Binkley, Mathew; Boote, Jeff; Boyd, Eric; Brown, Aaron; Brown, Robert; Lehman, Tom; McKee, Shawn; Meekhof, Benjeman; Mughal, Azher; Newman, Harvey; Rozsa, Sandor; Sheldon, Paul; Tackett, Alan; Voicu, Ramiro; Wolff, Stephen; Yang, Xi

2012-12-01

Scientific innovation continues to increase requirements for the computing and networking infrastructures of the world. Collaborative partners, instrumentation, storage, and processing facilities are often geographically and topologically separated, as is the case with LHC virtual organizations. These separations challenge the technology used to interconnect available resources, often delivered by Research and Education (R&E) networking providers, and leads to complications in the overall process of end-to-end data management. Capacity and traffic management are key concerns of R&E network operators; a delicate balance is required to serve both long-lived, high capacity network flows, as well as more traditional end-user activities. The advent of dynamic circuit services, a technology that enables the creation of variable duration, guaranteed bandwidth networking channels, allows for the efficient use of common network infrastructures. These gains are seen particularly in locations where overall capacity is scarce compared to the (sustained peak) needs of user communities. Related efforts, including those of the LHCOPN [3] operations group and the emerging LHCONE [4] project, may take advantage of available resources by designating specific network activities as a “high priority”, allowing reservation of dedicated bandwidth or optimizing for deadline scheduling and predicable delivery patterns. This paper presents the DYNES instrument, an NSF funded cyberinfrastructure project designed to facilitate end-to-end dynamic circuit services [2]. This combination of hardware and software innovation is being deployed across R&E networks in the United States at selected end-sites located on University Campuses. DYNES is peering with international efforts in other countries using similar solutions, and is increasing the reach of this emerging technology. This global data movement solution could be integrated into computing paradigms such as cloud and grid computing platforms, and through the use of APIs can be integrated into existing data movement software.

A Digitally Programmable Cytomorphic Chip for Simulation of Arbitrary Biochemical Reaction Networks.

PubMed

Woo, Sung Sik; Kim, Jaewook; Sarpeshkar, Rahul

2018-04-01

Prior work has shown that compact analog circuits can faithfully represent and model fundamental biomolecular circuits via efficient log-domain cytomorphic transistor equivalents. Such circuits have emphasized basis functions that are dominant in genetic transcription and translation networks and deoxyribonucleic acid (DNA)-protein binding. Here, we report a system featuring digitally programmable 0.35 μm BiCMOS analog cytomorphic chips that enable arbitrary biochemical reaction networks to be exactly represented thus enabling compact and easy composition of protein networks as well. Since all biomolecular networks can be represented as chemical reaction networks, our protein networks also include the former genetic network circuits as a special case. The cytomorphic analog protein circuits use one fundamental association-dissociation-degradation building-block circuit that can be configured digitally to exactly represent any zeroth-, first-, and second-order reaction including loading, dynamics, nonlinearity, and interactions with other building-block circuits. To address a divergence issue caused by random variations in chip fabrication processes, we propose a unique way of performing computation based on total variables and conservation laws, which we instantiate at both the circuit and network levels. Thus, scalable systems that operate with finite error over infinite time can be built. We show how the building-block circuits can be composed to form various network topologies, such as cascade, fan-out, fan-in, loop, dimerization, or arbitrary networks using total variables. We demonstrate results from a system that combines interacting cytomorphic chips to simulate a cancer pathway and a glycolysis pathway. Both simulations are consistent with conventional software simulations. Our highly parallel digitally programmable analog cytomorphic systems can lead to a useful design, analysis, and simulation tool for studying arbitrary large-scale biological networks in systems and synthetic biology.

Neural control of locomotion and training-induced plasticity after spinal and cerebral lesions.

PubMed

Knikou, Maria

2010-10-01

Standing and walking require a plethora of sensorimotor interactions that occur throughout the nervous system. Sensory afferent feedback plays a crucial role in the rhythmical muscle activation pattern, as it affects through spinal reflex circuits the spinal neuronal networks responsible for inducing and maintaining rhythmicity, drives short-term and long-term re-organization of the brain and spinal cord circuits, and contributes to recovery of walking after locomotor training. Therefore, spinal circuits integrating sensory signals are adjustable networks with learning capabilities. In this review, I will synthesize the mechanisms underlying phase-dependent modulation of spinal reflexes in healthy humans as well as those with spinal or cerebral lesions along with findings on afferent regulation of spinal reflexes and central pattern generator in reduced animal preparations. Recovery of walking after locomotor training has been documented in numerous studies but the re-organization of spinal interneuronal and cortical circuits need to be further explored at cellular and physiological levels. For maximizing sensorimotor recovery in people with spinal or cerebral lesions, a multidisciplinary approach (rehabilitation, pharmacology, and electrical stimulation) delivered during various sensorimotor constraints is needed. Copyright 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Nonreciprocal Signal Routing in an Active Quantum Network

NASA Astrophysics Data System (ADS)

Tureci, Hakan E.; Metelmann, Anja

As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain driven linear or non-linear elements judiciously embedded in the circuit offer a viable solution. We present a general strategy for routing non-reciprocally quantum signals between two sites of a given lattice of resonators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of superconducting non-linear elements on the links connecting the nodes of the main lattice. Solutions for spatially selective driving of the link-elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to non-reciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the scattering matrix of the network. The presented strategy provides a design space that is governed by a dynamically tunable non-Hermitian generator that can be used to minimize the added quantum noise as well. This work was supported by the U.S. Army Research Office (ARO) under Grant No. W911NF-15-1-0299.

Definition, analysis and development of an optical data distribution network for integrated avionics and control systems. Part 2: Component development and system integration

NASA Technical Reports Server (NTRS)

Yen, H. W.; Morrison, R. J.

1984-01-01

Fiber optic transmission is emerging as an attractive concept in data distribution onboard civil aircraft. Development of an Optical Data Distribution Network for Integrated Avionics and Control Systems for commercial aircraft will provide a data distribution network that gives freedom from EMI-RFI and ground loop problems, eliminates crosstalk and short circuits, provides protection and immunity from lightning induced transients and give a large bandwidth data transmission capability. In addition there is a potential for significantly reducing the weight and increasing the reliability over conventional data distribution networks. Wavelength Division Multiplexing (WDM) is a candidate method for data communication between the various avionic subsystems. With WDM all systems could conceptually communicate with each other without time sharing and requiring complicated coding schemes for each computer and subsystem to recognize a message. However, the state of the art of optical technology limits the application of fiber optics in advanced integrated avionics and control systems. Therefore, it is necessary to address the architecture for a fiber optics data distribution system for integrated avionics and control systems as well as develop prototype components and systems.

Minimizing the area required for time constants in integrated circuits

NASA Technical Reports Server (NTRS)

Lyons, J. C.

1972-01-01

When a medium- or large-scale integrated circuit is designed, efforts are usually made to avoid the use of resistor-capacitor time constant generators. The capacitor needed for this circuit usually takes up more surface area on the chip than several resistors and transistors. When the use of this network is unavoidable, the designer usually makes an effort to see that the choice of resistor and capacitor combinations is such that a minimum amount of surface area is consumed. The optimum ratio of resistance to capacitance that will result in this minimum area is equal to the ratio of resistance to capacitance which may be obtained from a unit of surface area for the particular process being used. The minimum area required is a function of the square root of the reciprocal of the products of the resistance and capacitance per unit area. This minimum occurs when the area required by the resistor is equal to the area required by the capacitor.

Design of pressure-driven microfluidic networks using electric circuit analogy.

PubMed

Oh, Kwang W; Lee, Kangsun; Ahn, Byungwook; Furlani, Edward P

2012-02-07

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

On-chip passive three-port circuit of all-optical ordered-route transmission.

PubMed

Liu, Li; Dong, Jianji; Gao, Dingshan; Zheng, Aoling; Zhang, Xinliang

2015-05-13

On-chip photonic circuits of different specific functions are highly desirable and becoming significant demands in all-optical communication network. Especially, the function to control the transmission directions of the optical signals in integrated circuits is a fundamental research. Previous schemes, such as on-chip optical circulators, are mostly realized by Faraday effect which suffers from material incompatibilities between semiconductors and magneto-optical materials. Achieving highly functional circuits in which light circulates in a particular direction with satisfied performances are still difficult in pure silicon photonics platform. Here, we propose and experimentally demonstrate a three-port passive device supporting optical ordered-route transmission based on silicon thermo-optic effect for the first time. By injecting strong power from only one port, the light could transmit through the three ports in a strict order (1→2, 2→3, 3→1) while be blocked in the opposite order (1→3, 3→2, 2→1). The blocking extinction ratios and operation bandwidths have been investigated in this paper. Moreover, with compact size, economic fabrication process and great extensibility, this proposed photonic integrated circuit is competitive to be applied in on-chip all-optical information processing systems, such as path priority selector.

On-chip passive three-port circuit of all-optical ordered-route transmission

PubMed Central

Liu, Li; Dong, Jianji; Gao, Dingshan; Zheng, Aoling; Zhang, Xinliang

2015-01-01

On-chip photonic circuits of different specific functions are highly desirable and becoming significant demands in all-optical communication network. Especially, the function to control the transmission directions of the optical signals in integrated circuits is a fundamental research. Previous schemes, such as on-chip optical circulators, are mostly realized by Faraday effect which suffers from material incompatibilities between semiconductors and magneto-optical materials. Achieving highly functional circuits in which light circulates in a particular direction with satisfied performances are still difficult in pure silicon photonics platform. Here, we propose and experimentally demonstrate a three-port passive device supporting optical ordered-route transmission based on silicon thermo-optic effect for the first time. By injecting strong power from only one port, the light could transmit through the three ports in a strict order (1→2, 2→3, 3→1) while be blocked in the opposite order (1→3, 3→2, 2→1). The blocking extinction ratios and operation bandwidths have been investigated in this paper. Moreover, with compact size, economic fabrication process and great extensibility, this proposed photonic integrated circuit is competitive to be applied in on-chip all-optical information processing systems, such as path priority selector. PMID:25970855

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

PubMed

Merolla, Paul A; Arthur, John V; Alvarez-Icaza, Rodrigo; Cassidy, Andrew S; Sawada, Jun; Akopyan, Filipp; Jackson, Bryan L; Imam, Nabil; Guo, Chen; Nakamura, Yutaka; Brezzo, Bernard; Vo, Ivan; Esser, Steven K; Appuswamy, Rathinakumar; Taba, Brian; Amir, Arnon; Flickner, Myron D; Risk, William P; Manohar, Rajit; Modha, Dharmendra S

2014-08-08

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts. Copyright © 2014, American Association for the Advancement of Science.

Integrating Metal-Oxide-Decorated CNT Networks with a CMOS Readout in a Gas Sensor

PubMed Central

Lee, Hyunjoong; Lee, Sanghoon; Kim, Dai-Hong; Perello, David; Park, Young June; Hong, Seong-Hyeon; Yun, Minhee; Kim, Suhwan

2012-01-01

We have implemented a tin-oxide-decorated carbon nanotube (CNT) network gas sensor system on a single die. We have also demonstrated the deposition of metallic tin on the CNT network, its subsequent oxidation in air, and the improvement of the lifetime of the sensors. The fabricated array of CNT sensors contains 128 sensor cells for added redundancy and increased accuracy. The read-out integrated circuit (ROIC) was combined with coarse and fine time-to-digital converters to extend its resolution in a power-efficient way. The ROIC is fabricated using a 0.35 μm CMOS process, and the whole sensor system consumes 30 mA at 5 V. The sensor system was successfully tested in the detection of ammonia gas at elevated temperatures. PMID:22736966

Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment.

PubMed

Peters, Sarah K; Dunlop, Katharine; Downar, Jonathan

2016-01-01

The salience network (SN) plays a central role in cognitive control by integrating sensory input to guide attention, attend to motivationally salient stimuli and recruit appropriate functional brain-behavior networks to modulate behavior. Mounting evidence suggests that disturbances in SN function underlie abnormalities in cognitive control and may be a common etiology underlying many psychiatric disorders. Such functional and anatomical abnormalities have been recently apparent in studies and meta-analyses of psychiatric illness using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). Of particular importance, abnormal structure and function in major cortical nodes of the SN, the dorsal anterior cingulate cortex (dACC) and anterior insula (AI), have been observed as a common neurobiological substrate across a broad spectrum of psychiatric disorders. In addition to cortical nodes of the SN, the network's associated subcortical structures, including the dorsal striatum, mediodorsal thalamus and dopaminergic brainstem nuclei, comprise a discrete regulatory loop circuit. The SN's cortico-striato-thalamo-cortical loop increasingly appears to be central to mechanisms of cognitive control, as well as to a broad spectrum of psychiatric illnesses and their available treatments. Functional imbalances within the SN loop appear to impair cognitive control, and specifically may impair self-regulation of cognition, behavior and emotion, thereby leading to symptoms of psychiatric illness. Furthermore, treating such psychiatric illnesses using invasive or non-invasive brain stimulation techniques appears to modulate SN cortical-subcortical loop integrity, and these effects may be central to the therapeutic mechanisms of brain stimulation treatments in many psychiatric illnesses. Here, we review clinical and experimental evidence for abnormalities in SN cortico-striatal-thalamic loop circuits in major depression, substance use disorders (SUD), anxiety disorders, schizophrenia and eating disorders (ED). We also review emergent therapeutic evidence that novel invasive and non-invasive brain stimulation treatments may exert therapeutic effects by normalizing abnormalities in the SN loop, thereby restoring the capacity for cognitive control. Finally, we consider a series of promising directions for future investigations on the role of SN cortico-striatal-thalamic loop circuits in the pathophysiology and treatment of psychiatric disorders.

NASCOM network: Ground communications reliability report

NASA Technical Reports Server (NTRS)

1973-01-01

A reliability performance analysis of the NASCOM Network circuits is reported. Network performance narrative summary is presented to include significant changes in circuit configurations, current figures, and trends in each trouble category with notable circuit totals specified. Lost time and interruption tables listing circuits which were affected by outages showing their totals category are submitted. A special analysis of circuits with low reliabilities is developed with tables depicting the performance and graphs for individual reliabilities.

Circuit to Construct Mapping: A Mathematical Tool for Assisting the Diagnosis and Treatment in Major Depressive Disorder

PubMed Central

Bielczyk, Natalia Z.; Buitelaar, Jan K.; Glennon, Jeffrey C.; Tiesinga, Paul H. E.

2015-01-01

Major depressive disorder (MDD) is a serious condition with a lifetime prevalence exceeding 16% worldwide. MDD is a heterogeneous disorder that involves multiple behavioral symptoms on the one hand and multiple neuronal circuits on the other hand. In this review, we integrate the literature on cognitive and physiological biomarkers of MDD with the insights derived from mathematical models of brain networks, especially models that can be used for fMRI datasets. We refer to the recent NIH research domain criteria initiative, in which a concept of “constructs” as functional units of mental disorders is introduced. Constructs are biomarkers present at multiple levels of brain functioning – cognition, genetics, brain anatomy, and neurophysiology. In this review, we propose a new approach which we called circuit to construct mapping (CCM), which aims to characterize causal relations between the underlying network dynamics (as the cause) and the constructs referring to the clinical symptoms of MDD (as the effect). CCM involves extracting diagnostic categories from behavioral data, linking circuits that are causal to these categories with use of clinical neuroimaging data, and modeling the dynamics of the emerging circuits with attractor dynamics in order to provide new, neuroimaging-related biomarkers for MDD. The CCM approach optimizes the clinical diagnosis and patient stratification. It also addresses the recent demand for linking circuits to behavior, and provides a new insight into clinical treatment by investigating the dynamics of neuronal circuits underneath cognitive dimensions of MDD. CCM can serve as a new regime toward personalized medicine, assisting the diagnosis and treatment of MDD. PMID:25767450

Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

PubMed Central

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

2013-01-01

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

Hybrid VLSI/QCA Architecture for Computing FFTs

NASA Technical Reports Server (NTRS)

Fijany, Amir; Toomarian, Nikzad; Modarres, Katayoon; Spotnitz, Matthew

2003-01-01

A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes.

Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability.

PubMed

Wei, Luqing; Chen, Hong; Wu, Guo-Rong

2018-01-01

The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.

The structural and functional brain networks that support human social networks.

PubMed

Noonan, M P; Mars, R B; Sallet, J; Dunbar, R I M; Fellows, L K

2018-02-20

Social skills rely on a specific set of cognitive processes, raising the possibility that individual differences in social networks are related to differences in specific brain structural and functional networks. Here, we tested this hypothesis with multimodality neuroimaging. With diffusion MRI (DMRI), we showed that differences in structural integrity of particular white matter (WM) tracts, including cingulum bundle, extreme capsule and arcuate fasciculus were associated with an individual's social network size (SNS). A voxel-based morphology analysis demonstrated correlations between gray matter (GM) volume and SNS in limbic and temporal lobe regions. These structural changes co-occured with functional network differences. As a function of SNS, dorsomedial and dorsolateral prefrontal cortex showed altered resting-state functional connectivity with the default mode network (DMN). Finally, we integrated these three complementary methods, interrogating the relationship between social GM clusters and specific WM and resting-state networks (RSNs). Probabilistic tractography seeded in these GM nodes utilized the SNS-related WM pathways. Further, the spatial and functional overlap between the social GM clusters and the DMN was significantly closer than other control RSNs. These integrative analyses provide convergent evidence of the role of specific circuits in SNS, likely supporting the adaptive behavior necessary for success in extensive social environments. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Laser programmable integrated circuit for forming synapses in neural networks

DOEpatents

Fu, C.Y.

1997-02-11

Customizable neural network in which one or more resistors form each synapse is disclosed. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength. 5 figs.

Neuronal integration of dynamic sources: Bayesian learning and Bayesian inference.

PubMed

Siegelmann, Hava T; Holzman, Lars E

2010-09-01

One of the brain's most basic functions is integrating sensory data from diverse sources. This ability causes us to question whether the neural system is computationally capable of intelligently integrating data, not only when sources have known, fixed relative dependencies but also when it must determine such relative weightings based on dynamic conditions, and then use these learned weightings to accurately infer information about the world. We suggest that the brain is, in fact, fully capable of computing this parallel task in a single network and describe a neural inspired circuit with this property. Our implementation suggests the possibility that evidence learning requires a more complex organization of the network than was previously assumed, where neurons have different specialties, whose emergence brings the desired adaptivity seen in human online inference.

Programmable chemical controllers made from DNA.

PubMed

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2013-10-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

Programmable chemical controllers made from DNA

NASA Astrophysics Data System (ADS)

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2013-10-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

Programmable chemical controllers made from DNA

PubMed Central

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2014-01-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language', and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents. PMID:24077029

Development of brain-wide connectivity architecture in awake rats.

PubMed

Ma, Zilu; Ma, Yuncong; Zhang, Nanyin

2018-08-01

Childhood and adolescence are both critical developmental periods, evidenced by complex neurophysiological changes the brain undergoes and high occurrence rates of neuropsychiatric disorders during these periods. Despite substantial progress in elucidating the developmental trajectories of individual neural circuits, our knowledge of developmental changes of whole-brain connectivity architecture in animals is sparse. To fill this gap, here we longitudinally acquired rsfMRI data in awake rats during five developmental stages from juvenile to adulthood. We found that the maturation timelines of brain circuits were heterogeneous and system specific. Functional connectivity (FC) tended to decrease in subcortical circuits, but increase in cortical circuits during development. In addition, the developing brain exhibited hemispheric functional specialization, evidenced by reduced inter-hemispheric FC between homotopic regions, and lower similarity of region-to-region FC patterns between the two hemispheres. Finally, we showed that whole-brain network development was characterized by reduced clustering (i.e. local communication) but increased integration (distant communication). Taken together, the present study has systematically characterized the development of brain-wide connectivity architecture from juvenile to adulthood in awake rats. It also serves as a critical reference point for understanding circuit- and network-level changes in animal models of brain development-related disorders. Furthermore, FC data during brain development in awake rodents contain high translational value and can shed light onto comparative neuroanatomy. Copyright © 2018 Elsevier Inc. All rights reserved.

Development and Simulation of Increased Generation on a Secondary Circuit of a Microgrid

NASA Astrophysics Data System (ADS)

Reyes, Karina

As fossil fuels are depleted and their environmental impacts remain, other sources of energy must be considered to generate power. Renewable sources, for example, are emerging to play a major role in this regard. In parallel, electric vehicle (EV) charging is evolving as a major load demand. To meet reliability and resiliency goals demanded by the electricity market, interest in microgrids are growing as a distributed energy resource (DER). In this thesis, the effects of intermittent renewable power generation and random EV charging on secondary microgrid circuits are analyzed in the presence of a controllable battery in order to characterize and better understand the dynamics associated with intermittent power production and random load demands in the context of the microgrid paradigm. For two reasons, a secondary circuit on the University of California, Irvine (UCI) Microgrid serves as the case study. First, the secondary circuit (UC-9) is heavily loaded and an integral component of a highly characterized and metered microgrid. Second, a unique "next-generation" distributed energy resource has been deployed at the end of the circuit that integrates photovoltaic power generation, battery storage, and EV charging. In order to analyze this system and evaluate the impact of the DER on the secondary circuit, a model was developed to provide a real-time load flow analysis. The research develops a power management system applicable to similarly integrated systems. The model is verified by metered data obtained from a network of high resolution electric meters and estimated load data for the buildings that have unknown demand. An increase in voltage is observed when the amount of photovoltaic power generation is increased. To mitigate this effect, a constant power factor is set. Should the real power change dramatically, the reactive power is changed to mitigate voltage fluctuations.

An Electronic-Nose Sensor Node Based on a Polymer-Coated Surface Acoustic Wave Array for Wireless Sensor Network Applications

PubMed Central

Tang, Kea-Tiong; Li, Cheng-Han; Chiu, Shih-Wen

2011-01-01

This study developed an electronic-nose sensor node based on a polymer-coated surface acoustic wave (SAW) sensor array. The sensor node comprised an SAW sensor array, a frequency readout circuit, and an Octopus II wireless module. The sensor array was fabricated on a large K2 128° YX LiNbO3 sensing substrate. On the surface of this substrate, an interdigital transducer (IDT) was produced with a Cr/Au film as its metallic structure. A mixed-mode frequency readout application specific integrated circuit (ASIC) was fabricated using a TSMC 0.18 μm process. The ASIC output was connected to a wireless module to transmit sensor data to a base station for data storage and analysis. This sensor node is applicable for wireless sensor network (WSN) applications. PMID:22163865

An electronic-nose sensor node based on a polymer-coated surface acoustic wave array for wireless sensor network applications.

PubMed

Tang, Kea-Tiong; Li, Cheng-Han; Chiu, Shih-Wen

2011-01-01

This study developed an electronic-nose sensor node based on a polymer-coated surface acoustic wave (SAW) sensor array. The sensor node comprised an SAW sensor array, a frequency readout circuit, and an Octopus II wireless module. The sensor array was fabricated on a large K(2) 128° YX LiNbO3 sensing substrate. On the surface of this substrate, an interdigital transducer (IDT) was produced with a Cr/Au film as its metallic structure. A mixed-mode frequency readout application specific integrated circuit (ASIC) was fabricated using a TSMC 0.18 μm process. The ASIC output was connected to a wireless module to transmit sensor data to a base station for data storage and analysis. This sensor node is applicable for wireless sensor network (WSN) applications.

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

PubMed

Zenke, Friedemann; Ganguli, Surya

2018-06-01

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Beyond G-band : a 235 GHz InP MMIC amplifier

NASA Technical Reports Server (NTRS)

Dawson, Douglas; Samoska, Lorene; Fung, A. K.; Lee, Karen; Lai, Richard; Grundbacher, Ronald; Liu, Po-Hsin; Raja, Rohit

2005-01-01

We present results on an InP monolithic millimeter- wave integrated circuit (MMIC) amplifier having 10-dB gain at 235 GHz. We designed this circuit and fabricated the chip in Northrop Grumman Space Technology's (NGST) 0.07- m InP high electron mobility transistor (HEMT) process. Using a WR3 (220-325 GHz) waveguide vector network analyzer system interfaced to waveguide wafer probes, we measured this chip on-wafer for -parameters. To our knowledge, this is the first time a WR3 waveguide on-wafer measurement system has been used to measure gain in a MMIC amplifier above 230 GHz.

Making sense out of spinal cord somatosensory development

PubMed Central

Seal, Rebecca P.

2016-01-01

The spinal cord integrates and relays somatosensory input, leading to complex motor responses. Research over the past couple of decades has identified transcription factor networks that function during development to define and instruct the generation of diverse neuronal populations within the spinal cord. A number of studies have now started to connect these developmentally defined populations with their roles in somatosensory circuits. Here, we review our current understanding of how neuronal diversity in the dorsal spinal cord is generated and we discuss the logic underlying how these neurons form the basis of somatosensory circuits. PMID:27702783

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.

Recent advances in superconducting-mixer simulations

NASA Technical Reports Server (NTRS)

Withington, S.; Kennedy, P. R.

1992-01-01

Over the last few years, considerable progress have been made in the development of techniques for fabricating high-quality superconducting circuits, and this success, together with major advances in the theoretical understanding of quantum detection and mixing at millimeter and submillimeter wavelengths, has made the development of CAD techniques for superconducting nonlinear circuits an important new enterprise. For example, arrays of quasioptical mixers are now being manufactured, where the antennas, matching networks, filters and superconducting tunnel junctions are all fabricated by depositing niobium and a variety of oxides on a single quartz substrate. There are no adjustable tuning elements on these integrated circuits, and therefore, one must be able to predict their electrical behavior precisely. This requirement, together with a general interest in the generic behavior of devices such as direct detectors and harmonic mixers, has lead us to develop a range of CAD tools for simulating the large-signal, small-signal, and noise behavior of superconducting tunnel junction circuits.

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

PubMed Central

Berényi, Antal; Somogyvári, Zoltán; Nagy, Anett J.; Roux, Lisa; Long, John D.; Fujisawa, Shigeyoshi; Stark, Eran; Leonardo, Anthony; Harris, Timothy D.

2013-01-01

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function. PMID:24353300

Architectures and Design for Next-Generation Hybrid Circuit/Packet Networks

NASA Astrophysics Data System (ADS)

Vadrevu, Sree Krishna Chaitanya

Internet traffic is increasing rapidly at an annual growth rate of 35% with aggregate traffic exceeding several Exabyte's per month. The traffic is also becoming heterogeneous in bandwidth and quality-of-service (QoS) requirements with growing popularity of cloud computing, video-on-demand (VoD), e-science, etc. Hybrid circuit/packet networks which can jointly support circuit and packet services along with the adoption of high-bit-rate transmission systems form an attractive solution to address the traffic growth. 10 Gbps and 40 Gbps transmission systems are widely deployed in telecom backbone networks such as Comcast, AT&T, etc., and network operators are considering migration to 100 Gbps and beyond. This dissertation proposes robust architectures, capacity migration strategies, and novel service frameworks for next-generation hybrid circuit/packet architectures. In this dissertation, we study two types of hybrid circuit/packet networks: a) IP-over-WDM networks, in which the packet (IP) network is overlaid on top of the circuit (optical WDM) network and b) Hybrid networks in which the circuit and packet networks are deployed side by side such as US DoE's ESnet. We investigate techniques to dynamically migrate capacity between the circuit and packet sections by exploiting traffic variations over a day, and our methods show that significant bandwidth savings can be obtained with improved reliability of services. Specifically, we investigate how idle backup circuit capacity can be used to support packet services in IP-over-WDM networks, and similarly, excess capacity in packet network to support circuit services in ESnet. Control schemes that enable our mechanisms are also discussed. In IP-over-WDM networks, with upcoming 100 Gbps and beyond, dedicated protection will induce significant under-utilization of backup resources. We investigate design strategies to loan idle circuit backup capacity to support IP/packet services. However, failure of backup circuits will preempt IP services routed over them, and thus it is important to ensure IP topology survivability to successfully re-route preempted IP services. Integer-linear-program (ILP) and heuristic solutions have been developed and network cost reduction up to 60% has been observed. In ESnet, we study loaning packet links to support circuit services. Mixed-line-rate (MLR) networks supporting 10/40/100 Gbps on the same fiber are becoming increasingly popular. Services that accept degradation in bandwidth, latency, jitter, etc. under failure scenarios for lower cost are known as degraded services. We study degradation in bandwidth for lower cost under failure scenarios, a concept called partial protection, in the context of MLR networks. We notice partial protection enables significant cost savings compared to full protection. To cope with traffic growth, network operators need to deploy equipment at periodic time intervals, and this is known as the multi-period planning and upgrade problem. We study three important multi-period planning approaches, namely incremental planning, all-period planning, and two-period planning with mixed line rates. Our approaches predict the network equipment that needs to be deployed optimally at which nodes and at which time periods in the network to meet QoS requirements.

Deterministic Integration of Quantum Dots into on-Chip Multimode Interference Beamsplitters Using in Situ Electron Beam Lithography

NASA Astrophysics Data System (ADS)

Schnauber, Peter; Schall, Johannes; Bounouar, Samir; Höhne, Theresa; Park, Suk-In; Ryu, Geun-Hwan; Heindel, Tobias; Burger, Sven; Song, Jin-Dong; Rodt, Sven; Reitzenstein, Stephan

2018-04-01

The development of multi-node quantum optical circuits has attracted great attention in recent years. In particular, interfacing quantum-light sources, gates and detectors on a single chip is highly desirable for the realization of large networks. In this context, fabrication techniques that enable the deterministic integration of pre-selected quantum-light emitters into nanophotonic elements play a key role when moving forward to circuits containing multiple emitters. Here, we present the deterministic integration of an InAs quantum dot into a 50/50 multi-mode interference beamsplitter via in-situ electron beam lithography. We demonstrate the combined emitter-gate interface functionality by measuring triggered single-photon emission on-chip with $g^{(2)}(0) = 0.13\\pm 0.02$. Due to its high patterning resolution as well as spectral and spatial control, in-situ electron beam lithography allows for integration of pre-selected quantum emitters into complex photonic systems. Being a scalable single-step approach, it paves the way towards multi-node, fully integrated quantum photonic chips.

Gene Circuit Analysis of the Terminal Gap Gene huckebein

PubMed Central

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-01-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

Gene circuit analysis of the terminal gap gene huckebein.

PubMed

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-10-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.

Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch.

PubMed

Blanchard, Andrew E; Liao, Chen; Lu, Ting

2018-02-06

Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit's architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm-integrated modeling of the circuit-host system-for quantitative understanding of engineered gene networks. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Mechanically Flexible and High-Performance CMOS Logic Circuits.

PubMed

Honda, Wataru; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2015-10-13

Low-power flexible logic circuits are key components required by the next generation of flexible electronic devices. For stable device operation, such components require a high degree of mechanical flexibility and reliability. Here, the mechanical properties of low-power flexible complementary metal-oxide-semiconductor (CMOS) logic circuits including inverter, NAND, and NOR are investigated. To fabricate CMOS circuits on flexible polyimide substrates, carbon nanotube (CNT) network films are used for p-type transistors, whereas amorphous InGaZnO films are used for the n-type transistors. The power consumption and voltage gain of CMOS inverters are <500 pW/mm at Vin = 0 V (<7.5 nW/mm at Vin = 5 V) and >45, respectively. Importantly, bending of the substrate is not found to cause significant changes in the device characteristics. This is also observed to be the case for more complex flexible NAND and NOR logic circuits for bending states with a curvature radius of 2.6 mm. The mechanical stability of these CMOS logic circuits makes them ideal candidates for use in flexible integrated devices.

Mechanically Flexible and High-Performance CMOS Logic Circuits

PubMed Central

Honda, Wataru; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2015-01-01

Low-power flexible logic circuits are key components required by the next generation of flexible electronic devices. For stable device operation, such components require a high degree of mechanical flexibility and reliability. Here, the mechanical properties of low-power flexible complementary metal–oxide–semiconductor (CMOS) logic circuits including inverter, NAND, and NOR are investigated. To fabricate CMOS circuits on flexible polyimide substrates, carbon nanotube (CNT) network films are used for p-type transistors, whereas amorphous InGaZnO films are used for the n-type transistors. The power consumption and voltage gain of CMOS inverters are <500 pW/mm at Vin = 0 V (<7.5 nW/mm at Vin = 5 V) and >45, respectively. Importantly, bending of the substrate is not found to cause significant changes in the device characteristics. This is also observed to be the case for more complex flexible NAND and NOR logic circuits for bending states with a curvature radius of 2.6 mm. The mechanical stability of these CMOS logic circuits makes them ideal candidates for use in flexible integrated devices. PMID:26459882

Fast Neural Solution Of A Nonlinear Wave Equation

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Toomarian, Nikzad

1996-01-01

Neural algorithm for simulation of class of nonlinear wave phenomena devised. Numerically solves special one-dimensional case of Korteweg-deVries equation. Intended to be executed rapidly by neural network implemented as charge-coupled-device/charge-injection device, very-large-scale integrated-circuit analog data processor of type described in "CCD/CID Processors Would Offer Greater Precision" (NPO-18972).

Vulnerability-Based Critical Neurons, Synapses, and Pathways in the Caenorhabditis elegans Connectome

PubMed Central

Kim, Seongkyun; Kim, Hyoungkyu; Kralik, Jerald D.; Jeong, Jaeseung

2016-01-01

Determining the fundamental architectural design of complex nervous systems will lead to significant medical and technological advances. Yet it remains unclear how nervous systems evolved highly efficient networks with near optimal sharing of pathways that yet produce multiple distinct behaviors to reach the organism’s goals. To determine this, the nematode roundworm Caenorhabditis elegans is an attractive model system. Progress has been made in delineating the behavioral circuits of the C. elegans, however, many details are unclear, including the specific functions of every neuron and synapse, as well as the extent the behavioral circuits are separate and parallel versus integrative and serial. Network analysis provides a normative approach to help specify the network design. We investigated the vulnerability of the Caenorhabditis elegans connectome by performing computational experiments that (a) “attacked” 279 individual neurons and 2,990 weighted synaptic connections (composed of 6,393 chemical synapses and 890 electrical junctions) and (b) quantified the effects of each removal on global network properties that influence information processing. The analysis identified 12 critical neurons and 29 critical synapses for establishing fundamental network properties. These critical constituents were found to be control elements—i.e., those with the most influence over multiple underlying pathways. Additionally, the critical synapses formed into circuit-level pathways. These emergent pathways provide evidence for (a) the importance of backward locomotion, avoidance behavior, and social feeding behavior to the organism; (b) the potential roles of specific neurons whose functions have been unclear; and (c) both parallel and serial design elements in the connectome—i.e., specific evidence for a mixed architectural design. PMID:27540747

Diagnostic layer integration in FPGA-based pipeline measurement systems for HEP experiments

NASA Astrophysics Data System (ADS)

Pozniak, Krzysztof T.

2007-08-01

Integrated triggering and data acquisition systems for high energy physics experiments may be considered as fast, multichannel, synchronous, distributed, pipeline measurement systems. A considerable extension of functional, technological and monitoring demands, which has recently been imposed on them, forced a common usage of large field-programmable gate array (FPGA), digital signal processing-enhanced matrices and fast optical transmission for their realization. This paper discusses modelling, design, realization and testing of pipeline measurement systems. A distribution of synchronous data stream flows is considered in the network. A general functional structure of a single network node is presented. A suggested, novel block structure of the node model facilitates full implementation in the FPGA chip, circuit standardization and parametrization, as well as integration of functional and diagnostic layers. A general method for pipeline system design was derived. This method is based on a unified model of the synchronous data network node. A few examples of practically realized, FPGA-based, pipeline measurement systems were presented. The described systems were applied in ZEUS and CMS.

SDN-NGenIA, a software defined next generation integrated architecture for HEP and data intensive science

NASA Astrophysics Data System (ADS)

Balcas, J.; Hendricks, T. W.; Kcira, D.; Mughal, A.; Newman, H.; Spiropulu, M.; Vlimant, J. R.

2017-10-01

The SDN Next Generation Integrated Architecture (SDN-NGeNIA) project addresses some of the key challenges facing the present and next generations of science programs in HEP, astrophysics, and other fields, whose potential discoveries depend on their ability to distribute, process and analyze globally distributed Petascale to Exascale datasets. The SDN-NGenIA system under development by Caltech and partner HEP and network teams is focused on the coordinated use of network, computing and storage infrastructures, through a set of developments that build on the experience gained in recently completed and previous projects that use dynamic circuits with bandwidth guarantees to support major network flows, as demonstrated across LHC Open Network Environment [1] and in large scale demonstrations over the last three years, and recently integrated with PhEDEx and Asynchronous Stage Out data management applications of the CMS experiment at the Large Hadron Collider. In addition to the general program goals of supporting the network needs of the LHC and other science programs with similar needs, a recent focus is the use of the Leadership HPC facility at Argonne National Lab (ALCF) for data intensive applications.

Silicon-Germanium Films Grown on Sapphire for Ka-Band Communications Applications

NASA Technical Reports Server (NTRS)

Alterovitz, Samuel A.; Mueller, Carl H.; Croke, Edward T.

2004-01-01

NASA's vision in the space communications area is to develop a broadband data network in which there is a high degree of interconnectivity among the various satellite systems, ground stations, and wired systems. To accomplish this goal, we will need complex electronic circuits integrating analog and digital data handling at the Ka-band (26 to 40 GHz). The purpose of this project is to show the feasibility of a new technology for Ka-band communications applications, namely silicon germanium (SiGe) on sapphire. This new technology will have several advantages in comparison to the existing silicon-substrate- based circuits. The main advantages are extremely low parasitic reactances that enable much higher quality active and passive components, better device isolation, higher radiation tolerance, and the integration of digital and analog circuitry on a single chip.

Ultrascalable petaflop parallel supercomputer

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

A robust low-rate coding scheme for packet video

NASA Technical Reports Server (NTRS)

Chen, Y. C.; Sayood, Khalid; Nelson, D. J.; Arikan, E. (Editor)

1991-01-01

Due to the rapidly evolving field of image processing and networking, video information promises to be an important part of telecommunication systems. Although up to now video transmission has been transported mainly over circuit-switched networks, it is likely that packet-switched networks will dominate the communication world in the near future. Asynchronous transfer mode (ATM) techniques in broadband-ISDN can provide a flexible, independent and high performance environment for video communication. For this paper, the network simulator was used only as a channel in this simulation. Mixture blocking coding with progressive transmission (MBCPT) has been investigated for use over packet networks and has been found to provide high compression rate with good visual performance, robustness to packet loss, tractable integration with network mechanics and simplicity in parallel implementation.

Neural network pattern recognition of thermal-signature spectra for chemical defense

NASA Astrophysics Data System (ADS)

Carrieri, Arthur H.; Lim, Pascal I.

1995-05-01

We treat infrared patterns of absorption or emission by nerve and blister agent compounds (and simulants of this chemical group) as features for the training of neural networks to detect the compounds' liquid layers on the ground or their vapor plumes during evaporation by external heating. Training of a four-layer network architecture is composed of a backward-error-propagation algorithm and a gradient-descent paradigm. We conduct testing by feed-forwarding preprocessed spectra through the network in a scaled format consistent with the structure of the training-data-set representation. The best-performance weight matrix (spectral filter) evolved from final network training and testing with software simulation trials is electronically transferred to a set of eight artificial intelligence integrated circuits (ICs') in specific modular form (splitting of weight matrices). This form makes full use of all input-output IC nodes. This neural network computer serves an important real-time detection function when it is integrated into pre-and postprocessing data-handling units of a tactical prototype thermoluminescence sensor now under development at the Edgewood Research, Development, and Engineering Center.

Effects of Distributed Generation on Overcurrent Relay Coordination and an Adaptive Protection Scheme

NASA Astrophysics Data System (ADS)

Ilik, Semih C.; Arsoy, Aysen B.

2017-07-01

Integration of distributed generation (DG) such as renewable energy sources to electrical network becomes more prevalent in recent years. Grid connection of DG has effects on load flow directions, voltage profile, short circuit power and especially protection selectivity. Applying traditional overcurrent protection scheme is inconvenient when system reliability and sustainability are considered. If a fault happens in DG connected network, short circuit contribution of DG, creates additional branch element feeding the fault current; compels to consider directional overcurrent (OC) protection scheme. Protection coordination might get lost for changing working conditions when DG sources are connected. Directional overcurrent relay parameters are determined for downstream and upstream relays when different combinations of DG connected singular or plural, on radial test system. With the help of proposed flow chart, relay parameters are updated and coordination between relays kept sustained for different working conditions in DigSILENT PowerFactory program.

Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability

PubMed Central

Wei, Luqing; Chen, Hong; Wu, Guo-Rong

2018-01-01

The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability. PMID:29545744

Millimeter And Submillimeter-Wave Integrated Circuits On Quartz

NASA Technical Reports Server (NTRS)

Mehdi, Imran; Mazed, Mohammad; Siegel, Peter; Smith, R. Peter

1995-01-01

Proposed Quartz substrate Upside-down Integrated Device (QUID) relies on UV-curable adhesive to bond semiconductor with quartz. Integrated circuits including planar GaAs Schottky diodes and passive circuit elements (such as bandpass filters) fabricated on quartz substrates. Circuits designed to operate as mixers in waveguide circuit at millimeter and submillimeter wavelengths. Integrated circuits mechanically more robust, larger, and easier to handle than planar Schottky diode chips. Quartz substrate more suitable for waveguide circuits than GaAs substrate.

SIFamide Translates Hunger Signals into Appetitive and Feeding Behavior in Drosophila.

PubMed

Martelli, Carlotta; Pech, Ulrike; Kobbenbring, Simon; Pauls, Dennis; Bahl, Britta; Sommer, Mirjam Vanessa; Pooryasin, Atefeh; Barth, Jonas; Arias, Carmina Warth Perez; Vassiliou, Chrystalleni; Luna, Abud Jose Farca; Poppinga, Haiko; Richter, Florian Gerhard; Wegener, Christian; Fiala, André; Riemensperger, Thomas

2017-07-11

Animal behavior is, on the one hand, controlled by neuronal circuits that integrate external sensory stimuli and induce appropriate motor responses. On the other hand, stimulus-evoked or internally generated behavior can be influenced by motivational conditions, e.g., the metabolic state. Motivational states are determined by physiological parameters whose homeostatic imbalances are signaled to and processed within the brain, often mediated by modulatory peptides. Here, we investigate the regulation of appetitive and feeding behavior in the fruit fly, Drosophila melanogaster. We report that four neurons in the fly brain that release SIFamide are integral elements of a complex neuropeptide network that regulates feeding. We show that SIFamidergic cells integrate feeding stimulating (orexigenic) and feeding suppressant (anorexigenic) signals to appropriately sensitize sensory circuits, promote appetitive behavior, and enhance food intake. Our study advances the cellular dissection of evolutionarily conserved signaling pathways that convert peripheral metabolic signals into feeding-related behavior. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Functional Interactions between Newborn and Mature Neurons Leading to Integration into Established Neuronal Circuits.

PubMed

Boulanger-Weill, Jonathan; Candat, Virginie; Jouary, Adrien; Romano, Sebastián A; Pérez-Schuster, Verónica; Sumbre, Germán

2017-06-19

From development up to adulthood, the vertebrate brain is continuously supplied with newborn neurons that integrate into established mature circuits. However, how this process is coordinated during development remains unclear. Using two-photon imaging, GCaMP5 transgenic zebrafish larvae, and sparse electroporation in the larva's optic tectum, we monitored spontaneous and induced activity of large neuronal populations containing newborn and functionally mature neurons. We observed that the maturation of newborn neurons is a 4-day process. Initially, newborn neurons showed undeveloped dendritic arbors, no neurotransmitter identity, and were unresponsive to visual stimulation, although they displayed spontaneous calcium transients. Later on, newborn-labeled neurons began to respond to visual stimuli but in a very variable manner. At the end of the maturation period, newborn-labeled neurons exhibited visual tuning curves (spatial receptive fields and direction selectivity) and spontaneous correlated activity with neighboring functionally mature neurons. At this developmental stage, newborn-labeled neurons presented complex dendritic arbors and neurotransmitter identity (excitatory or inhibitory). Removal of retinal inputs significantly perturbed the integration of newborn neurons into the functionally mature tectal network. Our results provide a comprehensive description of the maturation of newborn neurons during development and shed light on potential mechanisms underlying their integration into a functionally mature neuronal circuit. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Algorithms and architecture for multiprocessor based circuit simulation

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

Deutsch, J.T.

Accurate electrical simulation is critical to the design of high performance integrated circuits. Logic simulators can verify function and give first-order timing information. Switch level simulators are more effective at dealing with charge sharing than standard logic simulators, but cannot provide accurate timing information or discover DC problems. Delay estimation techniques and cell level simulation can be used in constrained design methods, but must be tuned for each application, and circuit simulation must still be used to generate the cell models. None of these methods has the guaranteed accuracy that many circuit designers desire, and none can provide detailed waveformmore » information. Detailed electrical-level simulation can predict circuit performance if devices and parasitics are modeled accurately. However, the computational requirements of conventional circuit simulators make it impractical to simulate current large circuits. In this dissertation, the implementation of Iterated Timing Analysis (ITA), a relaxation-based technique for accurate circuit simulation, on a special-purpose multiprocessor is presented. The ITA method is an SOR-Newton, relaxation-based method which uses event-driven analysis and selective trace to exploit the temporal sparsity of the electrical network. Because event-driven selective trace techniques are employed, this algorithm lends itself to implementation on a data-driven computer.« less

Soldering Tool for Integrated Circuits

NASA Technical Reports Server (NTRS)

Takahashi, Ted H.

1987-01-01

Many connections soldered simultaneously in confined spaces. Improved soldering tool bonds integrated circuits onto printed-circuit boards. Intended especially for use with so-called "leadless-carrier" integrated circuits.

Optical MEMS platform for low-cost on-chip integration of planar light circuits and optical switching

NASA Astrophysics Data System (ADS)

German, Kristine A.; Kubby, Joel; Chen, Jingkuang; Diehl, James; Feinberg, Kathleen; Gulvin, Peter; Herko, Larry; Jia, Nancy; Lin, Pinyen; Liu, Xueyuan; Ma, Jun; Meyers, John; Nystrom, Peter; Wang, Yao Rong

2004-07-01

Xerox Corporation has developed a technology platform for on-chip integration of latching MEMS optical waveguide switches and Planar Light Circuit (PLC) components using a Silicon On Insulator (SOI) based process. To illustrate the current state of this new technology platform, working prototypes of a Reconfigurable Optical Add/Drop Multiplexer (ROADM) and a l-router will be presented along with details of the integrated latching MEMS optical switches. On-chip integration of optical switches and PLCs can greatly reduce the size, manufacturing cost and operating cost of multi-component optical equipment. It is anticipated that low-cost, low-overhead optical network products will accelerate the migration of functions and services from high-cost long-haul markets to price sensitive markets, including networks for metropolitan areas and fiber to the home. Compared to the more common silica-on-silicon PLC technology, the high index of refraction of silicon waveguides created in the SOI device layer enables miniaturization of optical components, thereby increasing yield and decreasing cost projections. The latching SOI MEMS switches feature moving waveguides, and are advantaged across multiple attributes relative to alternative switching technologies, such as thermal optical switches and polymer switches. The SOI process employed was jointly developed under the auspice of the NIST APT program in partnership with Coventor, Corning IntelliSense Corp., and MicroScan Systems to enable fabrication of a broad range of free space and guided wave MicroOptoElectroMechanical Systems (MOEMS).

The 1991 3rd NASA Symposium on VLSI Design

NASA Technical Reports Server (NTRS)

Maki, Gary K.

1991-01-01

Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2.

vPELS: An E-Learning Social Environment for VLSI Design with Content Security Using DRM

ERIC Educational Resources Information Center

Dewan, Jahangir; Chowdhury, Morshed; Batten, Lynn

2014-01-01

This article provides a proposal for personal e-learning system (vPELS [where "v" stands for VLSI: very large scale integrated circuit])) architecture in the context of social network environment for VLSI Design. The main objective of vPELS is to develop individual skills on a specific subject--say, VLSI--and share resources with peers.…

Motor cognition-motor semantics: action perception theory of cognition and communication.

PubMed

Pulvermüller, Friedemann; Moseley, Rachel L; Egorova, Natalia; Shebani, Zubaida; Boulenger, Véronique

2014-03-01

A new perspective on cognition views cortical cell assemblies linking together knowledge about actions and perceptions not only as the vehicles of integrated action and perception processing but, furthermore, as a brain basis for a wide range of higher cortical functions, including attention, meaning and concepts, sequences, goals and intentions, and even communicative social interaction. This article explains mechanisms relevant to mechanistic action perception theory, points to concrete neuronal circuits in brains along with artificial neuronal network simulations, and summarizes recent brain imaging and other experimental data documenting the role of action perception circuits in cognition, language and communication. © 2013 Published by Elsevier Ltd.

Nanowires and nanoribbons as subwavelength optical waveguides and their use as components in photonic circuits and devices

DOEpatents

Yang, Peidong; Law, Matt; Sirbuly, Donald J.; Johnson, Justin C.; Saykally, Richard; Fan, Rong; Tao, Andrea

2012-10-02

Nanoribbons and nanowires having diameters less than the wavelength of light are used in the formation and operation of optical circuits and devices. Such nanostructures function as subwavelength optical waveguides which form a fundamental building block for optical integration. The extraordinary length, flexibility and strength of these structures enable their manipulation on surfaces, including the precise positioning and optical linking of nanoribbon/wire waveguides and other nanoribbon/wire elements to form optical networks and devices. In addition, such structures provide for waveguiding in liquids, enabling them to further be used in other applications such as optical probes and sensors.

Adaptive neuro fuzzy inference system-based power estimation method for CMOS VLSI circuits

NASA Astrophysics Data System (ADS)

Vellingiri, Govindaraj; Jayabalan, Ramesh

2018-03-01

Recent advancements in very large scale integration (VLSI) technologies have made it feasible to integrate millions of transistors on a single chip. This greatly increases the circuit complexity and hence there is a growing need for less-tedious and low-cost power estimation techniques. The proposed work employs Back-Propagation Neural Network (BPNN) and Adaptive Neuro Fuzzy Inference System (ANFIS), which are capable of estimating the power precisely for the complementary metal oxide semiconductor (CMOS) VLSI circuits, without requiring any knowledge on circuit structure and interconnections. The ANFIS to power estimation application is relatively new. Power estimation using ANFIS is carried out by creating initial FIS modes using hybrid optimisation and back-propagation (BP) techniques employing constant and linear methods. It is inferred that ANFIS with the hybrid optimisation technique employing the linear method produces better results in terms of testing error that varies from 0% to 0.86% when compared to BPNN as it takes the initial fuzzy model and tunes it by means of a hybrid technique combining gradient descent BP and mean least-squares optimisation algorithms. ANFIS is the best suited for power estimation application with a low RMSE of 0.0002075 and a high coefficient of determination (R) of 0.99961.

The Development of an IMU Integrated Clothes for Postural Monitoring Using Conductive Yarn and Interconnecting Technology.

PubMed

Kang, Sung-Won; Choi, Hyeob; Park, Hyung-Il; Choi, Byoung-Gun; Im, Hyobin; Shin, Dongjun; Jung, Young-Giu; Lee, Jun-Young; Park, Hong-Won; Park, Sukyung; Roh, Jung-Sim

2017-11-07

Spinal disease is a common yet important condition that occurs because of inappropriate posture. Prevention could be achieved by continuous posture monitoring, but most measurement systems cannot be used in daily life due to factors such as burdensome wires and large sensing modules. To improve upon these weaknesses, we developed comfortable "smart wear" for posture measurement using conductive yarn for circuit patterning and a flexible printed circuit board (FPCB) for interconnections. The conductive yarn was made by twisting polyester yarn and metal filaments, and the resistance per unit length was about 0.05 Ω/cm. An embroidered circuit was made using the conductive yarn, which showed increased yield strength and uniform electrical resistance per unit length. Circuit networks of sensors and FPCBs for interconnection were integrated into clothes using a computer numerical control (CNC) embroidery process. The system was calibrated and verified by comparing the values measured by the smart wear with those measured by a motion capture camera system. Six subjects performed fixed movements and free computer work, and, with this system, we were able to measure the anterior/posterior direction tilt angle with an error of less than 4°. The smart wear does not have excessive wires, and its structure will be optimized for better posture estimation in a later study.

Three-Dimensional Flexible Complementary Metal-Oxide-Semiconductor Logic Circuits Based On Two-Layer Stacks of Single-Walled Carbon Nanotube Networks.

PubMed

Zhao, Yudan; Li, Qunqing; Xiao, Xiaoyang; Li, Guanhong; Jin, Yuanhao; Jiang, Kaili; Wang, Jiaping; Fan, Shoushan

2016-02-23

We have proposed and fabricated stable and repeatable, flexible, single-walled carbon nanotube (SWCNT) thin film transistor (TFT) complementary metal-oxide-semiconductor (CMOS) integrated circuits based on a three-dimensional (3D) structure. Two layers of SWCNT-TFT devices were stacked, where one layer served as n-type devices and the other one served as p-type devices. On the basis of this method, it is able to save at least half of the area required to construct an inverter and make large-scale and high-density integrated CMOS circuits easier to design and manufacture. The 3D flexible CMOS inverter gain can be as high as 40, and the total noise margin is more than 95%. Moreover, the input and output voltage of the inverter are exactly matched for cascading. 3D flexible CMOS NOR, NAND logic gates, and 15-stage ring oscillators were fabricated on PI substrates with high performance as well. Stable electrical properties of these circuits can be obtained with bending radii as small as 3.16 mm, which shows that such a 3D structure is a reliable architecture and suitable for carbon nanotube electrical applications in complex flexible and wearable electronic devices.

Thermally-isolated silicon-based integrated circuits and related methods

DOEpatents

Wojciechowski, Kenneth; Olsson, Roy H.; Clews, Peggy J.; Bauer, Todd

2017-05-09

Thermally isolated devices may be formed by performing a series of etches on a silicon-based substrate. As a result of the series of etches, silicon material may be removed from underneath a region of an integrated circuit (IC). The removal of the silicon material from underneath the IC forms a gap between remaining substrate and the integrated circuit, though the integrated circuit remains connected to the substrate via a support bar arrangement that suspends the integrated circuit over the substrate. The creation of this gap functions to release the device from the substrate and create a thermally-isolated integrated circuit.

Nuevas tecnicas basadas en redes neuronales para el diseno de filtros de microondas multicapa apantallados

NASA Astrophysics Data System (ADS)

Pascual Garcia, Juan

In this PhD thesis one method of shielded multilayer circuit neural network based analysis has been developed. One of the most successful analysis procedures of these kind of structures is the Integral Equation technique (IE) solved by the Method of Moments (MoM). In order to solve the IE, in the version which uses the media relevant potentials, it is necessary to have a formulation of the Green's functions associated to the mentioned potentials. The main computational burden in the IE resolution lies on the numerical evaluation of the Green's functions. In this work, the circuit analysis has been drastically accelerated thanks to the approximation of the Green's functions by means of neural networks. Once trained, the neural networks substitute the Green's functions in the IE. Two different types of neural networks have been used: the Radial basis function neural networks (RBFNN) and the Chebyshev neural networks. Thanks mainly to two distinct operations the correct approximation of the Green's functions has been possible. On the one hand, a very effective input space division has been developed. On the other hand, the elimination of the singularity makes feasible the approximation of slow variation functions. Two different singularity elimination strategies have been developed. The first one is based on the multiplication by the source-observation points distance (rho). The second one outperforms the first one. It consists of the extraction of two layers of spatial images from the whole summation of images. With regard to the Chebyshev neural networks, the OLS training algorithm has been applied in a novel fashion. This method allows the optimum design in this kind of neural networks. In this way, the performance of these neural networks outperforms greatly the RBFNNs one. In both networks, the time gain reached makes the neural method profitable. The time invested in the input space division and in the neural training is negligible with only few circuit analysis. To show, in a practical way, the ability of the neural based analysis method, two new design procedures have been developed. The first method uses the Genetic Algorithms to optimize an initial filter which does not fulfill the established specifications. A new fitness function, specially well suited to design filters, has been defined in order to assure the correct convergence of the optimization process. This new function measures the fulfillment of the specifications and it also prevents the appearance of the premature convergence problem. The second method is found on the approximation, by means of neural networks, of the relations between the electrical parameters, which defined the circuit response, and the physical dimensions that synthesize the aforementioned parameters. The neural networks trained with these data can be used in the design of many circuits in a given structure. Both methods had been show their ability in the design of practical filters.

Integrated system for remotely monitoring critical physiological parameters

NASA Astrophysics Data System (ADS)

Alexakis, S.; Karalis, S.; Asvestas, P.

2015-09-01

Monitoring several human parameters (temperature, heart rate, blood pressure etc.) is an essential task in health care in hospitals as well as in home care. This paper presents the design and implementation of an integrated, embedded system that includes an electrocardiograph of nine leads and two channels, a digital thermometer for measuring the body temperature and a power supply. The system provides networking capabilities (wired or wireless) and is accessible by means of a web interface that allows the user to select the leads, as well as to review the values of heart rate (beats per minute) and body temperature. Furthermore, there is the option of saving all the data in a Micro SD memory card or in a Google Spreadsheet. The necessary analog circuits for signal conditioning (amplification and filtering) were manufactured on printed circuit boards (PCB). The system was built around Arduino Yun, which is a platform that contains a microcontroller and a microprocessor running a special LINUX distribution. Furthermore, the Arduino Yun provides the necessary network connectivity capabilities by means of the integrated Wi-Fi and Ethernet interfaces. The web interface was developed using HTML pages with JavaScript support. The system was tested on simulated data as well as real data, providing satisfactory accuracy regarding the measurement of the heart rate (±3 bpm error) and the temperature (±0.3°C error).

CMOL: A New Concept for Nanoelectronics

NASA Astrophysics Data System (ADS)

Likharev, Konstantin

2005-03-01

I will review the recent work on devices and architectures for future hybrid semiconductor/molecular integrated circuits, in particular those of ``CMOL'' variety [1]. Such circuits would combine an advanced CMOS subsystem fabricated by the usual lithographic patterning, two layers of parallel metallic nanowires formed, e.g., by nanoimprint, and two-terminal molecular devices self-assembled on the nanowire crosspoints. Estimates show that this powerful combination may allow CMOL circuits to reach an unparalleled density (up to 10^12 functions per cm^2) and ultrahigh rate of information processing (up to 10^20 operations per second on a single chip), at acceptable power dissipation. The main challenges on the way toward practical CMOL technology are: (i) reliable chemically-directed self-assembly of mid-size organic molecules, and (ii) the development of efficient defect-tolerant architectures for CMOL circuits. Our recent work has shown that such architectures may be developed not only for terabit-scale memories and naturally defect-tolerant mixed-signal neuromorphic networks, but (rather unexpectedly) also for FPGA-style digital Boolean circuits. [1] For details, see http://rsfq1.physics.sunysb.edu/˜likharev/nano/Springer04.pdf

Reverse Engineering Validation using a Benchmark Synthetic Gene Circuit in Human Cells

PubMed Central

Kang, Taek; White, Jacob T.; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas

2013-01-01

Multi-component biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network. PMID:23654266

Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

PubMed

Kang, Taek; White, Jacob T; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas

2013-05-17

Multicomponent biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network.

19 CFR 10.14 - Fabricated components subject to the exemption.

Code of Federal Regulations, 2010 CFR

2010-04-01

... assembled, such as transistors, diodes, integrated circuits, machinery parts, or precut parts of wearing..., or integrated circuit wafers containing individual integrated circuit dice which have been scribed or... resulted in a substantial transformation of the foreign copper ingots. Example 2. An integrated circuit...

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study

PubMed Central

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

PubMed

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

Targeting circuits

PubMed Central

Rajasethupathy, Priyamvada; Ferenczi, Emily; Deisseroth, Karl

2017-01-01

Current optogenetic methodology enables precise inhibition or excitation of neural circuits, spanning timescales as needed from the acute (milliseconds) to the chronic (many days or more), for experimental modulation of network activity and animal behavior. Such broad temporal versatility, unique to optogenetic control, is particularly powerful when combined with brain activity measurements that span both acute and chronic timescales as well. This enables, for instance, the study of adaptive circuit dynamics across the intact brain, and tuning interventions to match activity patterns naturally observed during behavior in the same individual. Although the impact of this approach has been greater on basic research than on clinical translation, it is natural to ask if specific neural circuit activity patterns discovered to be involved in controlling adaptive or maladaptive behaviors could become targets for treatment of neuropsychiatric diseases. Here we consider the landscape of such ideas related to therapeutic targeting of circuit dynamics, taking note of developments not only in optical but also in ultrasonic, magnetic, and thermal methods. We note the recent emergence of first-in-kind optogenetically-guided clinical outcomes, as well as opportunities related to the integration of interventions and readouts spanning diverse circuit-physiology, molecular, and behavioral modalities. PMID:27104976

Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment

PubMed Central

Peters, Sarah K.; Dunlop, Katharine; Downar, Jonathan

2016-01-01

The salience network (SN) plays a central role in cognitive control by integrating sensory input to guide attention, attend to motivationally salient stimuli and recruit appropriate functional brain-behavior networks to modulate behavior. Mounting evidence suggests that disturbances in SN function underlie abnormalities in cognitive control and may be a common etiology underlying many psychiatric disorders. Such functional and anatomical abnormalities have been recently apparent in studies and meta-analyses of psychiatric illness using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). Of particular importance, abnormal structure and function in major cortical nodes of the SN, the dorsal anterior cingulate cortex (dACC) and anterior insula (AI), have been observed as a common neurobiological substrate across a broad spectrum of psychiatric disorders. In addition to cortical nodes of the SN, the network’s associated subcortical structures, including the dorsal striatum, mediodorsal thalamus and dopaminergic brainstem nuclei, comprise a discrete regulatory loop circuit. The SN’s cortico-striato-thalamo-cortical loop increasingly appears to be central to mechanisms of cognitive control, as well as to a broad spectrum of psychiatric illnesses and their available treatments. Functional imbalances within the SN loop appear to impair cognitive control, and specifically may impair self-regulation of cognition, behavior and emotion, thereby leading to symptoms of psychiatric illness. Furthermore, treating such psychiatric illnesses using invasive or non-invasive brain stimulation techniques appears to modulate SN cortical-subcortical loop integrity, and these effects may be central to the therapeutic mechanisms of brain stimulation treatments in many psychiatric illnesses. Here, we review clinical and experimental evidence for abnormalities in SN cortico-striatal-thalamic loop circuits in major depression, substance use disorders (SUD), anxiety disorders, schizophrenia and eating disorders (ED). We also review emergent therapeutic evidence that novel invasive and non-invasive brain stimulation treatments may exert therapeutic effects by normalizing abnormalities in the SN loop, thereby restoring the capacity for cognitive control. Finally, we consider a series of promising directions for future investigations on the role of SN cortico-striatal-thalamic loop circuits in the pathophysiology and treatment of psychiatric disorders. PMID:28082874

Unfolding an electronic integrate-and-fire circuit.

PubMed

Carrillo, Humberto; Hoppensteadt, Frank

2010-01-01

Many physical and biological phenomena involve accumulation and discharge processes that can occur on significantly different time scales. Models of these processes have contributed to understand excitability self-sustained oscillations and synchronization in arrays of oscillators. Integrate-and-fire (I+F) models are popular minimal fill-and-flush mathematical models. They are used in neuroscience to study spiking and phase locking in single neuron membranes, large scale neural networks, and in a variety of applications in physics and electrical engineering. We show here how the classical first-order I+F model fits into the theory of nonlinear oscillators of van der Pol type by demonstrating that a particular second-order oscillator having small parameters converges in a singular perturbation limit to the I+F model. In this sense, our study provides a novel unfolding of such models and it identifies a constructible electronic circuit that is closely related to I+F.

The hybrid photonic planar integrated receiver with a polymer optical waveguide

NASA Astrophysics Data System (ADS)

Busek, Karel; Jerábek, Vitezslav; Armas Arciniega, Julio; Prajzler, Václav

2008-11-01

This article describes design of the photonic receiver composed of the system polymer planar waveguides, InGaAs p-i-n photodiode and integrated HBT amplifier on a low loss composite substrate. The photonic receiver was the main part of the hybrid integrated microwave optoelectronic transceiver TRx (transciever TRx) for the optical networks PON (passive optical networks) with FTTH (fiber-to-the-home) topology. In this article are presented the research results of threedimensional field between output facet of a optical waveguide and p-i-n photodiode. In terms of our research, there was optimized the optical coupling among the facet waveguide and pi-n photodiode and the electrical coupling among p-i-n photodiode and input of HBT amplifier. The hybrid planar lightwave circuit (PLC) of the transceiver TRx will be composed from a two parts - polymer optical waveguide including VHGT filter section and a optoelectronic microwave section.

Hippocampal and ventral medial prefrontal activation during retrieval-mediated learning supports novel inference.

PubMed

Zeithamova, Dagmar; Dominick, April L; Preston, Alison R

2012-07-12

Memory enables flexible use of past experience to inform new behaviors. Although leading theories hypothesize that this fundamental flexibility results from the formation of integrated memory networks relating multiple experiences, the neural mechanisms that support memory integration are not well understood. Here, we demonstrate that retrieval-mediated learning, whereby prior event details are reinstated during encoding of related experiences, supports participants' ability to infer relationships between distinct events that share content. Furthermore, we show that activation changes in a functionally coupled hippocampal and ventral medial prefrontal cortical circuit track the formation of integrated memories and successful inferential memory performance. These findings characterize the respective roles of these regions in retrieval-mediated learning processes that support relational memory network formation and inferential memory in the human brain. More broadly, these data reveal fundamental mechanisms through which memory representations are constructed into prospectively useful formats. Copyright © 2012 Elsevier Inc. All rights reserved.

Hippocampal and ventral medial prefrontal activation during retrieval-mediated learning supports novel inference

PubMed Central

Zeithamova, Dagmar; Dominick, April L.; Preston, Alison R.

2012-01-01

SUMMARY Memory enables flexible use of past experience to inform new behaviors. Though leading theories hypothesize that this fundamental flexibility results from the formation of integrated memory networks relating multiple experiences, the neural mechanisms that support memory integration are not well understood. Here, we demonstrate that retrieval-mediated learning, whereby prior event details are reinstated during encoding of related experiences, supports participants’ ability to infer relationships between distinct events that share content. Furthermore, we show that activation changes in a functionally coupled hippocampal and ventral medial prefrontal cortical circuit track the formation of integrated memories and successful inferential memory performance. These findings characterize the respective roles of these regions in retrieval-mediated learning processes that support relational memory network formation and inferential memory in the human brain. More broadly, these data reveal fundamental mechanisms through which memory representations are constructed into prospectively useful formats. PMID:22794270

Engineering genetic circuit interactions within and between synthetic minimal cells

NASA Astrophysics Data System (ADS)

Adamala, Katarzyna P.; Martin-Alarcon, Daniel A.; Guthrie-Honea, Katriona R.; Boyden, Edward S.

2017-05-01

Genetic circuits and reaction cascades are of great importance for synthetic biology, biochemistry and bioengineering. An open question is how to maximize the modularity of their design to enable the integration of different reaction networks and to optimize their scalability and flexibility. One option is encapsulation within liposomes, which enables chemical reactions to proceed in well-isolated environments. Here we adapt liposome encapsulation to enable the modular, controlled compartmentalization of genetic circuits and cascades. We demonstrate that it is possible to engineer genetic circuit-containing synthetic minimal cells (synells) to contain multiple-part genetic cascades, and that these cascades can be controlled by external signals as well as inter-liposomal communication without crosstalk. We also show that liposomes that contain different cascades can be fused in a controlled way so that the products of incompatible reactions can be brought together. Synells thus enable a more modular creation of synthetic biology cascades, an essential step towards their ultimate programmability.

Lithographically fabricated gold nanowire waveguides for plasmonic routers and logic gates.

PubMed

Gao, Long; Chen, Li; Wei, Hong; Xu, Hongxing

2018-06-14

Fabricating plasmonic nanowire waveguides and circuits by lithographic fabrication methods is highly desired for nanophotonic circuitry applications. Here we report an approach for fabricating metal nanowire networks by using electron beam lithography and metal film deposition techniques. The gold nanowire structures are fabricated on quartz substrates without using any adhesion layer but coated with a thin layer of Al2O3 film for immobilization. The thermal annealing during the Al2O3 deposition process decreases the surface plasmon loss. In a Y-shaped gold nanowire network, the surface plasmons can be routed to different branches by controlling the polarization of the excitation light, and the routing behavior is dependent on the length of the main nanowire. Simulated electric field distributions show that the zigzag distribution of the electric field in the nanowire network determines the surface plasmon routing. By using two laser beams to excite surface plasmons in a Y-shaped nanowire network, the output intensity can be modulated by the interference of surface plasmons, which can be used to design Boolean logic gates. We experimentally demonstrate that AND, OR, XOR and NOT gates can be realized in three-terminal nanowire networks, and NAND, NOR and XNOR gates can be realized in four-terminal nanowire networks. This work takes a step toward the fabrication of on-chip integrated plasmonic circuits.

Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers

NASA Astrophysics Data System (ADS)

Ho, Ching S.; Liou, Juin J.; Georgiopoulos, Michael; Christodoulou, Christos G.

1994-03-01

This paper presents an analog circuit design and implementation for an adaptive resonance theory neural network architecture called the augmented ART1 neural network (AART1-NN). Practical monolithic operational amplifiers (Op-Amps) LM741 and LM318 are selected to implement the circuit, and a simple compensation scheme is developed to adjust the Op-Amp electrical characteristics to meet the design requirement. A 7-node prototype circuit has been designed and verified using the Pspice circuit simulator run on a Sun workstation. Results simulated from the AART1-NN circuit using the LM741, LM318, and ideal Op-Amps are presented and compared.

Molecular Signaling Network Motifs Provide a Mechanistic Basis for Cellular Threshold Responses

PubMed Central

Bhattacharya, Sudin; Conolly, Rory B.; Clewell, Harvey J.; Kaminski, Norbert E.; Andersen, Melvin E.

2014-01-01

Background: Increasingly, there is a move toward using in vitro toxicity testing to assess human health risk due to chemical exposure. As with in vivo toxicity testing, an important question for in vitro results is whether there are thresholds for adverse cellular responses. Empirical evaluations may show consistency with thresholds, but the main evidence has to come from mechanistic considerations. Objectives: Cellular response behaviors depend on the molecular pathway and circuitry in the cell and the manner in which chemicals perturb these circuits. Understanding circuit structures that are inherently capable of resisting small perturbations and producing threshold responses is an important step towards mechanistically interpreting in vitro testing data. Methods: Here we have examined dose–response characteristics for several biochemical network motifs. These network motifs are basic building blocks of molecular circuits underpinning a variety of cellular functions, including adaptation, homeostasis, proliferation, differentiation, and apoptosis. For each motif, we present biological examples and models to illustrate how thresholds arise from specific network structures. Discussion and Conclusion: Integral feedback, feedforward, and transcritical bifurcation motifs can generate thresholds. Other motifs (e.g., proportional feedback and ultrasensitivity)produce responses where the slope in the low-dose region is small and stays close to the baseline. Feedforward control may lead to nonmonotonic or hormetic responses. We conclude that network motifs provide a basis for understanding thresholds for cellular responses. Computational pathway modeling of these motifs and their combinations occurring in molecular signaling networks will be a key element in new risk assessment approaches based on in vitro cellular assays. Citation: Zhang Q, Bhattacharya S, Conolly RB, Clewell HJ III, Kaminski NE, Andersen ME. 2014. Molecular signaling network motifs provide a mechanistic basis for cellular threshold responses. Environ Health Perspect 122:1261–1270; http://dx.doi.org/10.1289/ehp.1408244 PMID:25117432

Single-mode glass waveguide technology for optical interchip communication on board level

NASA Astrophysics Data System (ADS)

Brusberg, Lars; Neitz, Marcel; Schröder, Henning

2012-01-01

The large bandwidth demand in long-distance telecom networks lead to single-mode fiber interconnects as result of low dispersion, low loss and dense wavelength multiplexing possibilities. In contrast, multi-mode interconnects are suitable for much shorter lengths up to 300 meters and are promising for optical links between racks and on board level. Active optical cables based on multi-mode fiber links are at the market and research in multi-mode waveguide integration on board level is still going on. Compared to multi-mode, a single-mode waveguide has much more integration potential because of core diameters of around 20% of a multi-mode waveguide by a much larger bandwidth. But light coupling in single-mode waveguides is much more challenging because of lower coupling tolerances. Together with the silicon photonics technology, a single-mode waveguide technology on board-level will be the straight forward development goal for chip-to-chip optical interconnects integration. Such a hybrid packaging platform providing 3D optical single-mode links bridges the gap between novel photonic integrated circuits and the glass fiber based long-distance telecom networks. Following we introduce our 3D photonic packaging approach based on thin glass substrates with planar integrated optical single-mode waveguides for fiber-to-chip and chip-to-chip interconnects. This novel packaging approach merges micro-system packaging and glass integrated optics. It consists of a thin glass substrate with planar integrated singlemode waveguide circuits, optical mirrors and lenses providing an integration platform for photonic IC assembly and optical fiber interconnect. Thin glass is commercially available in panel and wafer formats and characterizes excellent optical and high-frequency properties. That makes it perfect for microsystem packaging. The paper presents recent results in single-mode waveguide technology on wafer level and waveguide characterization. Furthermore the integration in a hybrid packaging process and design issues are discussed.

Active 2D materials for on-chip nanophotonics and quantum optics

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

Shiue, Ren-Jye; Efetov, Dmitri K.; Grosso, Gabriele

Abstract Two-dimensional materials have emerged as promising candidates to augment existing optical networks for metrology, sensing, and telecommunication, both in the classical and quantum mechanical regimes. Here, we review the development of several on-chip photonic components ranging from electro-optic modulators, photodetectors, bolometers, and light sources that are essential building blocks for a fully integrated nanophotonic and quantum photonic circuit.

Active 2D materials for on-chip nanophotonics and quantum optics

NASA Astrophysics Data System (ADS)

Shiue, Ren-Jye; Efetov, Dmitri K.; Grosso, Gabriele; Peng, Cheng; Fong, Kin Chung; Englund, Dirk

2017-03-01

Two-dimensional materials have emerged as promising candidates to augment existing optical networks for metrology, sensing, and telecommunication, both in the classical and quantum mechanical regimes. Here, we review the development of several on-chip photonic components ranging from electro-optic modulators, photodetectors, bolometers, and light sources that are essential building blocks for a fully integrated nanophotonic and quantum photonic circuit.

Audiovisual Rehabilitation in Hemianopia: A Model-Based Theoretical Investigation

PubMed Central

Magosso, Elisa; Cuppini, Cristiano; Bertini, Caterina

2017-01-01

Hemianopic patients exhibit visual detection improvement in the blind field when audiovisual stimuli are given in spatiotemporally coincidence. Beyond this “online” multisensory improvement, there is evidence of long-lasting, “offline” effects induced by audiovisual training: patients show improved visual detection and orientation after they were trained to detect and saccade toward visual targets given in spatiotemporal proximity with auditory stimuli. These effects are ascribed to the Superior Colliculus (SC), which is spared in these patients and plays a pivotal role in audiovisual integration and oculomotor behavior. Recently, we developed a neural network model of audiovisual cortico-collicular loops, including interconnected areas representing the retina, striate and extrastriate visual cortices, auditory cortex, and SC. The network simulated unilateral V1 lesion with possible spared tissue and reproduced “online” effects. Here, we extend the previous network to shed light on circuits, plastic mechanisms, and synaptic reorganization that can mediate the training effects and functionally implement visual rehabilitation. The network is enriched by the oculomotor SC-brainstem route, and Hebbian mechanisms of synaptic plasticity, and is used to test different training paradigms (audiovisual/visual stimulation in eye-movements/fixed-eyes condition) on simulated patients. Results predict different training effects and associate them to synaptic changes in specific circuits. Thanks to the SC multisensory enhancement, the audiovisual training is able to effectively strengthen the retina-SC route, which in turn can foster reinforcement of the SC-brainstem route (this occurs only in eye-movements condition) and reinforcement of the SC-extrastriate route (this occurs in presence of survived V1 tissue, regardless of eye condition). The retina-SC-brainstem circuit may mediate compensatory effects: the model assumes that reinforcement of this circuit can translate visual stimuli into short-latency saccades, possibly moving the stimuli into visual detection regions. The retina-SC-extrastriate circuit is related to restitutive effects: visual stimuli can directly elicit visual detection with no need for eye movements. Model predictions and assumptions are critically discussed in view of existing behavioral and neurophysiological data, forecasting that other oculomotor compensatory mechanisms, beyond short-latency saccades, are likely involved, and stimulating future experimental and theoretical investigations. PMID:29326578

Audiovisual Rehabilitation in Hemianopia: A Model-Based Theoretical Investigation.

PubMed

Magosso, Elisa; Cuppini, Cristiano; Bertini, Caterina

2017-01-01

Hemianopic patients exhibit visual detection improvement in the blind field when audiovisual stimuli are given in spatiotemporally coincidence. Beyond this "online" multisensory improvement, there is evidence of long-lasting, "offline" effects induced by audiovisual training: patients show improved visual detection and orientation after they were trained to detect and saccade toward visual targets given in spatiotemporal proximity with auditory stimuli. These effects are ascribed to the Superior Colliculus (SC), which is spared in these patients and plays a pivotal role in audiovisual integration and oculomotor behavior. Recently, we developed a neural network model of audiovisual cortico-collicular loops, including interconnected areas representing the retina, striate and extrastriate visual cortices, auditory cortex, and SC. The network simulated unilateral V1 lesion with possible spared tissue and reproduced "online" effects. Here, we extend the previous network to shed light on circuits, plastic mechanisms, and synaptic reorganization that can mediate the training effects and functionally implement visual rehabilitation. The network is enriched by the oculomotor SC-brainstem route, and Hebbian mechanisms of synaptic plasticity, and is used to test different training paradigms (audiovisual/visual stimulation in eye-movements/fixed-eyes condition) on simulated patients. Results predict different training effects and associate them to synaptic changes in specific circuits. Thanks to the SC multisensory enhancement, the audiovisual training is able to effectively strengthen the retina-SC route, which in turn can foster reinforcement of the SC-brainstem route (this occurs only in eye-movements condition) and reinforcement of the SC-extrastriate route (this occurs in presence of survived V1 tissue, regardless of eye condition). The retina-SC-brainstem circuit may mediate compensatory effects: the model assumes that reinforcement of this circuit can translate visual stimuli into short-latency saccades, possibly moving the stimuli into visual detection regions. The retina-SC-extrastriate circuit is related to restitutive effects: visual stimuli can directly elicit visual detection with no need for eye movements. Model predictions and assumptions are critically discussed in view of existing behavioral and neurophysiological data, forecasting that other oculomotor compensatory mechanisms, beyond short-latency saccades, are likely involved, and stimulating future experimental and theoretical investigations.

Electrical Design and Evaluation of Asynchronous Serial Bus Communication Network of 48 Sensor Platform LSIs with Single-Ended I/O for Integrated MEMS-LSI Sensors.

PubMed

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki; Muroyama, Masanori

2018-01-15

For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we have developed a dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) (referred to as "sensor platform LSI") for bus-networked Micro-Electro-Mechanical-Systems (MEMS)-LSI integrated sensors. In this LSI, collision avoidance, adaptation and event-driven functions are simply implemented to relieve data collision and congestion in asynchronous serial bus communication. In this study, we developed a network system with 48 sensor platform LSIs based on Printed Circuit Board (PCB) in a backbone bus topology with the bus length being 2.4 m. We evaluated the serial communication performance when 48 LSIs operated simultaneously with the adaptation function. The number of data packets received from each LSI was almost identical, and the average sampling frequency of 384 capacitance channels (eight for each LSI) was 73.66 Hz.

Modular thought in the circuit analysis

NASA Astrophysics Data System (ADS)

Wang, Feng

2018-04-01

Applied to solve the problem of modular thought, provides a whole for simplification's method, the complex problems have become of, and the study of circuit is similar to the above problems: the complex connection between components, make the whole circuit topic solution seems to be more complex, and actually components the connection between the have rules to follow, this article mainly tells the story of study on the application of the circuit modular thought. First of all, this paper introduces the definition of two-terminal network and the concept of two-terminal network equivalent conversion, then summarizes the common source resistance hybrid network modular approach, containing controlled source network modular processing method, lists the common module, typical examples analysis.

An Integrative Neuroscience Framework for the Treatment of Chronic Pain: From Cellular Alterations to Behavior.

PubMed

Greenwald, Jess D; Shafritz, Keith M

2018-01-01

Chronic pain can result from many pain syndromes including complex regional pain syndrome (CRPS), phantom limb pain and chronic low back pain, among others. On a molecular level, chronic pain syndromes arise from hypersensitization within the dorsal horn of the spinal cord, a process known as central sensitization. Central sensitization involves an upregulation of ionotropic and metabotropic glutamate receptors (mGluRs) similar to that of long-term potentiation (LTP). Regions of the brain in which LTP occurs, such as the amygdala and hippocampus, are implicated in fear- and memory-related brain circuity. Chronic pain dramatically influences patient quality of life. Individuals with chronic pain may develop pain-related anxiety and pain-related fear. The syndrome also alters functional connectivity in the default-mode network (DMN) and salience network. On a cellular/molecular level, central sensitization may be reversed through degradative glutamate receptor pathways. This, however, rarely happens. Instead, cortical brain regions may serve in a top-down regulatory capacity for the maintenance or alleviation of pain. Specifically, the medial prefrontal cortex (mPFC), which plays a critical role in fear-related brain circuits, the DMN, and salience network may be the driving forces in this process. On a cellular level, the mPFC may form new neural circuits through LTP that may cause extinction of pre-existing pain pathways found within fear-related brain circuits, the DMN, and salience network. In order to promote new LTP connections between the mPFC and other key brain structures, such as the amygdala and insula, we propose a holistic rehabilitation program including cognitive behavioral therapy (CBT) and revolving around: (1) cognitive reappraisals; (2) mindfulness meditation; and (3) functional rehabilitation. Unlike current medical interventions focusing upon pain-relieving medications, we do not believe that chronic pain treatment should focus on reversing the effects of central sensitization. Instead, we propose here that it is critical to focus on non-invasive efforts to promote new neural circuits originating from the mPFC.

Pairing Increases Activation of V1aR, but not OTR, in Auditory Regions of Zebra Finches: The Importance of Signal Modality in Nonapeptide-Social Behavior Relationships.

PubMed

Tomaszycki, Michelle L; Atchley, Derek

2017-10-01

Social relationships are complex, involving the production and comprehension of signals, individual recognition, and close coordination of behavior between two or more individuals. The nonapeptides oxytocin and vasopressin are widely believed to regulate social relationships. These findings come largely from prairie voles, in which nonapeptide receptors in olfactory neural circuits drive pair bonding. This research is assumed to apply to all species. Previous reviews have offered two competing hypotheses. The work of Sarah Newman has implicated a common neural network across species, the Social Behavior Network. In contrast, others have suggested that there are signal modality-specific networks that regulate social behavior. Our research focuses on evaluating these two competing hypotheses in the zebra finch, a species that relies heavily on vocal/auditory signals for communication, specifically the neural circuits underlying singing in males and song perception in females. We have demonstrated that the quality of vocal interactions is highly important for the formation of long-term monogamous bonds in zebra finches. Qualitative evidence at first suggests that nonapeptide receptor distributions are very different between monogamous rodents (olfactory species) and monogamous birds (vocal/auditory species). However, we have demonstrated that social bonding behaviors are not only correlated with activation of nonapeptide receptors in vocal and auditory circuits, but also involve regions of the common Social Behavior Network. Here, we show increased Vasopressin 1a receptor, but not oxytocin receptor, activation in two auditory regions following formation of a pair bond. To our knowledge, this is the first study to suggest a role of nonapeptides in the auditory circuit in pair bonding. Thus, we highlight converging mechanisms of social relationships and also point to the importance of studying multiple species to understand mechanisms of behavior. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

A synthetic mammalian electro-genetic transcription circuit.

PubMed

Weber, Wilfried; Luzi, Stefan; Karlsson, Maria; Sanchez-Bustamante, Carlota Diaz; Frey, Urs; Hierlemann, Andreas; Fussenegger, Martin

2009-03-01

Electric signal processing has evolved to manage rapid information transfer in neuronal networks and muscular contraction in multicellular organisms and controls the most sophisticated man-built devices. Using a synthetic biology approach to assemble electronic parts with genetic control units engineered into mammalian cells, we designed an electric power-adjustable transcription control circuit able to integrate the intensity of a direct current over time, to translate the amplitude or frequency of an alternating current into an adjustable genetic readout or to modulate the beating frequency of primary heart cells. Successful miniaturization of the electro-genetic devices may pave the way for the design of novel hybrid electro-genetic implants assembled from electronic and genetic parts.

A synthetic mammalian electro-genetic transcription circuit

PubMed Central

Weber, Wilfried; Luzi, Stefan; Karlsson, Maria; Sanchez-Bustamante, Carlota Diaz; Frey, Urs; Hierlemann, Andreas; Fussenegger, Martin

2009-01-01

Electric signal processing has evolved to manage rapid information transfer in neuronal networks and muscular contraction in multicellular organisms and controls the most sophisticated man-built devices. Using a synthetic biology approach to assemble electronic parts with genetic control units engineered into mammalian cells, we designed an electric power-adjustable transcription control circuit able to integrate the intensity of a direct current over time, to translate the amplitude or frequency of an alternating current into an adjustable genetic readout or to modulate the beating frequency of primary heart cells. Successful miniaturization of the electro-genetic devices may pave the way for the design of novel hybrid electro-genetic implants assembled from electronic and genetic parts. PMID:19190091

Next generation communications satellites: multiple access and network studies

NASA Technical Reports Server (NTRS)

Meadows, H. E.; Schwartz, M.; Stern, T. E.; Ganguly, S.; Kraimeche, B.; Matsuo, K.; Gopal, I.

1982-01-01

Efficient resource allocation and network design for satellite systems serving heterogeneous user populations with large numbers of small direct-to-user Earth stations are discussed. Focus is on TDMA systems involving a high degree of frequency reuse by means of satellite-switched multiple beams (SSMB) with varying degrees of onboard processing. Algorithms for the efficient utilization of the satellite resources were developed. The effect of skewed traffic, overlapping beams and batched arrivals in packet-switched SSMB systems, integration of stream and bursty traffic, and optimal circuit scheduling in SSMB systems: performance bounds and computational complexity are discussed.

Electronic circuits and systems: A compilation. [including integrated circuits, logic circuits, varactor diode circuits, low pass filters, and optical equipment circuits

NASA Technical Reports Server (NTRS)

1975-01-01

Technological information is presented electronic circuits and systems which have potential utility outside the aerospace community. Topics discussed include circuit components such as filters, converters, and integrators, circuits designed for use with specific equipment or systems, and circuits designed primarily for use with optical equipment or displays.

Integration and manufacture of multifunctional planar lightwave circuits

NASA Astrophysics Data System (ADS)

Lipscomb, George F.; Ticknor, Anthony J.; Stiller, Marc A.; Chen, Wenjie; Schroeter, Paul

2001-11-01

The demands of exponentially growing Internet traffic, coupled with the advent of Dense Wavelength Division Multiplexing (DWDM) fiber optic systems to meet those demands, have triggered a revolution in the telecommunications industry. This dramatic change has been built upon, and has driven, improvements in fiber optic component technology. The next generation of systems for the all optical network will require higher performance components coupled with dramatically lower costs. One approach to achieve significantly lower costs per function is to employ Planar Lightwave Circuits (PLC) to integrate multiple optical functions in a single package. PLCs are optical circuits laid out on a silicon wafer, and are made using tools and techniques developed to extremely high levels by the semi-conductor industry. In this way multiple components can be fabricated and interconnected at once, significantly reducing both the manufacturing and the packaging/assembly costs. Currently, the predominant commercial application of PLC technology is arrayed-waveguide gratings (AWG's) for multiplexing and demultiplexing multiple wavelength channels in a DWDM system. Although this is generally perceived as a single-function device, it can be performing the function of more than 100 discrete fiber-optic components and already represents a considerable degree of integration. Furthermore, programmable functions such as variable-optical attenuators (VOAs) and switches made with compatible PLC technology are now moving into commercial production. In this paper, we present results on the integration of active and passive functions together using PLC technology, e.g. a 40 channel AWG multiplexer with 40 individually controllable VOAs.

CMOS nanoelectrode array for all-electrical intracellular electrophysiological imaging

NASA Astrophysics Data System (ADS)

Abbott, Jeffrey; Ye, Tianyang; Qin, Ling; Jorgolli, Marsela; Gertner, Rona S.; Ham, Donhee; Park, Hongkun

2017-05-01

Developing a new tool capable of high-precision electrophysiological recording of a large network of electrogenic cells has long been an outstanding challenge in neurobiology and cardiology. Here, we combine nanoscale intracellular electrodes with complementary metal-oxide-semiconductor (CMOS) integrated circuits to realize a high-fidelity all-electrical electrophysiological imager for parallel intracellular recording at the network level. Our CMOS nanoelectrode array has 1,024 recording/stimulation 'pixels' equipped with vertical nanoelectrodes, and can simultaneously record intracellular membrane potentials from hundreds of connected in vitro neonatal rat ventricular cardiomyocytes. We demonstrate that this network-level intracellular recording capability can be used to examine the effect of pharmaceuticals on the delicate dynamics of a cardiomyocyte network, thus opening up new opportunities in tissue-based pharmacological screening for cardiac and neuronal diseases as well as fundamental studies of electrogenic cells and their networks.

General analytical solutions for DC/AC circuit-network analysis

NASA Astrophysics Data System (ADS)

Rubido, Nicolás; Grebogi, Celso; Baptista, Murilo S.

2017-06-01

In this work, we present novel general analytical solutions for the currents that are developed in the edges of network-like circuits when some nodes of the network act as sources/sinks of DC or AC current. We assume that Ohm's law is valid at every edge and that charge at every node is conserved (with the exception of the source/sink nodes). The resistive, capacitive, and/or inductive properties of the lines in the circuit define a complex network structure with given impedances for each edge. Our solution for the currents at each edge is derived in terms of the eigenvalues and eigenvectors of the Laplacian matrix of the network defined from the impedances. This derivation also allows us to compute the equivalent impedance between any two nodes of the circuit and relate it to currents in a closed circuit which has a single voltage generator instead of many input/output source/sink nodes. This simplifies the treatment that could be done via Thévenin's theorem. Contrary to solving Kirchhoff's equations, our derivation allows to easily calculate the redistribution of currents that occurs when the location of sources and sinks changes within the network. Finally, we show that our solutions are identical to the ones found from Circuit Theory nodal analysis.

Ultra-thin silicon (UTSi) on insulator CMOS transceiver and time-division multiplexed switch chips for smart pixel integration

NASA Astrophysics Data System (ADS)

Zhang, Liping; Sawchuk, Alexander A.

2001-12-01

We describe the design, fabrication and functionality of two different 0.5 micron CMOS optoelectronic integrated circuit (OEIC) chips based on the Peregrine Semiconductor Ultra-Thin Silicon on insulator technology. The Peregrine UTSi silicon- on-sapphire (SOS) technology is a member of the silicon-on- insulator (SOI) family. The low-loss synthetic sapphire substrate is optically transparent and has good thermal conductivity and coefficient of thermal expansion properties, which meet the requirements for flip-chip bonding of VCSELs and other optoelectronic input-output components. One chip contains transceiver and network components, including four channel high-speed CMOS transceiver modules, pseudo-random bit stream (PRBS) generators, a voltage controlled oscillator (VCO) and other test circuits. The transceiver chips can operate in both self-testing mode and networking mode. An on- chip clock and true-single-phase-clock (TSPC) D-flip-flop have been designed to generate a PRBS at over 2.5 Gb/s for the high-speed transceiver arrays to operate in self-testing mode. In the networking mode, an even number of transceiver chips forms a ring network through free-space or fiber ribbon interconnections. The second chip contains four channel optical time-division multiplex (TDM) switches, optical transceiver arrays, an active pixel detector and additional test devices. The eventual applications of these chips will require monolithic OEICs with integrated optical input and output. After fabrication and testing, the CMOS transceiver array dies will be packaged with 850 nm vertical cavity surface emitting lasers (VCSELs), and metal-semiconductor- metal (MSM) or GaAs p-i-n detector die arrays to achieve high- speed optical interconnections. The hybrid technique could be either wire bonding or flip-chip bonding of the CMOS SOS smart-pixel arrays with arrays of VCSELs and photodetectors onto an optoelectronic chip carrier as a multi-chip module (MCM).

30-100-GHz inductors and transformers for millimeter-wave (Bi)CMOS integrated circuits

NASA Astrophysics Data System (ADS)

Dickson, T. O.; Lacroix, M.-A.; Boret, S.; Gloria, D.; Beerkens, R.; Voinigescu, S. P.

2005-01-01

Silicon planar and three-dimensional inductors and transformers were designed and characterized on-wafer up to 100 GHz. Self-resonance frequencies (SRFs) beyond 100 GHz were obtained, demonstrating for the first time that spiral structures are suitable for applications such as 60-GHz wireless local area network and 77-GHz automotive RADAR. Minimizing area over substrate is critical to achieving high SRF. A stacked transformer is reported with S21 of -2.5 dB at 50 GHz, and which offers improved performance and less area (30 μm × 30 μm) than planar transformers or microstrip couplers. A compact inductor model is described, along with a methodology for extracting model parameters from simulated or measured y-parameters. Millimeter-wave SiGe BiCMOS mixer and voltage-controlled-oscillator circuits employing spiral inductors are presented with better or comparable performance to previously reported transmission-line-based circuits.

Automatic visual inspection system for microelectronics

NASA Technical Reports Server (NTRS)

Micka, E. Z. (Inventor)

1975-01-01

A system for automatically inspecting an integrated circuit was developed. A device for shining a scanning narrow light beam at an integrated circuit to be inspected and another light beam at an accepted integrated circuit was included. A pair of photodetectors that receive light reflected from these integrated circuits, and a comparing system compares the outputs of the photodetectors.

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

Wojciechowski, Kenneth; Olsson, Roy; Clews, Peggy J.

Thermally isolated devices may be formed by performing a series of etches on a silicon-based substrate. As a result of the series of etches, silicon material may be removed from underneath a region of an integrated circuit (IC). The removal of the silicon material from underneath the IC forms a gap between remaining substrate and the integrated circuit, though the integrated circuit remains connected to the substrate via a support bar arrangement that suspends the integrated circuit over the substrate. The creation of this gap functions to release the device from the substrate and create a thermally-isolated integrated circuit.

Design structure for in-system redundant array repair in integrated circuits

DOEpatents

Bright, Arthur A.; Crumley, Paul G.; Dombrowa, Marc; Douskey, Steven M.; Haring, Rudolf A.; Oakland, Steven F.; Quellette, Michael R.; Strissel, Scott A.

2008-11-25

A design structure for repairing an integrated circuit during operation of the integrated circuit. The integrated circuit comprising of a multitude of memory arrays and a fuse box holding control data for controlling redundancy logic of the arrays. The design structure provides the integrated circuit with a control data selector for passing the control data from the fuse box to the memory arrays; providing a source of alternate control data, external of the integrated circuit; and connecting the source of alternate control data to the control data selector. The design structure further passes the alternate control data from the source thereof, through the control data selector and to the memory arrays to control the redundancy logic of the memory arrays.

Laser Integration on Silicon Photonic Circuits Through Transfer Printing

DTIC Science & Technology

2017-03-10

AFRL-AFOSR-UK-TR-2017-0019 Laser integration on silicon photonic circuits through transfer printing Gunther Roelkens UNIVERSITEIT GENT VZW Final...TYPE Final 3. DATES COVERED (From - To) 15 Sep 2015 to 14 Sep 2016 4. TITLE AND SUBTITLE Laser integration on silicon photonic circuits through...parallel integration of III-V lasers on silicon photonic integrated circuits. The report discusses the technological process that has been developed as

The Development of an IMU Integrated Clothes for Postural Monitoring Using Conductive Yarn and Interconnecting Technology

PubMed Central

Kang, Sung-Won; Park, Hyung-Il; Choi, Byoung-Gun; Shin, Dongjun; Jung, Young-Giu; Lee, Jun-Young; Park, Hong-Won; Park, Sukyung

2017-01-01

Spinal disease is a common yet important condition that occurs because of inappropriate posture. Prevention could be achieved by continuous posture monitoring, but most measurement systems cannot be used in daily life due to factors such as burdensome wires and large sensing modules. To improve upon these weaknesses, we developed comfortable “smart wear” for posture measurement using conductive yarn for circuit patterning and a flexible printed circuit board (FPCB) for interconnections. The conductive yarn was made by twisting polyester yarn and metal filaments, and the resistance per unit length was about 0.05 Ω/cm. An embroidered circuit was made using the conductive yarn, which showed increased yield strength and uniform electrical resistance per unit length. Circuit networks of sensors and FPCBs for interconnection were integrated into clothes using a computer numerical control (CNC) embroidery process. The system was calibrated and verified by comparing the values measured by the smart wear with those measured by a motion capture camera system. Six subjects performed fixed movements and free computer work, and, with this system, we were able to measure the anterior/posterior direction tilt angle with an error of less than 4°. The smart wear does not have excessive wires, and its structure will be optimized for better posture estimation in a later study. PMID:29112125

Graphene radio frequency receiver integrated circuit.

PubMed

Han, Shu-Jen; Garcia, Alberto Valdes; Oida, Satoshi; Jenkins, Keith A; Haensch, Wilfried

2014-01-01

Graphene has attracted much interest as a future channel material in radio frequency electronics because of its superior electrical properties. Fabrication of a graphene integrated circuit without significantly degrading transistor performance has proven to be challenging, posing one of the major bottlenecks to compete with existing technologies. Here we present a fabrication method fully preserving graphene transistor quality, demonstrated with the implementation of a high-performance three-stage graphene integrated circuit. The circuit operates as a radio frequency receiver performing signal amplification, filtering and downconversion mixing. All circuit components are integrated into 0.6 mm(2) area and fabricated on 200 mm silicon wafers, showing the unprecedented graphene circuit complexity and silicon complementary metal-oxide-semiconductor process compatibility. The demonstrated circuit performance allow us to use graphene integrated circuit to perform practical wireless communication functions, receiving and restoring digital text transmitted on a 4.3-GHz carrier signal.

Graphene radio frequency receiver integrated circuit

NASA Astrophysics Data System (ADS)

Han, Shu-Jen; Garcia, Alberto Valdes; Oida, Satoshi; Jenkins, Keith A.; Haensch, Wilfried

2014-01-01

Graphene has attracted much interest as a future channel material in radio frequency electronics because of its superior electrical properties. Fabrication of a graphene integrated circuit without significantly degrading transistor performance has proven to be challenging, posing one of the major bottlenecks to compete with existing technologies. Here we present a fabrication method fully preserving graphene transistor quality, demonstrated with the implementation of a high-performance three-stage graphene integrated circuit. The circuit operates as a radio frequency receiver performing signal amplification, filtering and downconversion mixing. All circuit components are integrated into 0.6 mm2 area and fabricated on 200 mm silicon wafers, showing the unprecedented graphene circuit complexity and silicon complementary metal-oxide-semiconductor process compatibility. The demonstrated circuit performance allow us to use graphene integrated circuit to perform practical wireless communication functions, receiving and restoring digital text transmitted on a 4.3-GHz carrier signal.

JFET front-end circuits integrated in a detector-grade silicon substrate

NASA Astrophysics Data System (ADS)

Manghisoni, M.; Ratti, L.; Re, V.; Speziali, V.; Traversi, G.; Dalla Betta, G. F.; Boscardin, M.; Batignani, G.; Giorgi, M.; Bosisio, L.

2003-08-01

This paper presents the design and experimental results relevant to front-end circuits integrated on detector-grade high resistivity silicon. The fabrication technology is made available by the Istituto per la Ricerca Scientifica e Tecnologica (ITC-IRST), Trento, Italy and allows using a common substrate for different kinds of active devices, such as N-channel JFETs and MOSFETs, and for pixel, microstrip, and PIN detectors. This research activity is being carried out in the framework of a project aiming at the fabrication of a multichannel mixed analog-digital chip for the readout of solid-state detectors integrated in the same substrate. Possible applications are in the field of medical and industrial imaging and space and high energy physics experiments. An all-JFET charge sensitive amplifier, which can use either a resistive or a nonresistive feedback network, has been characterized. The two configurations have been compared to each other, paying particular attention to noise performances, in view of the design of the complete readout channel. Operation capability in harsh radiation environment has been evaluated through exposure to /spl gamma/-rays from a /sup 60/Co source.

Active C4 Electrodes for Local Field Potential Recording Applications

PubMed Central

Wang, Lu; Freedman, David; Sahin, Mesut; Ünlü, M. Selim; Knepper, Ronald

2016-01-01

Extracellular neural recording, with multi-electrode arrays (MEAs), is a powerful method used to study neural function at the network level. However, in a high density array, it can be costly and time consuming to integrate the active circuit with the expensive electrodes. In this paper, we present a 4 mm × 4 mm neural recording integrated circuit (IC) chip, utilizing IBM C4 bumps as recording electrodes, which enable a seamless active chip and electrode integration. The IC chip was designed and fabricated in a 0.13 μm BiCMOS process for both in vitro and in vivo applications. It has an input-referred noise of 4.6 μVrms for the bandwidth of 10 Hz to 10 kHz and a power dissipation of 11.25 mW at 2.5 V, or 43.9 μW per input channel. This prototype is scalable for implementing larger number and higher density electrode arrays. To validate the functionality of the chip, electrical testing results and acute in vivo recordings from a rat barrel cortex are presented. PMID:26861324

Monolithically integrated bacteriorhodopsin/semiconductor opto-electronic integrated circuit for a bio-photoreceiver.

PubMed

Xu, J; Bhattacharya, P; Váró, G

2004-03-15

The light-sensitive protein, bacteriorhodopsin (BR), is monolithically integrated with an InP-based amplifier circuit to realize a novel opto-electronic integrated circuit (OEIC) which performs as a high-speed photoreceiver. The circuit is realized by epitaxial growth of the field-effect transistors, currently used semiconductor device and circuit fabrication techniques, and selective area BR electro-deposition. The integrated photoreceiver has a responsivity of 175 V/W and linear photoresponse, with a dynamic range of 16 dB, with 594 nm photoexcitation. The dynamics of the photochemical cycle of BR has also been modeled and a proposed equivalent circuit simulates the measured BR photoresponse with good agreement.

Compact Interconnection Networks Based on Quantum Dots

NASA Technical Reports Server (NTRS)

Fijany, Amir; Toomarian, Nikzad; Modarress, Katayoon; Spotnitz, Matthew

2003-01-01

Architectures that would exploit the distinct characteristics of quantum-dot cellular automata (QCA) have been proposed for digital communication networks that connect advanced digital computing circuits. In comparison with networks of wires in conventional very-large-scale integrated (VLSI) circuitry, the networks according to the proposed architectures would be more compact. The proposed architectures would make it possible to implement complex interconnection schemes that are required for some advanced parallel-computing algorithms and that are difficult (and in many cases impractical) to implement in VLSI circuitry. The difficulty of implementation in VLSI and the major potential advantage afforded by QCA were described previously in Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42. To recapitulate: Wherever two wires in a conventional VLSI circuit cross each other and are required not to be in electrical contact with each other, there must be a layer of electrical insulation between them. This, in turn, makes it necessary to resort to a noncoplanar and possibly a multilayer design, which can be complex, expensive, and even impractical. As a result, much of the cost of designing VLSI circuits is associated with minimization of data routing and assignment of layers to minimize crossing of wires. Heretofore, these considerations have impeded the development of VLSI circuitry to implement complex, advanced interconnection schemes. On the other hand, with suitable design and under suitable operating conditions, QCA-based signal paths can be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. The proposed architectures require two advances in QCA-based circuitry beyond basic QCA-based binary-signal wires described in the cited prior article. One of these advances would be the development of QCA-based wires capable of bidirectional transmission of signals. The other advance would be the development of QCA circuits capable of high-impedance state outputs. The high-impedance states would be utilized along with the 0- and 1-state outputs of QCA.

Configurable hardware integrate and fire neurons for sparse approximation.

PubMed

Shapero, Samuel; Rozell, Christopher; Hasler, Paul

2013-09-01

Sparse approximation is an important optimization problem in signal and image processing applications. A Hopfield-Network-like system of integrate and fire (IF) neurons is proposed as a solution, using the Locally Competitive Algorithm (LCA) to solve an overcomplete L1 sparse approximation problem. A scalable system architecture is described, including IF neurons with a nonlinear firing function, and current-based synapses to provide linear computation. A network of 18 neurons with 12 inputs is implemented on the RASP 2.9v chip, a Field Programmable Analog Array (FPAA) with directly programmable floating gate elements. Said system uses over 1400 floating gates, the largest system programmed on a FPAA to date. The circuit successfully reproduced the outputs of a digital optimization program, converging to within 4.8% RMS, and an objective cost only 1.7% higher on average. The active circuit consumed 559 μA of current at 2.4 V and converges on solutions in 25 μs, with measurement of the converged spike rate taking an additional 1 ms. Extrapolating the scaling trends to a N=1000 node system, the spiking LCA compares favorably with state-of-the-art digital solutions, and analog solutions using a non-spiking approach. Copyright © 2013 Elsevier Ltd. All rights reserved.

Triboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring.

PubMed

Lin, Zhiming; Chen, Jun; Li, Xiaoshi; Zhou, Zhihao; Meng, Keyu; Wei, Wei; Yang, Jin; Wang, Zhong Lin

2017-09-26

Heart-rate monitoring plays a critical role in personal healthcare management. A low-cost, noninvasive, and user-friendly heart-rate monitoring system is highly desirable. Here, a self-powered wireless body sensor network (BSN) system is developed for heart-rate monitoring via integration of a downy-structure-based triboelectric nanogenerator (D-TENG), a power management circuit, a heart-rate sensor, a signal processing unit, and Bluetooth module for wireless data transmission. By converting the inertia energy of human walking into electric power, a maximum power of 2.28 mW with total conversion efficiency of 57.9% was delivered at low operation frequency, which is capable of immediately and sustainably driving the highly integrated BSN system. The acquired heart-rate signal by the sensor would be processed in the signal process circuit, sent to an external device via the Bluetooth module, and displayed on a personal cell phone in a real-time manner. Moreover, by combining a TENG-based generator and a TENG-based sensor, an all-TENG-based wireless BSN system was developed, realizing continuous and self-powered heart-rate monitoring. This work presents a potential method for personal heart-rate monitoring, featured as being self-powered, cost-effective, noninvasive, and user-friendly.

NT3-chitosan elicits robust endogenous neurogenesis to enable functional recovery after spinal cord injury

PubMed Central

Yang, Zhaoyang; Zhang, Aifeng; Duan, Hongmei; Zhang, Sa; Hao, Peng; Ye, Keqiang; Sun, Yi E.; Li, Xiaoguang

2015-01-01

Neural stem cells (NSCs) in the adult mammalian central nervous system (CNS) hold the key to neural regeneration through proper activation, differentiation, and maturation, to establish nascent neural networks, which can be integrated into damaged neural circuits to repair function. However, the CNS injury microenvironment is often inhibitory and inflammatory, limiting the ability of activated NSCs to differentiate into neurons and form nascent circuits. Here we report that neurotrophin-3 (NT3)-coupled chitosan biomaterial, when inserted into a 5-mm gap of completely transected and excised rat thoracic spinal cord, elicited robust activation of endogenous NSCs in the injured spinal cord. Through slow release of NT3, the biomaterial attracted NSCs to migrate into the lesion area, differentiate into neurons, and form functional neural networks, which interconnected severed ascending and descending axons, resulting in sensory and motor behavioral recovery. Our study suggests that enhancing endogenous neurogenesis could be a novel strategy for treatment of spinal cord injury. PMID:26460015

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

Linking Neurons to Network Function and Behavior by Two-Photon Holographic Optogenetics and Volumetric Imaging.

PubMed

Dal Maschio, Marco; Donovan, Joseph C; Helmbrecht, Thomas O; Baier, Herwig

2017-05-17

We introduce a flexible method for high-resolution interrogation of circuit function, which combines simultaneous 3D two-photon stimulation of multiple targeted neurons, volumetric functional imaging, and quantitative behavioral tracking. This integrated approach was applied to dissect how an ensemble of premotor neurons in the larval zebrafish brain drives a basic motor program, the bending of the tail. We developed an iterative photostimulation strategy to identify minimal subsets of channelrhodopsin (ChR2)-expressing neurons that are sufficient to initiate tail movements. At the same time, the induced network activity was recorded by multiplane GCaMP6 imaging across the brain. From this dataset, we computationally identified activity patterns associated with distinct components of the elicited behavior and characterized the contributions of individual neurons. Using photoactivatable GFP (paGFP), we extended our protocol to visualize single functionally identified neurons and reconstruct their morphologies. Together, this toolkit enables linking behavior to circuit activity with unprecedented resolution. Copyright © 2017 Elsevier Inc. All rights reserved.

Facile fabrication of networked patterns and their superior application to realize the virus immobilized networked pattern circuit.

PubMed

Choi, Kyung Min; Lee, Seok Jae; Choi, Jung Hoon; Park, Tae Jung; Park, Jong Wan; Shin, Weon Ho; Kang, Jeung Ku

2010-12-07

A facile route to fabricate a protein-immobilized network pattern circuit for rapid and highly sensitive diagnosis was developed via the evaporation directed impromptu patterning method and selective avian influenza virus (AIV) immobilization. The response to the 10 fg mL(-1) anti-AI antibody demonstrates that this easy and simple circuit has about 1000 times higher sensitivity compared to those of conventional approaches.

Microchannel cooling of face down bonded chips

DOEpatents

Bernhardt, Anthony F.

1993-01-01

Microchannel cooling is applied to flip-chip bonded integrated circuits, in a manner which maintains the advantages of flip-chip bonds, while overcoming the difficulties encountered in cooling the chips. The technique is suited to either multichip integrated circuit boards in a plane, or to stacks of circuit boards in a three dimensional interconnect structure. Integrated circuit chips are mounted on a circuit board using flip-chip or control collapse bonds. A microchannel structure is essentially permanently coupled with the back of the chip. A coolant delivery manifold delivers coolant to the microchannel structure, and a seal consisting of a compressible elastomer is provided between the coolant delivery manifold and the microchannel structure. The integrated circuit chip and microchannel structure are connected together to form a replaceable integrated circuit module which can be easily decoupled from the coolant delivery manifold and the circuit board. The coolant supply manifolds may be disposed between the circuit boards in a stack and coupled to supplies of coolant through a side of the stack.

Microchannel cooling of face down bonded chips

DOEpatents

Bernhardt, A.F.

1993-06-08

Microchannel cooling is applied to flip-chip bonded integrated circuits, in a manner which maintains the advantages of flip-chip bonds, while overcoming the difficulties encountered in cooling the chips. The technique is suited to either multi chip integrated circuit boards in a plane, or to stacks of circuit boards in a three dimensional interconnect structure. Integrated circuit chips are mounted on a circuit board using flip-chip or control collapse bonds. A microchannel structure is essentially permanently coupled with the back of the chip. A coolant delivery manifold delivers coolant to the microchannel structure, and a seal consisting of a compressible elastomer is provided between the coolant delivery manifold and the microchannel structure. The integrated circuit chip and microchannel structure are connected together to form a replaceable integrated circuit module which can be easily decoupled from the coolant delivery manifold and the circuit board. The coolant supply manifolds may be disposed between the circuit boards in a stack and coupled to supplies of coolant through a side of the stack.

The evolvability of programmable hardware.

PubMed

Raman, Karthik; Wagner, Andreas

2011-02-06

In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected 'neutral networks' in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 10(45) logic circuits ('genotypes') and 10(19) logic functions ('phenotypes'). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry.

Computer-aided linear-circuit design.

NASA Technical Reports Server (NTRS)

Penfield, P.

1971-01-01

Usually computer-aided design (CAD) refers to programs that analyze circuits conceived by the circuit designer. Among the services such programs should perform are direct network synthesis, analysis, optimization of network parameters, formatting, storage of miscellaneous data, and related calculations. The program should be embedded in a general-purpose conversational language such as BASIC, JOSS, or APL. Such a program is MARTHA, a general-purpose linear-circuit analyzer embedded in APL.

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity.

PubMed

Tsai, Kuo-Ting; Hu, Chin-Kun; Li, Kuan-Wei; Hwang, Wen-Liang; Chou, Ya-Hui

2018-05-23

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

Spontaneous network activity and synaptic development

PubMed Central

Kerschensteiner, Daniel

2014-01-01

Throughout development, the nervous system produces patterned spontaneous activity. Research over the last two decades has revealed a core group of mechanisms that mediate spontaneous activity in diverse circuits. Many circuits engage several of these mechanisms sequentially to accommodate developmental changes in connectivity. In addition to shared mechanisms, activity propagates through developing circuits and neuronal pathways (i.e. linked circuits in different brain areas) in stereotypic patterns. Increasing evidence suggests that spontaneous network activity shapes synaptic development in vivo. Variations in activity-dependent plasticity may explain how similar mechanisms and patterns of activity can be employed to establish diverse circuits. Here, I will review common mechanisms and patterns of spontaneous activity in emerging neural networks and discuss recent insights into their contribution to synaptic development. PMID:24280071

Optical detectors for GaAs MMIC integration: Technology assessment

NASA Technical Reports Server (NTRS)

Claspy, P. C.; Bhasin, K. B.

1989-01-01

Fiber optic links are being considered to transmit digital and analog signals in phased array antenna feed networks in space communications systems. The radiating elements in these arrays will be GaAs monolithic microwave integrated circuits (MMIC's) in numbers ranging from a few hundred to several thousand. If such optical interconnects are to be practical it appears essential that the associated components, including detectors, be monolithically integrated on the same chip as the microwave circuitry. The general issue of monolithic integration of microwave and optoelectronic components is addressed from the point of view of fabrication technology and compatibility. Particular attention is given to the fabrication technology of various types of GaAs optical detectors that are designed to operate at a wavelength of 830 nm.

Motor and cortico-striatal-thalamic connectivity alterations in intrauterine growth restriction.

PubMed

Eixarch, Elisenda; Muñoz-Moreno, Emma; Bargallo, Nuria; Batalle, Dafnis; Gratacos, Eduard

2016-06-01

Intrauterine growth restriction is associated with short- and long-term neurodevelopmental problems. Structural brain changes underlying these alterations have been described with the use of different magnetic resonance-based methods that include changes in whole structural brain networks. However, evaluation of specific brain circuits and its correlation with related functions has not been investigated in intrauterine growth restriction. In this study, we aimed to investigate differences in tractography-related metrics in cortico-striatal-thalamic and motor networks in intrauterine growth restricted children and whether these parameters were related with their specific function in order to explore its potential use as an imaging biomarker of altered neurodevelopment. We included a group of 24 intrauterine growth restriction subjects and 27 control subjects that were scanned at 1 year old; we acquired T1-weighted and 30 directions diffusion magnetic resonance images. Each subject brain was segmented in 93 regions with the use of anatomical automatic labeling atlas, and deterministic tractography was performed. Brain regions included in motor and cortico-striatal-thalamic networks were defined based in functional and anatomic criteria. Within the streamlines that resulted from the whole brain tractography, those belonging to each specific circuit were selected and tractography-related metrics that included number of streamlines, fractional anisotropy, and integrity were calculated for each network. We evaluated differences between both groups and further explored the correlation of these parameters with the results of socioemotional, cognitive, and motor scales from Bayley Scale at 2 years of age. Reduced fractional anisotropy (cortico-striatal-thalamic, 0.319 ± 0.018 vs 0.315 ± 0.015; P = .010; motor, 0.322 ± 0.019 vs 0.319 ± 0.020; P = .019) and integrity cortico-striatal-thalamic (0.407 ± 0.040 vs 0.399 ± 0.034; P = .018; motor, 0.417 ± 0.044 vs 0.409 ± 0.046; P = .016) in both networks were observed in the intrauterine growth restriction group, with no differences in number of streamlines. More importantly, strong specific correlation was found between tractography-related metrics and its relative function in both networks in intrauterine growth restricted children. Motor network metrics were correlated specifically with motor scale results (fractional anisotropy: rho = 0.857; integrity: rho = 0.740); cortico-striatal-thalamic network metrics were correlated with cognitive (fractional anisotropy: rho = 0.793; integrity, rho = 0.762) and socioemotional scale (fractional anisotropy: rho = 0.850; integrity: rho = 0.877). These results support the existence of altered brain connectivity in intrauterine growth restriction demonstrated by altered connectivity in motor and cortico-striatal-thalamic networks, with reduced fractional anisotropy and integrity. The specific correlation between tractography-related metrics and neurodevelopmental outcomes in intrauterine growth restriction shows the potential to use this approach to develop imaging biomarkers to predict specific neurodevelopmental outcome in infants who are at risk because of intrauterine growth restriction and other prenatal diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Topological Properties of Some Integrated Circuits for Very Large Scale Integration Chip Designs

NASA Astrophysics Data System (ADS)

Swanson, S.; Lanzerotti, M.; Vernizzi, G.; Kujawski, J.; Weatherwax, A.

2015-03-01

This talk presents topological properties of integrated circuits for Very Large Scale Integration chip designs. These circuits can be implemented in very large scale integrated circuits, such as those in high performance microprocessors. Prior work considered basic combinational logic functions and produced a mathematical framework based on algebraic topology for integrated circuits composed of logic gates. Prior work also produced an historically-equivalent interpretation of Mr. E. F. Rent's work for today's complex circuitry in modern high performance microprocessors, where a heuristic linear relationship was observed between the number of connections and number of logic gates. This talk will examine topological properties and connectivity of more complex functionally-equivalent integrated circuits. The views expressed in this article are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense or the U.S. Government.

New strategy for drug discovery by large-scale association analysis of molecular networks of different species.

PubMed

Zhang, Bo; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Wu, Ziyin; Zhang, Wenjuan; Yang, Xiaoyan; Gong, Fukai; Li, Yuerong; Chen, Xiaoyu; Gao, Shuo; Chen, Xuetong; Li, Yan; Lu, Aiping; Wang, Yonghua

2016-02-25

The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.

Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.

PubMed

Dutta, Sangya; Kumar, Vinay; Shukla, Aditya; Mohapatra, Nihar R; Ganguly, Udayan

2017-08-15

Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~10 11 neuron based) large neural networks.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

RRAM-based hardware implementations of artificial neural networks: progress update and challenges ahead

NASA Astrophysics Data System (ADS)

Prezioso, M.; Merrikh-Bayat, F.; Chakrabarti, B.; Strukov, D.

2016-02-01

Artificial neural networks have been receiving increasing attention due to their superior performance in many information processing tasks. Typically, scaling up the size of the network results in better performance and richer functionality. However, large neural networks are challenging to implement in software and customized hardware are generally required for their practical implementations. In this work, we will discuss our group's recent efforts on the development of such custom hardware circuits, based on hybrid CMOS/memristor circuits, in particular of CMOL variety. We will start by reviewing the basics of memristive devices and of CMOL circuits. We will then discuss our recent progress towards demonstration of hybrid circuits, focusing on the experimental and theoretical results for artificial neural networks based on crossbarintegrated metal oxide memristors. We will conclude presentation with the discussion of the remaining challenges and the most pressing research needs.

High-gain AlGaAs/GaAs double heterojunction Darlington phototransistors for optical neural networks

NASA Technical Reports Server (NTRS)

Kim, Jae H. (Inventor); Lin, Steven H. (Inventor)

1991-01-01

High-gain MOCVD-grown (metal-organic chemical vapor deposition) AlGaAs/GaAs/AlGaAs n-p-n double heterojunction bipolar transistors (DHBTs) and Darlington phototransistor pairs are provided for use in optical neural networks and other optoelectronic integrated circuit applications. The reduced base doping level used results in effective blockage of Zn out-diffusion, enabling a current gain of 500, higher than most previously reported values for Zn-diffused-base DHBTs. Darlington phototransitor pairs of this material can achieve a current gain of over 6000, which satisfies the gain requirement for optical neural network designs, which advantageously may employ neurons comprising the Darlington phototransistor pairs in series with a light source.

Computerized power supply analysis: State equation generation and terminal models

NASA Technical Reports Server (NTRS)

Garrett, S. J.

1978-01-01

To aid engineers that design power supply systems two analysis tools that can be used with the state equation analysis package were developed. These tools include integration routines that start with the description of a power supply in state equation form and yield analytical results. The first tool uses a computer program that works with the SUPER SCEPTRE circuit analysis program and prints the state equation for an electrical network. The state equations developed automatically by the computer program are used to develop an algorithm for reducing the number of state variables required to describe an electrical network. In this way a second tool is obtained in which the order of the network is reduced and a simpler terminal model is obtained.

Understanding Biological Regulation Through Synthetic Biology.

PubMed

Bashor, Caleb J; Collins, James J

2018-05-20

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Method of forming through substrate vias (TSVs) and singulating and releasing die having the TSVs from a mechanical support substrate

DOEpatents

Okandan, Murat; Nielson, Gregory N

2014-12-09

Accessing a workpiece object in semiconductor processing is disclosed. The workpiece object includes a mechanical support substrate, a release layer over the mechanical support substrate, and an integrated circuit substrate coupled over the release layer. The integrated circuit substrate includes a device layer having semiconductor devices. The method also includes etching through-substrate via (TSV) openings through the integrated circuit substrate that have buried ends at or within the release layer including using the release layer as an etch stop. TSVs are formed by introducing one or more conductive materials into the TSV openings. A die singulation trench is etched at least substantially through the integrated circuit substrate around a perimeter of an integrated circuit die. The integrated circuit die is at least substantially released from the mechanical support substrate.

Electro-optical Probing Of Terahertz Integrated Circuits

NASA Technical Reports Server (NTRS)

Bhasin, K. B.; Romanofsky, R.; Whitaker, J. F.; Valdmanis, J. A.; Mourou, G.; Jackson, T. A.

1990-01-01

Electro-optical probe developed to perform noncontact, nondestructive, and relatively noninvasive measurements of electric fields over broad spectrum at millimeter and shorter wavelengths in integrated circuits. Manipulated with conventional intregrated-circuit-wafer-probing equipment and operated without any special preparation of integrated circuits. Tip of probe small electro-optical crystal serving as proximity electric-field sensor.

Monolithic Microwave Integrated Circuits Based on GaAs Mesfet Technology

NASA Astrophysics Data System (ADS)

Bahl, Inder J.

Advanced military microwave systems are demanding increased integration, reliability, radiation hardness, compact size and lower cost when produced in large volume, whereas the microwave commercial market, including wireless communications, mandates low cost circuits. Monolithic Microwave Integrated Circuit (MMIC) technology provides an economically viable approach to meeting these needs. In this paper the design considerations for several types of MMICs and their performance status are presented. Multifunction integrated circuits that advance the MMIC technology are described, including integrated microwave/digital functions and a highly integrated transceiver at C-band.

The Drosophila TRPA1 Channel and Neuronal Circuits Controlling Rhythmic Behaviours and Sleep in Response to Environmental Temperature.

PubMed

Roessingh, Sanne; Stanewsky, Ralf

2017-10-03

trpA1 encodes a thermosensitive transient receptor potential channel (TRP channel) that functions in selection of preferred temperatures and noxious heat avoidance. In this review, we discuss the evidence for a role of TRPA1 in the control of rhythmic behaviours in Drosophila melanogaster . Activity levels during the afternoon and rhythmic temperature preference are both regulated by TRPA1. In contrast, TRPA1 is dispensable for temperature synchronisation of circadian clocks. We discuss the neuronal basis of TRPA1-mediated temperature effects on rhythmic behaviours, and conclude that they are mediated by partly overlapping but distinct neuronal circuits. We have previously shown that TRPA1 is required to maintain siesta sleep under warm temperature cycles. Here, we present new data investigating the neuronal circuit responsible for this regulation. First, we discuss the difficulties that remain in identifying the responsible neurons. Second, we discuss the role of clock neurons (s-LNv/DN1 network) in temperature-driven regulation of siesta sleep, and highlight the role of TRPA1 therein. Finally, we discuss the sexual dimorphic nature of siesta sleep and propose that the s-LNv/DN1 clock network could play a role in the integration of environmental information, mating status and other internal drives, to appropriately drive adaptive sleep/wake behaviour.

Memristor-based cellular nonlinear/neural network: design, analysis, and applications.

PubMed

Duan, Shukai; Hu, Xiaofang; Dong, Zhekang; Wang, Lidan; Mazumder, Pinaki

2015-06-01

Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current-voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights.

IP voice over ATM satellite: experimental results over satellite channels

NASA Astrophysics Data System (ADS)

Saraf, Koroush A.; Butts, Norman P.

1999-01-01

IP telephony, a new technology to provide voice communication over traditional data networks, has the potential to revolutionize telephone communication within the modern enterprise. This innovation uses packetization techniques to carry voice conversations over IP networks. This packet switched technology promises new integrated services, and lower cost long-distance communication compared to traditional circuit switched telephone networks. Future satellites will need to carry IP traffic efficiently in order to stay competitive in servicing the global data- networking and global telephony infrastructure. However, the effects of Voice over IP over switched satellite channels have not been investigated in detail. To fully understand the effects of satellite channels on Voice over IP quality; several experiments were conducted at Lockheed Martin Telecommunications' Satellite Integration Lab. The result of those experiments along with suggested improvements for voice communication over satellite are presented in this document. First, a detailed introduction of IP telephony as a suitable technology for voice communication over future satellites is presented. This is followed by procedures for the experiments, along with results and strategies. In conclusion we hope that these capability demonstrations will alleviate any uncertainty regarding the applicability of this technology to satellite networks.

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.

PubMed

Cheung, Kit; Schultz, Simon R; Luk, Wayne

2015-01-01

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation.

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

PubMed Central

Cheung, Kit; Schultz, Simon R.; Luk, Wayne

2016-01-01

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation. PMID:26834542

Wide-band polarization controller for Si photonic integrated circuits.

PubMed

Velha, P; Sorianello, V; Preite, M V; De Angelis, G; Cassese, T; Bianchi, A; Testa, F; Romagnoli, M

2016-12-15

A circuit for the management of any arbitrary polarization state of light is demonstrated on an integrated silicon (Si) photonics platform. This circuit allows us to adapt any polarization into the standard fundamental TE mode of a Si waveguide and, conversely, to control the polarization and set it to any arbitrary polarization state. In addition, the integrated thermal tuning allows kilohertz speed which can be used to perform a polarization scrambler. The circuit was used in a WDM link and successfully used to adapt four channels into a standard Si photonic integrated circuit.

General technique for the integration of MIC/MMIC'S with waveguides

NASA Technical Reports Server (NTRS)

Geller, Bernard D. (Inventor); Zaghloul, Amir I. (Inventor)

1987-01-01

A technique for packaging and integrating of a microwave integrated circuit (MIC) or monolithic microwave integrated circuit (MMIC) with a waveguide uses a printed conductive circuit pattern on a dielectric substrate to transform impedance and mode of propagation between the MIC/MMIC and the waveguide. The virtually coplanar circuit pattern lies on an equipotential surface within the waveguide and therefore makes possible single or dual polarized mode structures.

Large Scale Integrated Circuits for Military Applications.

DTIC Science & Technology

1977-05-01

economic incentive for riarrowing this gap is examined, y (U)^wo"categories of cost are analyzed: the direct life cycle cost of the integrated circuit...dependence of these costs on the physical charac- teristics of the integrated circuits is discussed. (U) The economic and physical characteristics of... economic incentive for narrowing this gap is examined. Two categories of cost are analyzed: the direct life cycle cost of the integrated circuit

Biological 2-Input Decoder Circuit in Human Cells

PubMed Central

2015-01-01

Decoders are combinational circuits that convert information from n inputs to a maximum of 2n outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions. PMID:24694115

Biological 2-input decoder circuit in human cells.

PubMed

Guinn, Michael; Bleris, Leonidas

2014-08-15

Decoders are combinational circuits that convert information from n inputs to a maximum of 2(n) outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions.

Six networks on a universal neuromorphic computing substrate.

PubMed

Pfeil, Thomas; Grübl, Andreas; Jeltsch, Sebastian; Müller, Eric; Müller, Paul; Petrovici, Mihai A; Schmuker, Michael; Brüderle, Daniel; Schemmel, Johannes; Meier, Karlheinz

2013-01-01

In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

Six Networks on a Universal Neuromorphic Computing Substrate

PubMed Central

Pfeil, Thomas; Grübl, Andreas; Jeltsch, Sebastian; Müller, Eric; Müller, Paul; Petrovici, Mihai A.; Schmuker, Michael; Brüderle, Daniel; Schemmel, Johannes; Meier, Karlheinz

2013-01-01

In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality. PMID:23423583

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Error modelling of quantum Hall array resistance standards

NASA Astrophysics Data System (ADS)

Marzano, Martina; Oe, Takehiko; Ortolano, Massimo; Callegaro, Luca; Kaneko, Nobu-Hisa

2018-04-01

Quantum Hall array resistance standards (QHARSs) are integrated circuits composed of interconnected quantum Hall effect elements that allow the realization of virtually arbitrary resistance values. In recent years, techniques were presented to efficiently design QHARS networks. An open problem is that of the evaluation of the accuracy of a QHARS, which is affected by contact and wire resistances. In this work, we present a general and systematic procedure for the error modelling of QHARSs, which is based on modern circuit analysis techniques and Monte Carlo evaluation of the uncertainty. As a practical example, this method of analysis is applied to the characterization of a 1 MΩ QHARS developed by the National Metrology Institute of Japan. Software tools are provided to apply the procedure to other arrays.

The dialectic of Hebb and homeostasis.

PubMed

Turrigiano, Gina G

2017-03-05

It has become widely accepted that homeostatic and Hebbian plasticity mechanisms work hand in glove to refine neural circuit function. Nonetheless, our understanding of how these fundamentally distinct forms of plasticity compliment (and under some circumstances interfere with) each other remains rudimentary. Here, I describe some of the recent progress of the field, as well as some of the deep puzzles that remain. These include unravelling the spatial and temporal scales of different homeostatic and Hebbian mechanisms, determining which aspects of network function are under homeostatic control, and understanding when and how homeostatic and Hebbian mechanisms must be segregated within neural circuits to prevent interference.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'. © 2017 The Author(s).

Integrated circuits, and design and manufacture thereof

DOEpatents

Auracher, Stefan; Pribbernow, Claus; Hils, Andreas

2006-04-18

A representation of a macro for an integrated circuit layout. The representation may define sub-circuit cells of a module. The module may have a predefined functionality. The sub-circuit cells may include at least one reusable circuit cell. The reusable circuit cell may be configured such that when the predefined functionality of the module is not used, the reusable circuit cell is available for re-use.

MQW Optical Feedback Modulators And Phase Shifters

NASA Technical Reports Server (NTRS)

Jackson, Deborah J.

1995-01-01

Laser diodes equipped with proposed multiple-quantum-well (MQW) optical feedback modulators prove useful in variety of analog and digital optical-communication applications, including fiber-optic signal-distribution networks and high-speed, low-crosstalk interconnections among super computers or very-high-speed integrated circuits. Development exploits accompanying electro-optical aspect of QCSE - variation in index of refraction with applied electric field. Also exploits sensitivity of laser diodes to optical feedback. Approach is reverse of prior approach.

Cingulate, Frontal and Parietal Cortical Dysfunction in Attention-Deficit/Hyperactivity Disorder

PubMed Central

Bush, George

2011-01-01

Functional and structural neuroimaging have identified abnormalities of the brain that are likely to contribute to the neuropathophysiology of attention-deficit/hyperactivity disorder (ADHD). In particular, hypofunction of the brain regions comprising the cingulo-frontal-parietal (CFP) cognitive-attention network have been consistently observed across studies. These are major components of neural systems that are relevant to ADHD, including cognitive/attention networks, motor systems and reward/feedback-based processing systems. Moreover, these areas interact with other brain circuits that have been implicated in ADHD, such as the “default mode” resting state network. ADHD imaging data related to CFP network dysfunction will be selectively highlighted here to help facilitate its integration with the other information presented in this special issue. Together, these reviews will help shed light on the neurobiology of ADHD. PMID:21489409

Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions.

PubMed

Foo, Mathias; Sawlekar, Rucha; Kulkarni, Vishwesh V; Bates, Declan G

2016-08-01

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller. We compare the performance of the PI and SC controllers in closed-loop with a nonlinear second-order chemical process. Our results show that the SC controller outperforms the PI controller in terms of both performance and robustness, and also requires fewer abstract chemical reactions to implement, highlighting its potential usefulness in the construction of biomolecular control circuits.

High-efficiency power transfer for silicon-based photonic devices

NASA Astrophysics Data System (ADS)

Son, Gyeongho; Yu, Kyoungsik

2018-02-01

We demonstrate an efficient coupling of guided light of 1550 nm from a standard single-mode optical fiber to a silicon waveguide using the finite-difference time-domain method and propose a fabrication method of tapered optical fibers for efficient power transfer to silicon-based photonic integrated circuits. Adiabatically-varying fiber core diameters with a small tapering angle can be obtained using the tube etching method with hydrofluoric acid and standard single-mode fibers covered by plastic jackets. The optical power transmission of the fundamental HE11 and TE-like modes between the fiber tapers and the inversely-tapered silicon waveguides was calculated with the finite-difference time-domain method to be more than 99% at a wavelength of 1550 nm. The proposed method for adiabatic fiber tapering can be applied in quantum optics, silicon-based photonic integrated circuits, and nanophotonics. Furthermore, efficient coupling within the telecommunication C-band is a promising approach for quantum networks in the future.

Antenna-coupled Superconducting Bolometers for Observations of the Cosmic Microwave Background Polarization

NASA Astrophysics Data System (ADS)

Myers, Michael James

We describe the development of a novel millimeter-wave cryogenic detector. The device integrates a planar antenna, superconducting transmission line, bandpass filter, and bolometer onto a single silicon wafer. The bolometer uses a superconducting Transition-Edge Sensor (TES) thermistor, which provides substantial advantages over conventional semiconductor bolometers. The detector chip is fabricated using standard micro-fabrication techniques. This highly-integrated detector architecture is particularly well-suited for use in the de- velopment of polarization-sensitive cryogenic receivers with thousands of pixels. Such receivers are needed to meet the sensitivity requirements of next-generation cosmic microwave background polarization experiments. The design, fabrication, and testing of prototype array pixels are described. Preliminary considerations for a full array design are also discussed. A set of on-chip millimeter-wave test structures were developed to help understand the performance of our millimeter-wave microstrip circuits. These test structures produce a calibrated transmission measurement for an arbitrary two-port circuit using optical techniques, rather than a network analyzer. Some results of fabricated test structures are presented.

40-Gb/s directly-modulated photonic crystal lasers under optical injection-locking

NASA Astrophysics Data System (ADS)

Chen, Chin-Hui; Takeda, Koji; Shinya, Akihiko; Nozaki, Kengo; Sato, Tomonari; Kawaguchi, Yoshihiro; Notomi, Masaya; Matsuo, Shinji

2011-08-01

CMOS integrated circuits (IC) usually requires high data bandwidth for off-chip input/output (I/O) data transport with sufficiently low power consumption in order to overcome pin-count limitation. In order to meet future requirements of photonic network interconnect, we propose an optical output device based on an optical injection-locked photonic crystal (PhC) laser to realize low-power and high-speed off-chip interconnects. This device enables ultralow-power operation and is suitable for highly integrated photonic circuits because of its strong light-matter interaction in the PhC nanocavity and ultra-compact size. High-speed operation is achieved by using the optical injection-locking (OIL) technique, which has been shown as an effective means to enhance modulation bandwidth beyond the relaxation resonance frequency limit. In this paper, we report experimental results of the OIL-PhC laser under various injection conditions and also demonstrate 40-Gb/s large-signal direct modulation with an ultralow energy consumption of 6.6 fJ/bit.

Hardware Prototyping of Neural Network based Fetal Electrocardiogram Extraction

NASA Astrophysics Data System (ADS)

Hasan, M. A.; Reaz, M. B. I.

2012-01-01

The aim of this paper is to model the algorithm for Fetal ECG (FECG) extraction from composite abdominal ECG (AECG) using VHDL (Very High Speed Integrated Circuit Hardware Description Language) for FPGA (Field Programmable Gate Array) implementation. Artificial Neural Network that provides efficient and effective ways of separating FECG signal from composite AECG signal has been designed. The proposed method gives an accuracy of 93.7% for R-peak detection in FHR monitoring. The designed VHDL model is synthesized and fitted into Altera's Stratix II EP2S15F484C3 using the Quartus II version 8.0 Web Edition for FPGA implementation.

Silicon photonics integrated circuits: a manufacturing platform for high density, low power optical I/O's.

PubMed

Absil, Philippe P; Verheyen, Peter; De Heyn, Peter; Pantouvaki, Marianna; Lepage, Guy; De Coster, Jeroen; Van Campenhout, Joris

2015-04-06

Silicon photonics integrated circuits are considered to enable future computing systems with optical input-outputs co-packaged with CMOS chips to circumvent the limitations of electrical interfaces. In this paper we present the recent progress made to enable dense multiplexing by exploiting the integration advantage of silicon photonics integrated circuits. We also discuss the manufacturability of such circuits, a key factor for a wide adoption of this technology.

Reusable vibration resistant integrated circuit mounting socket

DOEpatents

Evans, Craig N.

1995-01-01

This invention discloses a novel form of socket for integrated circuits to be mounted on printed circuit boards. The socket uses a novel contact which is fabricated out of a bimetallic strip with a shape which makes the end of the strip move laterally as temperature changes. The end of the strip forms a barb which digs into an integrated circuit lead at normal temperatures and holds it firmly in the contact, preventing loosening and open circuits from vibration. By cooling the contact containing the bimetallic strip the barb end can be made to release so that the integrated circuit lead can be removed from the socket without damage either to the lead or to the socket components.

Macromodels of digital integrated circuits for program packages of circuit engineering design

NASA Astrophysics Data System (ADS)

Petrenko, A. I.; Sliusar, P. B.; Timchenko, A. P.

1984-04-01

Various aspects of the generation of macromodels of digital integrated circuits are examined, and their effective application in program packages of circuit engineering design is considered. Three levels of macromodels are identified, and the application of such models to the simulation of circuit outputs is discussed.

Neural dynamics for landmark orientation and angular path integration

PubMed Central

Seelig, Johannes D.; Jayaraman, Vivek

2015-01-01

Summary Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed flies walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body — a toroidal structure in the center of the fly brain. The population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity — a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors — network structures proposed to support the function of navigational brain circuits. PMID:25971509

Integrated coherent matter wave circuits

DOE PAGES

Ryu, C.; Boshier, M. G.

2015-09-21

An integrated coherent matter wave circuit is a single device, analogous to an integrated optical circuit, in which coherent de Broglie waves are created and then launched into waveguides where they can be switched, divided, recombined, and detected as they propagate. Applications of such circuits include guided atom interferometers, atomtronic circuits, and precisely controlled delivery of atoms. We report experiments demonstrating integrated circuits for guided coherent matter waves. The circuit elements are created with the painted potential technique, a form of time-averaged optical dipole potential in which a rapidly moving, tightly focused laser beam exerts forces on atoms through theirmore » electric polarizability. Moreover, the source of coherent matter waves is a Bose–Einstein condensate (BEC). Finally, we launch BECs into painted waveguides that guide them around bends and form switches, phase coherent beamsplitters, and closed circuits. These are the basic elements that are needed to engineer arbitrarily complex matter wave circuitry.« less

Electrical circuit modeling and analysis of microwave acoustic interaction with biological tissues.

PubMed

Gao, Fei; Zheng, Qian; Zheng, Yuanjin

2014-05-01

Numerical study of microwave imaging and microwave-induced thermoacoustic imaging utilizes finite difference time domain (FDTD) analysis for simulation of microwave and acoustic interaction with biological tissues, which is time consuming due to complex grid-segmentation and numerous calculations, not straightforward due to no analytical solution and physical explanation, and incompatible with hardware development requiring circuit simulator such as SPICE. In this paper, instead of conventional FDTD numerical simulation, an equivalent electrical circuit model is proposed to model the microwave acoustic interaction with biological tissues for fast simulation and quantitative analysis in both one and two dimensions (2D). The equivalent circuit of ideal point-like tissue for microwave-acoustic interaction is proposed including transmission line, voltage-controlled current source, envelop detector, and resistor-inductor-capacitor (RLC) network, to model the microwave scattering, thermal expansion, and acoustic generation. Based on which, two-port network of the point-like tissue is built and characterized using pseudo S-parameters and transducer gain. Two dimensional circuit network including acoustic scatterer and acoustic channel is also constructed to model the 2D spatial information and acoustic scattering effect in heterogeneous medium. Both FDTD simulation, circuit simulation, and experimental measurement are performed to compare the results in terms of time domain, frequency domain, and pseudo S-parameters characterization. 2D circuit network simulation is also performed under different scenarios including different sizes of tumors and the effect of acoustic scatterer. The proposed circuit model of microwave acoustic interaction with biological tissue could give good agreement with FDTD simulated and experimental measured results. The pseudo S-parameters and characteristic gain could globally evaluate the performance of tumor detection. The 2D circuit network enables the potential to combine the quasi-numerical simulation and circuit simulation in a uniform simulator for codesign and simulation of a microwave acoustic imaging system, bridging bioeffect study and hardware development seamlessly.

Methods of fabricating applique circuits

DOEpatents

Dimos, Duane B.; Garino, Terry J.

1999-09-14

Applique circuits suitable for advanced packaging applications are introduced. These structures are particularly suited for the simple integration of large amounts (many nanoFarads) of capacitance into conventional integrated circuit and multichip packaging technology. In operation, applique circuits are bonded to the integrated circuit or other appropriate structure at the point where the capacitance is required, thereby minimizing the effects of parasitic coupling. An immediate application is to problems of noise reduction and control in modern high-frequency circuitry.

The Influence of Vacuum Circuit Breakers and Different Motor Models on Switching Overvoltages in Motor Circuits

NASA Astrophysics Data System (ADS)

Wong, Cat S. M.; Snider, L. A.; Lo, Edward W. C.; Chung, T. S.

Switching of induction motors with vacuum circuit breakers continues to be a concern. In this paper the influence on statistical overvoltages of the stochastic characteristics of vacuum circuit breakers, high frequency models of motors and transformers, and network characteristics, including cable lengths and network topology are evaluated and a general view of the overvoltages phenomena is presented. Finally, a real case study on the statistical voltage levels and risk-of-failure resulting from switching of a vacuum circuit breaker in an industrial installation in Hong Kong is presented.

Optimizing the switching time for 400 kV SF6 circuit breakers

NASA Astrophysics Data System (ADS)

Ciulica, D.

2018-01-01

This paper presents real-time voltage and current analysis for optimizing the wave switching point of the circuit breaker SF6. Circuit Breaker plays an important role in power systems. It provides protection for equipment in embedded stations in transport networks. SF6 Circuit Breaker is very important equipment in Power Systems, which is used for up to 400 kV due to its excellent performance. The controlled switching is used to eliminate transient modes and electrodynamic and dielectric charges in the network at manual switching of capacitor, shunt reactors and power transformers. These effects reduce the reliability and lifetime of the equipment installed on the network, or may lead to erroneous protection.

Electrical Design and Evaluation of Asynchronous Serial Bus Communication Network of 48 Sensor Platform LSIs with Single-Ended I/O for Integrated MEMS-LSI Sensors

PubMed Central

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki

2018-01-01

For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we have developed a dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) (referred to as “sensor platform LSI”) for bus-networked Micro-Electro-Mechanical-Systems (MEMS)-LSI integrated sensors. In this LSI, collision avoidance, adaptation and event-driven functions are simply implemented to relieve data collision and congestion in asynchronous serial bus communication. In this study, we developed a network system with 48 sensor platform LSIs based on Printed Circuit Board (PCB) in a backbone bus topology with the bus length being 2.4 m. We evaluated the serial communication performance when 48 LSIs operated simultaneously with the adaptation function. The number of data packets received from each LSI was almost identical, and the average sampling frequency of 384 capacitance channels (eight for each LSI) was 73.66 Hz. PMID:29342923

Australian national networked tele-test facility for integrated systems

NASA Astrophysics Data System (ADS)

Eshraghian, Kamran; Lachowicz, Stefan W.; Eshraghian, Sholeh

2001-11-01

The Australian Commonwealth government recently announced a grant of 4.75 million as part of a 13.5 million program to establish a world class networked IC tele-test facility in Australia. The facility will be based on a state-of-the-art semiconductor tester located at Edith Cowan University in Perth that will operate as a virtual centre spanning Australia. Satellite nodes will be located at the University of Western Australia, Griffith University, Macquarie University, Victoria University and the University of Adelaide. The facility will provide vital equipment to take Australia to the frontier of critically important and expanding fields in microelectronics research and development. The tele-test network will provide state of the art environment for the electronics and microelectronics research and the industry community around Australia to test and prototype Very Large Scale Integrated (VLSI) circuits and other System On a Chip (SOC) devices, prior to moving to the manufacturing stage. Such testing is absolutely essential to ensure that the device performs to specification. This paper presents the current context in which the testing facility is being established, the methodologies behind the integration of design and test strategies and the target shape of the tele-testing Facility.

Noise isolation system for high-speed circuits

DOEpatents

McNeilly, D.R.

1983-12-29

A noise isolation circuit is provided that consists of a dual function bypass which confines high-speed switching noise to the component or circuit which generates it and isolates the component or circuit from high-frequency noise transients which may be present on the ground and power supply busses. A local circuit ground is provided which is coupled to the system ground by sufficient impedance to force the dissipation of the noise signal in the local circuit or component generating the noise. The dual function bypass network couples high-frequency noise signals generated in the local component or circuit through a capacitor to the local ground while isolating the component or circuit from noise signals which may be present on the power supply busses or system ground. The network is an effective noise isolating system and is applicable to both high-speed analog and digital circuits.

Noise isolation system for high-speed circuits

DOEpatents

McNeilly, David R.

1986-01-01

A noise isolation circuit is provided that consists of a dual function bypass which confines high-speed switching noise to the component or circuit which generates it and isolates the component or circuit from high-frequency noise transients which may be present on the ground and power supply busses. A local circuit ground is provided which is coupled to the system ground by sufficient impedance to force the dissipation of the noise signal in the local circuit or component generating the noise. The dual function bypass network couples high-frequency noise signals generated in the local component or circuit through a capacitor to the local ground while isolating the component or circuit from noise signals which may be present on the power supply busses or system ground. The network is an effective noise isolating system and is applicable to both high-speed analog and digital circuits.

Lighting the Blue Touchpaper for UK e-Science - Closing Conference of ESLEA Project. ESLEA, March 26-28, 2007, Edinburgh

NASA Astrophysics Data System (ADS)

Clarke, Peter; Davenhall, Clive; Greenwood, Colin; Strong, Matthew

ESLEA, an EPSRC-funded project, aims to demonstrate the potential benefits of circuit-switched optical networks (lightpaths) to the UK e-Science community. This is being achieved by running a number of "proof of benefit" pilot applications over UKLight, the UK's first national optical research network. UKLight provides a new way for researchers to obtain dedicated "lightpaths" between remote sites and to deploy and test novel networking methods and technologies. It facilitates collaboration on global projects by providing a point of access to the fast growing international optical R&D infrastructure. A diverse range of data-intensive fields of academic endeavour are participating in the ESLEA project; all these groups require the integration of high-bandwidth switched lightpath circuits into their experimental and analysis infrastructure for international transport of high-volume applications data. In addition, network protocol research and development of circuit reservation mechanisms has been carried out to help the pilot applications to exploit the UKLight infrastructure effectively. Further information about ESLEA can be viewed at www.eslea.uklight.ac.uk. ESLEA activities are now coming to an end and work will finish from February to July 2007, depending upon the terms of funding of each pilot application. The first quarter of 2007 is considered the optimum time to hold a closing conference for the project. The objectives of the conference are to: 1. Provide a forum for the dissemination of research findings and learning experiences from the ESLEA project. 2. Enable colleagues from the UK and international e-Science communities to present, discuss and learn about the latest developments in networking technology. 3. Raise awareness about the deployment of the UKLight infrastructure and its relationship to SuperJANET 5. 4. Identify potential uses of UKLight by existing or future research projects

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer’s Disease

PubMed Central

Dulla, Chris G.; Coulter, Douglas A.; Ziburkus, Jokubas

2015-01-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer’s disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. PMID:25948650

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer's Disease.

PubMed

Dulla, Chris G; Coulter, Douglas A; Ziburkus, Jokubas

2016-06-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer's disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. © The Author(s) 2015.

Switching-type regulator circuit has increased efficiency

NASA Technical Reports Server (NTRS)

Clapp, W. M.

1967-01-01

Switching series regulator circuit uses an inductive network to feed most of the current applied to the control circuit to the load. This circuit eliminates resistive losses and the need for heat sinks.

Auto-programmable impulse neural circuits

NASA Technical Reports Server (NTRS)

Watula, D.; Meador, J.

1990-01-01

Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

A network thermodynamic two-port element to represent the coupled flow of salt and current. Improved alternative for the equivalent circuit.

PubMed Central

Mikulecky, D C

1979-01-01

A two-port for coupled salt and current flow is created by using the network thermodynamic approach in the same manner as that for coupled solute and volume flow (Mikulecky et al., 1977b; Mikulecky, 1977). This electrochemical two-port has distinct advantages over the equivalent circuit representation and overcomes difficulties pointed out by Finkelstein and Mauro (1963). The electrochemical two-port is used to produce a schematic diagram of the coupled flows through a tissue. The network is superimposable on the tissue morphology and preserves the physical qualities of the flows and forces in each part of an organized structure (e.g., an epithelium). The topological properties are manipulated independently from the constitutive (flow-force) relations. The constitutive relations are chosen from a number of alternatives depending on the detail and rigor desired. With the topology and constitutive parameters specified, the steady-state behavior is simulated with a network simulation program. By using capacitance to represent the filling and depletion of compartments, as well as the traditional electrical capacitances, time-dependent behavior is also simulated. Nonlinear effects arising from the integration of equations describing local behavior (e.g., the Nernst-Planck equations) are dealt with explicitly. The network thermodynamic approach provides a simple, straightforward method for representing a system diagrammatically and then simulating the system's behavior from the diagram with a minimum of mathematical manipulation. PMID:262391

Imbalance aware lithography hotspot detection: a deep learning approach

NASA Astrophysics Data System (ADS)

Yang, Haoyu; Luo, Luyang; Su, Jing; Lin, Chenxi; Yu, Bei

2017-03-01

With the advancement of VLSI technology nodes, light diffraction caused lithographic hotspots have become a serious problem affecting manufacture yield. Lithography hotspot detection at the post-OPC stage is imperative to check potential circuit failures when transferring designed patterns onto silicon wafers. Although conventional lithography hotspot detection methods, such as machine learning, have gained satisfactory performance, with extreme scaling of transistor feature size and more and more complicated layout patterns, conventional methodologies may suffer from performance degradation. For example, manual or ad hoc feature extraction in a machine learning framework may lose important information when predicting potential errors in ultra-large-scale integrated circuit masks. In this paper, we present a deep convolutional neural network (CNN) targeting representative feature learning in lithography hotspot detection. We carefully analyze impact and effectiveness of different CNN hyper-parameters, through which a hotspot-detection-oriented neural network model is established. Because hotspot patterns are always minorities in VLSI mask design, the training data set is highly imbalanced. In this situation, a neural network is no longer reliable, because a trained model with high classification accuracy may still suffer from high false negative results (missing hotspots), which is fatal in hotspot detection problems. To address the imbalance problem, we further apply minority upsampling and random-mirror flipping before training the network. Experimental results show that our proposed neural network model achieves highly comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

Modeling neural circuits in Parkinson's disease.

PubMed

Psiha, Maria; Vlamos, Panayiotis

2015-01-01

Parkinson's disease (PD) is caused by abnormal neural activity of the basal ganglia which are connected to the cerebral cortex in the brain surface through complex neural circuits. For a better understanding of the pathophysiological mechanisms of PD, it is important to identify the underlying PD neural circuits, and to pinpoint the precise nature of the crucial aberrations in these circuits. In this paper, the general architecture of a hybrid Multilayer Perceptron (MLP) network for modeling the neural circuits in PD is presented. The main idea of the proposed approach is to divide the parkinsonian neural circuitry system into three discrete subsystems: the external stimuli subsystem, the life-threatening events subsystem, and the basal ganglia subsystem. The proposed model, which includes the key roles of brain neural circuit in PD, is based on both feed-back and feed-forward neural networks. Specifically, a three-layer MLP neural network with feedback in the second layer was designed. The feedback in the second layer of this model simulates the dopamine modulatory effect of compacta on striatum.

Auditory-motor interaction revealed by fMRI: speech, music, and working memory in area Spt.

PubMed

Hickok, Gregory; Buchsbaum, Bradley; Humphries, Colin; Muftuler, Tugan

2003-07-01

The concept of auditory-motor interaction pervades speech science research, yet the cortical systems supporting this interface have not been elucidated. Drawing on experimental designs used in recent work in sensory-motor integration in the cortical visual system, we used fMRI in an effort to identify human auditory regions with both sensory and motor response properties, analogous to single-unit responses in known visuomotor integration areas. The sensory phase of the task involved listening to speech (nonsense sentences) or music (novel piano melodies); the "motor" phase of the task involved covert rehearsal/humming of the auditory stimuli. A small set of areas in the superior temporal and temporal-parietal cortex responded both during the listening phase and the rehearsal/humming phase. A left lateralized region in the posterior Sylvian fissure at the parietal-temporal boundary, area Spt, showed particularly robust responses to both phases of the task. Frontal areas also showed combined auditory + rehearsal responsivity consistent with the claim that the posterior activations are part of a larger auditory-motor integration circuit. We hypothesize that this circuit plays an important role in speech development as part of the network that enables acoustic-phonetic input to guide the acquisition of language-specific articulatory-phonetic gestures; this circuit may play a role in analogous musical abilities. In the adult, this system continues to support aspects of speech production, and, we suggest, supports verbal working memory.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

PubMed

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

The evolvability of programmable hardware

PubMed Central

Raman, Karthik; Wagner, Andreas

2011-01-01

In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected ‘neutral networks’ in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 1045 logic circuits (‘genotypes’) and 1019 logic functions (‘phenotypes’). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry. PMID:20534598

Software defined network architecture based research on load balancing strategy

NASA Astrophysics Data System (ADS)

You, Xiaoqian; Wu, Yang

2018-05-01

As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.

Performance Evaluation and Control of Distributed Computer Communication Networks.

DTIC Science & Technology

1984-09-01

including: L. Clare, L.A. De Moraes, J. Baker, M. Zuckerman, S. Katz, P. Rodrigues, R. Pazos , S. Resheff. Other participants are the following visiting...investigations have been reported in reference (1) and (2) below. References (1) M. Gerla, R. Pazos -Rangel "Bandwidth Allocation and Routing in ISDN’s," IEEE...and efficient methods for its solution are presented. (2) R.A. Pazos -Rangel "Evaluation and Design of Integrated Packet Switching and Circuit Switching

Medium scale carbon nanotube thin film integrated circuits on flexible plastic substrates

DOEpatents

Rogers, John A; Cao, Qing; Alam, Muhammad; Pimparkar, Ninad

2015-02-03

The present invention provides device components geometries and fabrication strategies for enhancing the electronic performance of electronic devices based on thin films of randomly oriented or partially aligned semiconducting nanotubes. In certain aspects, devices and methods of the present invention incorporate a patterned layer of randomly oriented or partially aligned carbon nanotubes, such as one or more interconnected SWNT networks, providing a semiconductor channel exhibiting improved electronic properties relative to conventional nanotubes-based electronic systems.

Critical Problems in Very Large Scale Computer Systems

DTIC Science & Technology

1990-03-31

Srinivas Devadas (617) 253-0454 Thomas F. Knight, Jr. (617) 253-7807 F. Thomson Leighton (617) 253-3662 Charles E. Leiserson (617) 253-5833 Jacob K...Aided Design of Integrated Circuits and Systems, pages 19-29, January 1990. [5] S. Arora, T. Leighton, and B . Maggs. On-line algorithms for path...selection in a non-blocking network. In Proceedings of the 21st Annual ACM Symposium on Theory of Computing, May 1990. To appear. [6] P. Ashar, S. Devadas

Circuit for Communication Over Power Lines

NASA Technical Reports Server (NTRS)

Krasowski, Michael J.; Prokop, Normal F.; Greer, Lawrence C., III; Nappier, Jennifer

2011-01-01

Many distributed systems share common sensors and instruments along with a common power line supplying current to the system. A communication technique and circuit has been developed that allows for the simple inclusion of an instrument, sensor, or actuator node within any system containing a common power bus. Wherever power is available, a node can be added, which can then draw power for itself, its associated sensors, and actuators from the power bus all while communicating with other nodes on the power bus. The technique modulates a DC power bus through capacitive coupling using on-off keying (OOK), and receives and demodulates the signal from the DC power bus through the same capacitive coupling. The circuit acts as serial modem for the physical power line communication. The circuit and technique can be made of commercially available components or included in an application specific integrated circuit (ASIC) design, which allows for the circuit to be included in current designs with additional circuitry or embedded into new designs. This device and technique moves computational, sensing, and actuation abilities closer to the source, and allows for the networking of multiple similar nodes to each other and to a central processor. This technique also allows for reconfigurable systems by adding or removing nodes at any time. It can do so using nothing more than the in situ power wiring of the system.

Tribotronic Tuning Diode for Active Analog Signal Modulation.

PubMed

Zhou, Tao; Yang, Zhi Wei; Pang, Yaokun; Xu, Liang; Zhang, Chi; Wang, Zhong Lin

2017-01-24

Realizing active interaction with external environment/stimuli is a great challenge for current electronics. In this paper, a tribotronic tuning diode (TTD) is proposed by coupling a variable capacitance diode and a triboelectric nanogenerator in free-standing sliding mode. When the friction layer is sliding on the device surface for electrification, a reverse bias voltage is created and applied to the diode for tuning the junction capacitance. When the sliding distance increases from 0 to 25 mm, the capacitance of the TTD decreases from about 39 to 8 pF. The proposed TTD has been integrated into analog circuits and exhibited excellent performances in frequency modulation, phase shift, and filtering by sliding a finger. This work has demonstrated tunable diode and active analog signal modulation by tribotronics, which has great potential to replace ordinary variable capacitance diodes in various practical applications such as signal processing, electronic tuning circuits, precise tuning circuits, active sensor networks, electronic communications, remote controls, flexible electronics, etc.

A Q-band low noise GaAs pHEMT MMIC power amplifier for pulse electron spin resonance spectrometer

NASA Astrophysics Data System (ADS)

Sitnikov, A.; Kalabukhova, E.; Oliynyk, V.; Kolisnichenko, M.

2017-05-01

We present the design and development of a single stage pulse power amplifier working in the frequency range 32-38 GHz based on a monolithic microwave integrated circuit (MMIC). We have designed the MMIC power amplifier by using the commercially available packaged GaAs pseudomorphic high electron mobility transistor. The circuit fabrication and assembly process includes the elaboration of the matching networks for the MMIC power amplifier and their assembling as well as the topology outline and fabrication of the printed circuit board of the waveguide-microstrip line transitions. At room ambient temperature, the measured peak output power from the prototype amplifier is 35.5 dBm for 16.6 dBm input driving power, corresponding to 19 dB gain. The measured rise/fall time of the output microwave signal modulated by a high-speed PIN diode was obtained as 5-6 ns at 20-250 ns pulse width with 100 kHz pulse repetition rate frequency.

A Q-band low noise GaAs pHEMT MMIC power amplifier for pulse electron spin resonance spectrometer.

PubMed

Sitnikov, A; Kalabukhova, E; Oliynyk, V; Kolisnichenko, M

2017-05-01

We present the design and development of a single stage pulse power amplifier working in the frequency range 32-38 GHz based on a monolithic microwave integrated circuit (MMIC). We have designed the MMIC power amplifier by using the commercially available packaged GaAs pseudomorphic high electron mobility transistor. The circuit fabrication and assembly process includes the elaboration of the matching networks for the MMIC power amplifier and their assembling as well as the topology outline and fabrication of the printed circuit board of the waveguide-microstrip line transitions. At room ambient temperature, the measured peak output power from the prototype amplifier is 35.5 dBm for 16.6 dBm input driving power, corresponding to 19 dB gain. The measured rise/fall time of the output microwave signal modulated by a high-speed PIN diode was obtained as 5-6 ns at 20-250 ns pulse width with 100 kHz pulse repetition rate frequency.

Hormonal gain control of a medial preoptic area social reward circuit

PubMed Central

McHenry, Jenna A.; Otis, James M.; Rossi, Mark A.; Robinson, J. Elliott; Kosyk, Oksana; Miller, Noah W.; McElligott, Zoe A.; Budygin, Evgeny A.; Rubinow, David R.; Stuber, Garret D.

2017-01-01

Neural networks that control reproduction must integrate social and hormonal signals, tune motivation, and invigorate social interactions. However, the neurocircuit mechanisms for these processes remain unresolved. The medial preoptic area (mPOA), an essential node for social behaviors and is comprised of molecularly-diverse neurons with widespread projections. Here, we identify a steroid-responsive subset of neurotensin (Nts) expressing mPOA neurons that interface with the ventral tegmental area (VTA) to form a socially-engaged reward circuit. Using in vivo 2-photon imaging in female mice, we show that mPOANts neurons preferentially encode attractive male cues compared to non-social appetitive stimuli. Ovarian hormone signals regulate both the physiological and cue encoding properties of these cells. Furthermore, optogenetic stimulation of mPOANts-VTA circuitry promotes rewarding phenotypes, social approach, and striatal dopamine release. Collectively, these data demonstrate that steroid-sensitive mPOA neurons encode ethologically-relevant stimuli and co-opt midbrain reward circuits to promote prosocial behavior critical for species survival. PMID:28135243

Efficient Probabilistic Diagnostics for Electrical Power Systems

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Chavira, Mark; Cascio, Keith; Poll, Scott; Darwiche, Adnan; Uckun, Serdar

2008-01-01

We consider in this work the probabilistic approach to model-based diagnosis when applied to electrical power systems (EPSs). Our probabilistic approach is formally well-founded, as it based on Bayesian networks and arithmetic circuits. We investigate the diagnostic task known as fault isolation, and pay special attention to meeting two of the main challenges . model development and real-time reasoning . often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-to-use speci.cation language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In essence, we introduce a high-level EPS speci.cation language from which Bayesian networks that can diagnose multiple simultaneous failures are auto-generated, and we illustrate the feasibility of using arithmetic circuits, compiled from Bayesian networks, for real-time diagnosis on real-world EPSs of interest to NASA. The experimental system is a real-world EPS, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. In experiments with the ADAPT Bayesian network, which currently contains 503 discrete nodes and 579 edges, we .nd high diagnostic accuracy in scenarios where one to three faults, both in components and sensors, were inserted. The time taken to compute the most probable explanation using arithmetic circuits has a small mean of 0.2625 milliseconds and standard deviation of 0.2028 milliseconds. In experiments with data from ADAPT we also show that arithmetic circuit evaluation substantially outperforms joint tree propagation and variable elimination, two alternative algorithms for diagnosis using Bayesian network inference.

Differential transimpedance amplifier circuit for correlated differential amplification

DOEpatents

Gresham, Christopher A [Albuquerque, NM; Denton, M Bonner [Tucson, AZ; Sperline, Roger P [Tucson, AZ

2008-07-22

A differential transimpedance amplifier circuit for correlated differential amplification. The amplifier circuit increase electronic signal-to-noise ratios in charge detection circuits designed for the detection of very small quantities of electrical charge and/or very weak electromagnetic waves. A differential, integrating capacitive transimpedance amplifier integrated circuit comprising capacitor feedback loops performs time-correlated subtraction of noise.

Electronic bidirectional valve circuit prevents crossover distortion and threshold effect

NASA Technical Reports Server (NTRS)

Kernick, A.

1966-01-01

Four-terminal network forms a bidirectional valve which will switch or alternate an ac signal without crossover distortion or threshold effect. In this network, an isolated control signal is sufficient for circuit turn-on.

Conic section function neural network circuitry for offline signature recognition.

PubMed

Erkmen, Burcu; Kahraman, Nihan; Vural, Revna A; Yildirim, Tulay

2010-04-01

In this brief, conic section function neural network (CSFNN) circuitry was designed for offline signature recognition. CSFNN is a unified framework for multilayer perceptron (MLP) and radial basis function (RBF) networks to make simultaneous use of advantages of both. The CSFNN circuitry architecture was developed using a mixed mode circuit implementation. The designed circuit system is problem independent. Hence, the general purpose neural network circuit system could be applied to various pattern recognition problems with different network sizes on condition with the maximum network size of 16-16-8. In this brief, CSFNN circuitry system has been applied to two different signature recognition problems. CSFNN circuitry was trained with chip-in-the-loop learning technique in order to compensate typical analog process variations. CSFNN hardware achieved highly comparable computational performances with CSFNN software for nonlinear signature recognition problems.

Design and construction of a VHGT-attached WDM-type triplex transceiver module using polymer PLC hybrid integration technology

NASA Astrophysics Data System (ADS)

Jerábek, Vitezslav; Hüttel, Ivan; Prajzler, Václav; Busek, K.; Seliger, P.

2008-11-01

We report about design and construction of the bidirectional transceiver TRx module for subscriber part of the passive optical network PON for a fiber to the home FTTH topology. The TRx module consists of a epoxy novolak resin polymer planar lightwave circuit (PLC) hybrid integration technology with volume holographic grating triplex filter VHGT, surface-illuminated photodetectors and spot-size converted Fabry-Pérot laser diode in SMD package. The hybrid PLC has composed from a two parts-polymer optical waveguide including VHGT filter section and a optoelectronic microwave section. The both parts are placed on the composite substrate.

High-density interconnect substrates and device packaging using conductive composites

NASA Astrophysics Data System (ADS)

Gandhi, Pradeep; Gallagher, Catherine; Matijasevic, Goran

1998-02-01

High-end printed circuit board manufacturing technology is receiving increasing attention due to higher functionality in smaller form factors. This is evident from the industry efforts to produced reliable microvias and related trace features to pack as much circuit density as possible. Cost, density and performance requirements have prodded entry into a market that was mainly reserved for ceramic and molded packages for the last forty years. To successfully meet the demanding specifications of this market segment, a worldwide effort is underway for the development of new materials, processes and equipment. A novel base technology that is applicable to most of the major packaging and redistribution elements in an electronic module is presented.High density multilayer circuits with landless blind and buried vias can be fabricated by filling the conductor paste into photoimaged dielectrics and thermally processing it at a relatively lower temperature. Via layers are prepared directly on the inherently planarized circuit layer in an identical fashion. Because these composite materials are applied in an additive fabrication method, metal substrates can be employed for high thermal dissipation and excellent CTE control over a wide temperature range. The conductor material is based on interpenetrating polymer and metal networks that are formed in situ from metal particles and a thermosetting flux/binder. The metal network is formed when the alloy particles melt and react with adjacent high melting point metal particle. Interaction also occurs between the alloy particles and pad, lead or previous trace metallizations provided they are solderable by alloys of tin. The new alloy composition created by the interdiffusion process within the bulk material has a higher melting point than the original alloy and thus solidifies immediately upon formation. This metallurgical reaction, known as transient liquid phase sintering, is facilitated by the polymer mixture. INtegration of the polymer and metal networks is maintained by utilizing a thermosetting polymer system that cures simultaneously with the metallurgical reaction. Although similar in concept and performance to cermet inks, these compositions differ in that their process temperatures are compatible with conventional printed wiring board materials and that the polymeric binder remains to provide adhesion and fatigue resistance to the metallurgical network.

A photonic circuit for complementary frequency shifting, in-phase quadrature/single sideband modulation and frequency multiplication: analysis and integration feasibility

NASA Astrophysics Data System (ADS)

Hasan, Mehedi; Hu, Jianqi; Nikkhah, Hamdam; Hall, Trevor

2017-08-01

A novel photonic integrated circuit architecture for implementing orthogonal frequency division multiplexing by means of photonic generation of phase-correlated sub-carriers is proposed. The circuit can also be used for implementing complex modulation, frequency up-conversion of the electrical signal to the optical domain and frequency multiplication. The principles of operation of the circuit are expounded using transmission matrices and the predictions of the analysis are verified by computer simulation using an industry-standard software tool. Non-ideal scenarios that may affect the correct function of the circuit are taken into consideration and quantified. The discussion of integration feasibility is illustrated by a photonic integrated circuit that has been fabricated using 'library' components and which features most of the elements of the proposed circuit architecture. The circuit is found to be practical and may be fabricated in any material platform that offers a linear electro-optic modulator such as organic or ferroelectric thin films hybridized with silicon photonics.

Neuromorphic photonic networks using silicon photonic weight banks.

PubMed

Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

2017-08-07

Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

An Exploratory Study Examining the Feasibility of Using Bayesian Networks to Predict Circuit Analysis Understanding

ERIC Educational Resources Information Center

Chung, Gregory K. W. K.; Dionne, Gary B.; Kaiser, William J.

2006-01-01

Our research question was whether we could develop a feasible technique, using Bayesian networks, to diagnose gaps in student knowledge. Thirty-four college-age participants completed tasks designed to measure conceptual knowledge, procedural knowledge, and problem-solving skills related to circuit analysis. A Bayesian network was used to model…

Network model and short circuit program for the Kennedy Space Center electric power distribution system

NASA Technical Reports Server (NTRS)

1976-01-01

Assumptions made and techniques used in modeling the power network to the 480 volt level are discussed. Basic computational techniques used in the short circuit program are described along with a flow diagram of the program and operational procedures. Procedures for incorporating network changes are included in this user's manual.

Interplay between Short- and Long-Term Plasticity in Cell-Assembly Formation

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2014-01-01

Various hippocampal and neocortical synapses of mammalian brain show both short-term plasticity and long-term plasticity, which are considered to underlie learning and memory by the brain. According to Hebb’s postulate, synaptic plasticity encodes memory traces of past experiences into cell assemblies in cortical circuits. However, it remains unclear how the various forms of long-term and short-term synaptic plasticity cooperatively create and reorganize such cell assemblies. Here, we investigate the mechanism in which the three forms of synaptic plasticity known in cortical circuits, i.e., spike-timing-dependent plasticity (STDP), short-term depression (STD) and homeostatic plasticity, cooperatively generate, retain and reorganize cell assemblies in a recurrent neuronal network model. We show that multiple cell assemblies generated by external stimuli can survive noisy spontaneous network activity for an adequate range of the strength of STD. Furthermore, our model predicts that a symmetric temporal window of STDP, such as observed in dopaminergic modulations on hippocampal neurons, is crucial for the retention and integration of multiple cell assemblies. These results may have implications for the understanding of cortical memory processes. PMID:25007209

Network motifs – recurring circuitry components in biological systems

EPA Science Inventory

Environmental perturbations, elicited by chemicals, dietary supplements, and drugs, can alter the dynamics of the molecular circuits and networks operating in cells, leading to multiple disease endpoints. Multi-component signal transduction pathways and gene regulatory circuits u...

A Network Thermodynamic Approach to Compartmental Analysis

PubMed Central

Mikulecky, D. C.; Huf, E. G.; Thomas, S. R.

1979-01-01

We introduce a general network thermodynamic method for compartmental analysis which uses a compartmental model of sodium flows through frog skin as an illustrative example (Huf and Howell, 1974a). We use network thermodynamics (Mikulecky et al., 1977b) to formulate the problem, and a circuit simulation program (ASTEC 2, SPICE2, or PCAP) for computation. In this way, the compartment concentrations and net fluxes between compartments are readily obtained for a set of experimental conditions involving a square-wave pulse of labeled sodium at the outer surface of the skin. Qualitative features of the influx at the outer surface correlate very well with those observed for the short circuit current under another similar set of conditions by Morel and LeBlanc (1975). In related work, the compartmental model is used as a basis for simulation of the short circuit current and sodium flows simultaneously using a two-port network (Mikulecky et al., 1977a, and Mikulecky et al., A network thermodynamic model for short circuit current transients in frog skin. Manuscript in preparation; Gary-Bobo et al., 1978). The network approach lends itself to computation of classic compartmental problems in a simple manner using circuit simulation programs (Chua and Lin, 1975), and it further extends the compartmental models to more complicated situations involving coupled flows and non-linearities such as concentration dependencies, chemical reaction kinetics, etc. PMID:262387

Network thermodynamic approach compartmental analysis. Na+ transients in frog skin.

PubMed

Mikulecky, D C; Huf, E G; Thomas, S R

1979-01-01

We introduce a general network thermodynamic method for compartmental analysis which uses a compartmental model of sodium flows through frog skin as an illustrative example (Huf and Howell, 1974a). We use network thermodynamics (Mikulecky et al., 1977b) to formulate the problem, and a circuit simulation program (ASTEC 2, SPICE2, or PCAP) for computation. In this way, the compartment concentrations and net fluxes between compartments are readily obtained for a set of experimental conditions involving a square-wave pulse of labeled sodium at the outer surface of the skin. Qualitative features of the influx at the outer surface correlate very well with those observed for the short circuit current under another similar set of conditions by Morel and LeBlanc (1975). In related work, the compartmental model is used as a basis for simulation of the short circuit current and sodium flows simultaneously using a two-port network (Mikulecky et al., 1977a, and Mikulecky et al., A network thermodynamic model for short circuit current transients in frog skin. Manuscript in preparation; Gary-Bobo et al., 1978). The network approach lends itself to computation of classic compartmental problems in a simple manner using circuit simulation programs (Chua and Lin, 1975), and it further extends the compartmental models to more complicated situations involving coupled flows and non-linearities such as concentration dependencies, chemical reaction kinetics, etc.

Selective Processing Techniques for Electronics and Opto-Electronic Applications: Quantum-Well Devices and Integrated Optic Circuits

DTIC Science & Technology

1993-02-10

new technology is to have sufficient control of processing to *- describable by an appropriate elecromagnetic model . build useful devices. For example...3. W aveguide Modulators .................................. 7 B. Integrated Optical Device and Circuit Modeling ... ................... .. 10 C...following categories: A. Integrated Optical Devices and Technology B. Integrated Optical Device and Circuit Modeling C. Cryogenic Etching for Low

Semicustom integrated circuits and the standard transistor array radix (STAR)

NASA Technical Reports Server (NTRS)

Edge, T. M.

1977-01-01

The development, application, pros and cons of the semicustom and custom approach to the integration of circuits are described. Improvements in terms of cost, reliability, secrecy, power, and size reduction are examined. Also presented is the standard transistor array radix, a semicustom approach to digital integrated circuits that offers the advantages of both custom and semicustom approaches to integration.

Subsurface microscopy of interconnect layers of an integrated circuit.

PubMed

Köklü, F Hakan; Unlü, M Selim

2010-01-15

We apply the NA-increasing lens technique to confocal and wide-field backside microscopy of integrated circuits. We demonstrate 325 nm (lambda(0)/4) lateral spatial resolution while imaging metal structures located inside the interconnect layer of an integrated circuit. Vectorial field calculations are presented justifying our findings.

Postirradiation Effects In Integrated Circuits

NASA Technical Reports Server (NTRS)

Shaw, David C.; Barnes, Charles E.

1993-01-01

Two reports discuss postirradiation effects in integrated circuits. Presents examples of postirradiation measurements of performances of integrated circuits of five different types: dual complementary metal oxide/semiconductor (CMOS) flip-flop; CMOS analog multiplier; two CMOS multiplying digital-to-analog converters; electrically erasable programmable read-only memory; and semiconductor/oxide/semiconductor octal buffer driver.

76 FR 14688 - In the Matter of Certain Large Scale Integrated Circuit Semiconductor Chips and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-17

... Integrated Circuit Semiconductor Chips and Products Containing the Same; Notice of a Commission Determination... certain large scale integrated circuit semiconductor chips and products containing same by reason of... existence of a domestic industry. The Commission's notice of investigation named several respondents...

77 FR 25747 - Certain Semiconductor Integrated Circuit Devices and Products Containing Same; Institution of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-01

... INTERNATIONAL TRADE COMMISSION [Inv. No. 337-TA-840] Certain Semiconductor Integrated Circuit... States after importation of certain semiconductor integrated circuit devices and products containing same... No. 6,847,904 (``the '904 patent''). The complaint further alleges that an industry in the United...

77 FR 19032 - Certain Semiconductor Integrated Circuit Devices and Products Containing Same Notice of Receipt...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-29

... INTERNATIONAL TRADE COMMISSION [DN 2888] Certain Semiconductor Integrated Circuit Devices and... Integrated Circuit Devices and Products Containing Same, DN 2888; the Commission is soliciting comments on... Commission's electronic docket (EDIS) at http://edis.usitc.gov , and will be available for inspection during...

77 FR 33486 - Certain Integrated Circuit Packages Provided With Multiple Heat-Conducting Paths and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-06

... INTERNATIONAL TRADE COMMISSION [Docket No. 2899] Certain Integrated Circuit Packages Provided With... complaint entitled Certain Integrated Circuit Packages Provided With Multiple Heat-Conducting Paths and..., telephone (202) 205-2000. The public version of the complaint can be accessed on the Commission's electronic...

A 1 GHz integrated circuit with carbon nanotube interconnects and silicon transistors.

PubMed

Close, Gael F; Yasuda, Shinichi; Paul, Bipul; Fujita, Shinobu; Wong, H-S Philip

2008-02-01

Due to their excellent electrical properties, metallic carbon nanotubes are promising materials for interconnect wires in future integrated circuits. Simulations have shown that the use of metallic carbon nanotube interconnects could yield more energy efficient and faster integrated circuits. The next step is to build an experimental prototype integrated circuit using carbon nanotube interconnects operating at high speed. Here, we report the fabrication of the first stand-alone integrated circuit combining silicon transistors and individual carbon nanotube interconnect wires on the same chip operating above 1 GHz. In addition to setting a milestone by operating above 1 GHz, this prototype is also a tool to investigate carbon nanotubes on a silicon-based platform at high frequencies, paving the way for future multi-GHz nanoelectronics.

The missing piece in the 'use it or lose it' puzzle: is inhibition regulated by activity or does it act on its own accord?

PubMed

Sun, Qian-Quan

2007-01-01

We have gained enormous insight into the mechanisms underlying both activity-dependent and (to a lesser degree) -independent plasticity of excitatory synapses. Recently, cortical inhibition has been shown to play a vital role in the formation of critical periods for sensory plasticity. As such, sculpting of neuronal circuits by inhibition may be a common mechanism by which activity organizes or reorganizes brain circuits. Disturbances in the balance of excitation and inhibition in the neocortex provoke abnormal activities, such as epileptic seizures and abnormal cortical development. However, both the process of experience-dependent postnatal maturation of neocortical inhibitory networks and its underlying mechanisms remain elusive. Mechanisms that match excitation and inhibition are central to achieving balanced function at the level of individual circuits. The goal of this review is to reinforce our understanding of the mechanisms by which developing inhibitory networks are able to adapt to sensory inputs, and to maintain their balance with developing excitatory networks. Discussion is centered on the following questions related to experience-dependent plasticity of neocortical inhibitory networks: 1) What are the roles of GABAergic inhibition in the postnatal maturation of neocortical circuits? 2) Does the maturation of neocortical inhibitory circuits proceed in an activity-dependent manner or do they develop independently of sensory inputs? 3) Does activity regulate inhibitory networks in the same way it regulates excitatory networks? 4) What are the molecular and cellular mechanisms that underlie the activity-dependent maturation of inhibitory networks? 5) What are the functional advantages of experience-dependent plasticity of inhibitory networks to network processing in sensory cortices?

Circuit-Detour Design and Implementation - Enhancing the Southern California's Seismic Network Reliability through Redundant Network Paths

NASA Astrophysics Data System (ADS)

Watkins, M.; Busby, R.; Rico, H.; Johnson, M.; Hauksson, E.

2003-12-01

We provide enhanced network robustness by apportioning redundant data communications paths for seismic stations in the field. By providing for more than one telemetry route, either physical or logical, network operators can improve availability of seismic data while experiencing occasional network outages, and also during the loss of key gateway interfaces such as a router or central processor. This is especially important for seismic stations in sparsely populated regions where a loss of a single site may result in a significant gap in the network's monitoring capability. A number of challenges arise in the application of a circuit-detour mechanism. One requirement is that it fits well within the existing framework of our real-time system processing. It is also necessary to craft a system that is not needlessly complex to maintain or implement, particularly during a crisis. The method that we use for circuit-detours does not require the reconfiguration of dataloggers or communications equipment in the field. Remote network configurations remain static, changes are only required at the central site. We have implemented standardized procedures to detour circuits on similar transport mediums, such as virtual circuits on the same leased line; as well as physically different communications pathways, such as a microwave link backed up by a leased line. The lessons learned from these improvements in reliability, and optimization efforts could be applied to other real-time seismic networks. A fundamental tenant of most seismic networks is that they are reliable and have a high percentage of real-time data availability. A reasonable way to achieve these expectations is to provide alternate means of delivering data to the central processing sites, with a simple method for utilizing these alternate paths.

The Drosophila TRPA1 Channel and Neuronal Circuits Controlling Rhythmic Behaviours and Sleep in Response to Environmental Temperature

PubMed Central

2017-01-01

trpA1 encodes a thermosensitive transient receptor potential channel (TRP channel) that functions in selection of preferred temperatures and noxious heat avoidance. In this review, we discuss the evidence for a role of TRPA1 in the control of rhythmic behaviours in Drosophila melanogaster. Activity levels during the afternoon and rhythmic temperature preference are both regulated by TRPA1. In contrast, TRPA1 is dispensable for temperature synchronisation of circadian clocks. We discuss the neuronal basis of TRPA1-mediated temperature effects on rhythmic behaviours, and conclude that they are mediated by partly overlapping but distinct neuronal circuits. We have previously shown that TRPA1 is required to maintain siesta sleep under warm temperature cycles. Here, we present new data investigating the neuronal circuit responsible for this regulation. First, we discuss the difficulties that remain in identifying the responsible neurons. Second, we discuss the role of clock neurons (s-LNv/DN1 network) in temperature-driven regulation of siesta sleep, and highlight the role of TRPA1 therein. Finally, we discuss the sexual dimorphic nature of siesta sleep and propose that the s-LNv/DN1 clock network could play a role in the integration of environmental information, mating status and other internal drives, to appropriately drive adaptive sleep/wake behaviour. PMID:28972543

An absorptive single-pole four-throw switch using multiple-contact MEMS switches and its application to a monolithic millimeter-wave beam-forming network

NASA Astrophysics Data System (ADS)

Lee, Sanghyo; Kim, Jong-Man; Kim, Yong-Kweon; Kwon, Youngwoo

2009-01-01

In this paper, a new absorptive single-pole four-throw (SP4T) switch based on multiple-contact switching is proposed and integrated with a Butler matrix to demonstrate a monolithic beam-forming network at millimeter waves (mm waves). In order to simplify the switching driving circuit and reduce the number of unit switches in an absorptive SP4T switch, the individual switches were replaced with long-span multiple-contact switches using stress-free single-crystalline-silicon MEMS technology. This approach improves the mechanical stability as well as the manufacturing yield, thereby allowing successful integration into a monolithic beam former. The fabricated absorptive SP4T MEMS switch shows insertion loss less than 1.3 dB, return losses better than 11 dB at 30 GHz and wideband isolation performance higher than 39 dB from 20 to 40 GHz. The absorptive SP4T MEMS switch is integrated with a 4 × 4 Butler matrix on a single chip to implement a monolithic beam-forming network, directing beam into four distinct angles. Array factors from the measured data show that the proposed absorptive SPnT MEMS switch can be effectively used for high-performance mm-wave beam-switching systems. This work corresponds to the first demonstration of a monolithic beam-forming network using switched beams.

Neural network integration during the perception of in-group and out-group members.

PubMed

Greven, Inez M; Ramsey, Richard

2017-11-01

Group biases guide social interactions by promoting in-group favouritism, but the neural mechanisms underpinning group biases remain unclear. While neuroscience research has shown that distributed brain circuits are associated with seeing in-group and out-group members as "us" and "them", it is less clear how these networks exchange signals. This fMRI study uses functional connectivity analyses to investigate the contribution of functional integration to group bias modulation of person perception. Participants were assigned to an arbitrary group and during scanning they observed bodies of in-group or out-group members that cued the recall of positive or negative social knowledge. The results showed that functional coupling between perceptual and cognitive neural networks is tuned to particular combinations of group membership and social knowledge valence. Specifically, coupling between body perception and theory-of-mind networks is biased towards seeing a person that had previously been paired with information consistent with group bias (positive for in-group and negative for out-group). This demonstrates how brain regions associated with visual analysis of others and belief reasoning exchange and integrate signals when evaluating in-group and out-group members. The results update models of person perception by showing how and when interplay occurs between perceptual and extended systems when developing a representation of another person. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Expert System Software

NASA Technical Reports Server (NTRS)

1989-01-01

C Language Integrated Production System (CLIPS) is a software shell for developing expert systems is designed to allow research and development of artificial intelligence on conventional computers. Originally developed by Johnson Space Center, it enables highly efficient pattern matching. A collection of conditions and actions to be taken if the conditions are met is built into a rule network. Additional pertinent facts are matched to the rule network. Using the program, E.I. DuPont de Nemours & Co. is monitoring chemical production machines; California Polytechnic State University is investigating artificial intelligence in computer aided design; Mentor Graphics has built a new Circuit Synthesis system, and Brooke and Brooke, a law firm, can determine which facts from a file are most important.

Method for producing a hybridization of detector array and integrated circuit for readout

NASA Technical Reports Server (NTRS)

Fossum, Eric R. (Inventor); Grunthaner, Frank J. (Inventor)

1993-01-01

A process is explained for fabricating a detector array in a layer of semiconductor material on one substrate and an integrated readout circuit in a layer of semiconductor material on a separate substrate in order to select semiconductor material for optimum performance of each structure, such as GaAs for the detector array and Si for the integrated readout circuit. The detector array layer is lifted off its substrate, laminated on the metallized surface on the integrated surface, etched with reticulating channels to the surface of the integrated circuit, and provided with interconnections between the detector array pixels and the integrated readout circuit through the channels. The adhesive material for the lamination is selected to be chemically stable to provide electrical and thermal insulation and to provide stress release between the two structures fabricated in semiconductor materials that may have different coefficients of thermal expansion.

Network for minimizing current imbalances in a faradaic battery

DOEpatents

Wozniak, Walter; Haskins, Harold J.

1994-01-01

A circuit for connecting a faradaic battery with circuitry for monitoring the condition of the battery includes a plurality of voltage divider networks providing battery voltage monitoring nodes and includes compensating resistors connected with the networks to maintain uniform discharge currents through the cells of the battery. The circuit also provides a reduced common mode voltage requirement for the monitoring circuitry by referencing the divider networks to one-half the battery voltage.

Identifying the integrated neural networks involved in capsaicin-induced pain using fMRI in awake TRPV1 knockout and wild-type rats

PubMed Central

Yee, Jason R.; Kenkel, William; Caccaviello, John C.; Gamber, Kevin; Simmons, Phil; Nedelman, Mark; Kulkarni, Praveen; Ferris, Craig F.

2015-01-01

In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1). Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type vs. knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain. PMID:25745388

Design and implementation of therapeutic ultrasound generating circuit for dental tissue formation and tooth-root healing.

PubMed

Woon Tiong Ang; Scurtescu, C; Wing Hoy; El-Bialy, T; Ying Yin Tsui; Jie Chen

2010-02-01

Biological tissue healing has recently attracted a great deal of research interest in various medical fields. Trauma to teeth, deep and root caries, and orthodontic treatment can all lead to various degrees of root resorption. In our previous study, we showed that low-intensity pulsed ultrasound (LIPUS) enhances the growth of lower incisor apices and accelerates their rate of eruption in rabbits by inducing dental tissue growth. We also performed clinical studies and demonstrated that LIPUS facilitates the healing of orthodontically induced teeth-root resorption in humans. However, the available LIPUS devices are too large to be used comfortably inside the mouth. In this paper, the design and implementation of a low-power LIPUS generator is presented. The generator is the core of the final intraoral device for preventing tooth root loss and enhancing tooth root tissue healing. The generator consists of a power-supply subsystem, an ultrasonic transducer, an impedance-matching circuit, and an integrated circuit composed of a digital controller circuitry and the associated driver circuit. Most of our efforts focus on the design of the impedance-matching circuit and the integrated system-on-chip circuit. The chip was designed and fabricated using 0.8- ¿m high-voltage technology from Dalsa Semiconductor, Inc. The power supply subsystem and its impedance-matching network are implemented using discrete components. The LIPUS generator was tested and verified to function as designed and is capable of producing ultrasound power up to 100 mW in the vicinity of the transducer's resonance frequency at 1.5 MHz. The power efficiency of the circuitry, excluding the power supply subsystem, is estimated at 70%. The final products will be tailored to the exact size of teeth or biological tissue, which is needed to be used for stimulating dental tissue (dentine and cementum) healing.

Activation of YUCCA5 by the Transcription Factor TCP4 Integrates Developmental and Environmental Signals to Promote Hypocotyl Elongation in Arabidopsis.

PubMed

Challa, Krishna Reddy; Aggarwal, Pooja; Nath, Utpal

2016-09-05

Cell expansion is an essential process in plant morphogenesis and is regulated by the coordinated action of environmental stimuli and endogenous factors, such as the phytohormones auxin and brassinosteroid. Although the biosynthetic pathways that generate these hormones and their downstream signaling mechanisms have been extensively studied, the upstream transcriptional network that modulates their levels and connects their action to cell morphogenesis is less clear. Here we show that the miR319-regulated TCP (TEOSINTE BRANCHED 1, CYCLODEA, PROLIFERATING CELL FACTORS) transcription factors, notably TCP4, directly activate YUCCA5 transcription and integrate the auxin response to a brassinosteroid-dependent molecular circuit that promotes cell elongation in Arabidopsis hypocotyls. Further, TCP4 modulates the common transcriptional network downstream to auxin-BR signaling, which is also triggered by environmental cues, such as light, to promote cell expansion. Our study links TCP function with the hormone response during cell morphogenesis and shows that developmental and environmental signals converge on a common transcriptional network to promote cell elongation. {copyright, serif} 2016 American Society of Plant Biologists. All rights reserved.

Processing Pathways in Mental Arithmetic—Evidence from Probabilistic Fiber Tracking

PubMed Central

Glauche, Volkmar; Weiller, Cornelius; Willmes, Klaus

2013-01-01

Numerical cognition is a case of multi-modular and distributed cerebral processing. So far neither the anatomo-functional connections between the cortex areas involved nor their integration into established frameworks such as the differentiation between dorsal and ventral processing streams have been specified. The current study addressed this issue combining a re-analysis of previously published fMRI data with probabilistic fiber tracking data from an independent sample. We aimed at differentiating neural correlates and connectivity for relatively easy and more difficult addition problems in healthy adults and their association with either rather verbally mediated fact retrieval or magnitude manipulations, respectively. The present data suggest that magnitude- and fact retrieval-related processing seem to be subserved by two largely separate networks, both of them comprising dorsal and ventral connections. Importantly, these networks not only differ in localization of activation but also in the connections between the cortical areas involved. However, it has to be noted that even though seemingly distinct anatomically, these networks operate as a functionally integrated circuit for mental calculation as revealed by a parametric analysis of brain activation. PMID:23383194

An Energy-Efficient ASIC for Wireless Body Sensor Networks in Medical Applications.

PubMed

Xiaoyu Zhang; Hanjun Jiang; Lingwei Zhang; Chun Zhang; Zhihua Wang; Xinkai Chen

2010-02-01

An energy-efficient application-specific integrated circuit (ASIC) featured with a work-on-demand protocol is designed for wireless body sensor networks (WBSNs) in medical applications. Dedicated for ultra-low-power wireless sensor nodes, the ASIC consists of a low-power microcontroller unit (MCU), a power-management unit (PMU), reconfigurable sensor interfaces, communication ports controlling a wireless transceiver, and an integrated passive radio-frequency (RF) receiver with energy harvesting ability. The MCU, together with the PMU, provides quite flexible communication and power-control modes for energy-efficient operations. The always-on passive RF receiver with an RF energy harvesting block offers the sensor nodes the capability of work-on-demand with zero standby power. Fabricated in standard 0.18-¿m complementary metal-oxide semiconductor technology, the ASIC occupies a die area of 2 mm × 2.5 mm. A wireless body sensor network sensor-node prototype using this ASIC only consumes < 10-nA current under the passive standby mode, and < 10 ¿A under the active standby mode, when supplied by a 3-V battery.

Resting state electrical brain activity and connectivity in fibromyalgia

PubMed Central

Vanneste, Sven; Ost, Jan; Van Havenbergh, Tony; De Ridder, Dirk

2017-01-01

The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients. PMID:28650974

Energy-efficient neuron, synapse and STDP integrated circuits.

PubMed

Cruz-Albrecht, Jose M; Yung, Michael W; Srinivasa, Narayan

2012-06-01

Ultra-low energy biologically-inspired neuron and synapse integrated circuits are presented. The synapse includes a spike timing dependent plasticity (STDP) learning rule circuit. These circuits have been designed, fabricated and tested using a 90 nm CMOS process. Experimental measurements demonstrate proper operation. The neuron and the synapse with STDP circuits have an energy consumption of around 0.4 pJ per spike and synaptic operation respectively.

Miniaturized ultrasound imaging probes enabled by CMUT arrays with integrated frontend electronic circuits.

PubMed

Khuri-Yakub, B T; Oralkan, Omer; Nikoozadeh, Amin; Wygant, Ira O; Zhuang, Steve; Gencel, Mustafa; Choe, Jung Woo; Stephens, Douglas N; de la Rama, Alan; Chen, Peter; Lin, Feng; Dentinger, Aaron; Wildes, Douglas; Thomenius, Kai; Shivkumar, Kalyanam; Mahajan, Aman; Seo, Chi Hyung; O'Donnell, Matthew; Truong, Uyen; Sahn, David J

2010-01-01

Capacitive micromachined ultrasonic transducer (CMUT) arrays are conveniently integrated with frontend integrated circuits either monolithically or in a hybrid multichip form. This integration helps with reducing the number of active data processing channels for 2D arrays. This approach also preserves the signal integrity for arrays with small elements. Therefore CMUT arrays integrated with electronic circuits are most suitable to implement miniaturized probes required for many intravascular, intracardiac, and endoscopic applications. This paper presents examples of miniaturized CMUT probes utilizing 1D, 2D, and ring arrays with integrated electronics.

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

PubMed

Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

2017-03-01

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity. Copyright © 2017. Published by Elsevier Inc.

Device for limiting single phase ground fault of mining machines

NASA Astrophysics Data System (ADS)

Fediuk, R. S.; Stoyushko, N. Yu; Yevdokimova, Yu G.; Smoliakov, A. K.; Batarshin, V. O.; Timokhin, R. A.

2017-10-01

The paper shows the reasons and consequences of the single-phase ground fault. With all the variety of devices for limiting the current single-phase ground fault, it was found that the most effective are Peterson coils having different switching circuits. Measuring of the capacity of the network is of great importance in this case, a number of options capacitance measurement are presented. A closer look is taken at the device for limiting the current of single-phase short circuit, developed in the Far Eastern Federal University under the direction of Dr. G.E. Kuvshinov. The calculation of single-phase short-circuit currents in the electrical network, without compensation and with compensation of capacitive current is carried out. Simulation of a single-phase circuit in a network with the proposed device is conducted.

75 FR 24742 - In the Matter of Certain Large Scale Integrated Circuit Semiconductor Chips and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-05

... Integrated Circuit Semiconductor Chips and Products Containing Same; Notice of Investigation AGENCY: U.S... of certain large scale integrated circuit semiconductor chips and products containing same by reason... alleges that an industry in the United States exists as required by subsection (a)(2) of section 337. The...

75 FR 5804 - In the Matter of: Certain Semiconductor Integrated Circuits and Products Containing Same; Notice...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-04

... Semiconductor Integrated Circuits and Products Containing Same; Notice of Commission Determination To Review in... importation of certain semiconductor integrated circuits and products containing same by reason of... that there exists a domestic industry with respect to each of the asserted patents. The complaint named...

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

Albert, Réka; Collins, James J.; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Carbon nanotube-based three-dimensional monolithic optoelectronic integrated system

NASA Astrophysics Data System (ADS)

Liu, Yang; Wang, Sheng; Liu, Huaping; Peng, Lian-Mao

2017-06-01

Single material-based monolithic optoelectronic integration with complementary metal oxide semiconductor-compatible signal processing circuits is one of the most pursued approaches in the post-Moore era to realize rapid data communication and functional diversification in a limited three-dimensional space. Here, we report an electrically driven carbon nanotube-based on-chip three-dimensional optoelectronic integrated circuit. We demonstrate that photovoltaic receivers, electrically driven transmitters and on-chip electronic circuits can all be fabricated using carbon nanotubes via a complementary metal oxide semiconductor-compatible low-temperature process, providing a seamless integration platform for realizing monolithic three-dimensional optoelectronic integrated circuits with diversified functionality such as the heterogeneous AND gates. These circuits can be vertically scaled down to sub-30 nm and operates in photovoltaic mode at room temperature. Parallel optical communication between functional layers, for example, bottom-layer digital circuits and top-layer memory, has been demonstrated by mapping data using a 2 × 2 transmitter/receiver array, which could be extended as the next generation energy-efficient signal processing paradigm.

Computer-aided engineering of semiconductor integrated circuits

NASA Astrophysics Data System (ADS)

Meindl, J. D.; Dutton, R. W.; Gibbons, J. F.; Helms, C. R.; Plummer, J. D.; Tiller, W. A.; Ho, C. P.; Saraswat, K. C.; Deal, B. E.; Kamins, T. I.

1980-07-01

Economical procurement of small quantities of high performance custom integrated circuits for military systems is impeded by inadequate process, device and circuit models that handicap low cost computer aided design. The principal objective of this program is to formulate physical models of fabrication processes, devices and circuits to allow total computer-aided design of custom large-scale integrated circuits. The basic areas under investigation are (1) thermal oxidation, (2) ion implantation and diffusion, (3) chemical vapor deposition of silicon and refractory metal silicides, (4) device simulation and analytic measurements. This report discusses the fourth year of the program.

Multichannel, Active Low-Pass Filters

NASA Technical Reports Server (NTRS)

Lev, James J.

1989-01-01

Multichannel integrated circuits cascaded to obtain matched characteristics. Gain and phase characteristics of channels of multichannel, multistage, active, low-pass filter matched by making filter of cascaded multichannel integrated-circuit operational amplifiers. Concept takes advantage of inherent equality of electrical characteristics of nominally-identical circuit elements made on same integrated-circuit chip. Characteristics of channels vary identically with changes in temperature. If additional matched channels needed, chips containing more than two operational amplifiers apiece (e.g., commercial quad operational amplifliers) used. Concept applicable to variety of equipment requiring matched gain and phase in multiple channels - radar, test instruments, communication circuits, and equipment for electronic countermeasures.

IP Network Design and Implementation for the Caltech-USGS Element of TriNet

NASA Astrophysics Data System (ADS)

Johnson, M. L.; Busby, R.; Watkins, M.; Schwarz, S.; Hauksson, E.

2001-12-01

The new seismic network IP numbering scheme for the Caltech-USGS element of TriNet is designed to provide emergency response plans for computer outages and/or telemetry circuit failures so that data acquisition may continue with minimal interruption. IP numbers from the seismic stations through the Caltech acquisition machines are numbered using private, non-routable IP addresses, which allows the network administrator to create redundancy in the network design, more freedom in choosing IP numbers, and uniformity in the LAN and WAN network addressing. The network scheme used by the Caltech-USGS element of TriNet is designed to create redundancy and load sharing over three or more T1 circuits. A T1 circuit can support 80 dataloggers sending data at a design rate of 19.2 kbps or 120 dataloggers transmitting at a nominal rate of 12.8 kbps. During a circuit detour, the 80 dataloggers on the failed T1 are equally divided between the remaining two circuits. This increases the loads on the remaining two circuits to 120 dataloggers, which is the maximum load each T1 can handle at the nominal rate. Each T1 circuit has a router interface onto a LAN at Caltech with an independent subnet address. Some devices, such as Solaris computers, allow a single interface to be numbered with several IP addresses, a so called "multinetted" interface. This allows the central acquisition computers to appear with distinct addresses that are routable via different T1 circuits, but simplifies the physical cables between devices. We identify these T1 circuits as T1-1, T1-2, and T1-3. At the remote end, each Frame Relay Access Device (FRAD) and connected datalogger(s) is a subnetted LAN. The numbering is arranged so the second octet in the LAN IP address of the FRAD and datalogger identify the datalogger's primary and alternate T1 circuits. For example; a LAN with an IP address of 10.12.0.0/24 has T1-1 as its primary T1, and T1-2 as its alternate circuit. Stations with this number scheme are sometimes referred to as group "12". LANs with IP addresses of 10.23.0.0/24 have T1-2 as the primary circuit, and T1-3 as the alternate circuit. Static routes on the acquisition system are used to direct traffic through the primary T1. The network can operate in one of three modes. The most common and desirable mode is "normal", where all three T1's are operational and Caltech has both a primary and secondary central acquisition system running. The second mode is a "failover", where the primary acquisition system is down (due to maintenance or failure) and the secondary acquisition system assumes the primary role. This includes sending acknowledgments to dataloggers and multicasts to the rest of the network. The third mode is a circuit detour. The port numbers on the central acquisition system for the dataloggers on the failed T1 are changed to match the auxiliary ports on the dataloggers. This allows for the auxiliary ports on the dataloggers to receive acknowledgements from the acquiring system through the detoured circuit. The static routes on the system are changed to go through the detoured circuit as specified by the group's IP numbers. At this point the two working T1's will be running at full capacity but the data acquisition will continue with minimal interruption while the third T1 is being restored. The primary acquisition computer continues to listen for data on the failed T1 should things improve spontaneously.

Changes in functional organization and white matter integrity in the connectome in Parkinson's disease.

PubMed

Tinaz, Sule; Lauro, Peter M; Ghosh, Pritha; Lungu, Codrin; Horovitz, Silvina G

2017-01-01

Parkinson's disease (PD) leads to dysfunction in multiple cortico-striatal circuits. The neurodegeneration has also been associated with impaired white matter integrity. This structural and functional "disconnection" in PD needs further characterization. We investigated the structural and functional organization of the PD whole brain connectome consisting of 200 nodes using diffusion tensor imaging and resting-state functional MRI, respectively. Data from 20 non-demented PD patients on dopaminergic medication and 20 matched controls were analyzed using graph theory-based methods. We focused on node strength, clustering coefficient, and local efficiency as measures of local network properties; and network modularity as a measure of information flow. PD patients showed reduced white matter connectivity in frontoparietal-striatal nodes compared to controls, but no change in modular organization of the white matter tracts. PD group also showed reduction in functional local network metrics in many nodes distributed across the connectome. There was also decreased functional modularity in the core cognitive networks including the default mode and dorsal attention networks, and sensorimotor network, as well as a lack of modular distinction in the orbitofrontal and basal ganglia nodes in the PD group compared to controls. Our results suggest that despite subtle white matter connectivity changes, the overall structural organization of the PD connectome remains robust at relatively early disease stages. However, there is a breakdown in the functional modular organization of the PD connectome.

Analog Delta-Back-Propagation Neural-Network Circuitry

NASA Technical Reports Server (NTRS)

Eberhart, Silvio

1990-01-01

Changes in synapse weights due to circuit drifts suppressed. Proposed fully parallel analog version of electronic neural-network processor based on delta-back-propagation algorithm. Processor able to "learn" when provided with suitable combinations of inputs and enforced outputs. Includes programmable resistive memory elements (corresponding to synapses), conductances (synapse weights) adjusted during learning. Buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in layers of electronic neurons in accordance with delta-back-propagation algorithm.

Reusable vibration resistant integrated circuit mounting socket

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

Evans, C.N.

1993-12-31

This invention discloses a novel form of socket for integrated circuits to be mounted on printed circuit boards. The socket uses a novel contact which is fabricated out of a bimetallic strip with a shape which makes the end of the strip move laterally as temperature changes. The end of the strip forms a barb which digs into an integrated circuit lead at normal temperatures and hold it firmly in the contact, preventing loosening and open circuits from vibration. By cooling the contact containing the bimetallic strip the barb end can be made to release so that the integrated circuitmore » lead can be removed from the socket without damage either to the lead or to the socket components.« less

Reusable vibration resistant integrated circuit mounting socket

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

Evans, C.N.

1995-08-29

This invention discloses a novel form of socket for integrated circuits to be mounted on printed circuit boards. The socket uses a novel contact which is fabricated out of a bimetallic strip with a shape which makes the end of the strip move laterally as temperature changes. The end of the strip forms a barb which digs into an integrated circuit lead at normal temperatures and holds it firmly in the contact, preventing loosening and open circuits from vibration. By cooling the contact containing the bimetallic strip the barb end can be made to release so that the integrated circuitmore » lead can be removed from the socket without damage either to the lead or to the socket components. 11 figs.« less

Vertically integrated, three-dimensional nanowire complementary metal-oxide-semiconductor circuits.

PubMed

Nam, SungWoo; Jiang, Xiaocheng; Xiong, Qihua; Ham, Donhee; Lieber, Charles M

2009-12-15

Three-dimensional (3D), multi-transistor-layer, integrated circuits represent an important technological pursuit promising advantages in integration density, operation speed, and power consumption compared with 2D circuits. We report fully functional, 3D integrated complementary metal-oxide-semiconductor (CMOS) circuits based on separate interconnected layers of high-mobility n-type indium arsenide (n-InAs) and p-type germanium/silicon core/shell (p-Ge/Si) nanowire (NW) field-effect transistors (FETs). The DC voltage output (V(out)) versus input (V(in)) response of vertically interconnected CMOS inverters showed sharp switching at close to the ideal value of one-half the supply voltage and, moreover, exhibited substantial DC gain of approximately 45. The gain and the rail-to-rail output switching are consistent with the large noise margin and minimal static power consumption of CMOS. Vertically interconnected, three-stage CMOS ring oscillators were also fabricated by using layer-1 InAs NW n-FETs and layer-2 Ge/Si NW p-FETs. Significantly, measurements of these circuits demonstrated stable, self-sustained oscillations with a maximum frequency of 108 MHz, which represents the highest-frequency integrated circuit based on chemically synthesized nanoscale materials. These results highlight the flexibility of bottom-up assembly of distinct nanoscale materials and suggest substantial promise for 3D integrated circuits.

Optical Circuit Switched Protocol

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

2000-01-01

The present invention is a system and method embodied in an optical circuit switched protocol for the transmission of data through a network. The optical circuit switched protocol is an all-optical circuit switched network and includes novel optical switching nodes for transmitting optical data packets within a network. Each optical switching node comprises a detector for receiving the header, header detection logic for translating the header into routing information and eliminating the header, and a controller for receiving the routing information and configuring an all optical path within the node. The all optical path located within the node is solely an optical path without having electronic storage of the data and without having optical delay of the data. Since electronic storage of the header is not necessary and the initial header is eliminated by the first detector of the first switching node. multiple identical headers are sent throughout the network so that subsequent switching nodes can receive and read the header for setting up an optical data path.

Supervised Learning Using Spike-Timing-Dependent Plasticity of Memristive Synapses.

PubMed

Nishitani, Yu; Kaneko, Yukihiro; Ueda, Michihito

2015-12-01

We propose a supervised learning model that enables error backpropagation for spiking neural network hardware. The method is modeled by modifying an existing model to suit the hardware implementation. An example of a network circuit for the model is also presented. In this circuit, a three-terminal ferroelectric memristor (3T-FeMEM), which is a field-effect transistor with a gate insulator composed of ferroelectric materials, is used as an electric synapse device to store the analog synaptic weight. Our model can be implemented by reflecting the network error to the write voltage of the 3T-FeMEMs and introducing a spike-timing-dependent learning function to the device. An XOR problem was successfully demonstrated as a benchmark learning by numerical simulations using the circuit properties to estimate the learning performance. In principle, the learning time per step of this supervised learning model and the circuit is independent of the number of neurons in each layer, promising a high-speed and low-power calculation in large-scale neural networks.

Low power digitally controlled oscillator designs with a novel 3-transistor XNOR gate

NASA Astrophysics Data System (ADS)

Kumar, Manoj; Arya, Sandeep K.; Pandey, Sujata

2012-03-01

Digital controlled oscillators (DCOs) are the core of all digital phase locked loop (ADPLL) circuits. Here, DCO structures with reduced hardware and power consumption having full digital control have been proposed. Three different DCO architectures have been proposed based on ring based topology. Three, four and five bit controlled DCO with NMOS, PMOS and NMOS & PMOS transistor switching networks are presented. A three-transistor XNOR gate has been used as the inverter which is used as the delay cell. Delay has been controlled digitally with a switch network of NMOS and PMOS transistors. The three bit DCO with one NMOS network shows frequency variations of 1.6141-1.8790 GHz with power consumption variations 251.9224-276.8591 μW. The four bit DCO with one NMOS network shows frequency variation of 1.6229-1.8868 GHz with varying power consumption of 251.9225-278.0740 μW. A six bit DCO with one NMOS switching network gave an output frequency of 1.7237-1.8962 GHz with power consumption of 251.928-278.998 μW. Output frequency and power consumption results for 4 & 6 bit DCO circuits with one PMOS and NMOS & PMOS switching network have also been presented. The phase noise parameter with an offset frequency of 1 MHz has also been reported for the proposed circuits. Comparisons with earlier reported circuits have been made and the present approach shows advantages over previous circuits.

Securing health sensing using integrated circuit metric.

PubMed

Tahir, Ruhma; Tahir, Hasan; McDonald-Maier, Klaus

2015-10-20

Convergence of technologies from several domains of computing and healthcare have aided in the creation of devices that can help health professionals in monitoring their patients remotely. An increase in networked healthcare devices has resulted in incidents related to data theft, medical identity theft and insurance fraud. In this paper, we discuss the design and implementation of a secure lightweight wearable health sensing system. The proposed system is based on an emerging security technology called Integrated Circuit Metric (ICMetric) that extracts the inherent features of a device to generate a unique device identification. In this paper, we provide details of how the physical characteristics of a health sensor can be used for the generation of hardware "fingerprints". The obtained fingerprints are used to deliver security services like authentication, confidentiality, secure admission and symmetric key generation. The generated symmetric key is used to securely communicate the health records and data of the patient. Based on experimental results and the security analysis of the proposed scheme, it is apparent that the proposed system enables high levels of security for health monitoring in resource optimized manner.

Securing Health Sensing Using Integrated Circuit Metric

PubMed Central

Tahir, Ruhma; Tahir, Hasan; McDonald-Maier, Klaus

2015-01-01

Convergence of technologies from several domains of computing and healthcare have aided in the creation of devices that can help health professionals in monitoring their patients remotely. An increase in networked healthcare devices has resulted in incidents related to data theft, medical identity theft and insurance fraud. In this paper, we discuss the design and implementation of a secure lightweight wearable health sensing system. The proposed system is based on an emerging security technology called Integrated Circuit Metric (ICMetric) that extracts the inherent features of a device to generate a unique device identification. In this paper, we provide details of how the physical characteristics of a health sensor can be used for the generation of hardware “fingerprints”. The obtained fingerprints are used to deliver security services like authentication, confidentiality, secure admission and symmetric key generation. The generated symmetric key is used to securely communicate the health records and data of the patient. Based on experimental results and the security analysis of the proposed scheme, it is apparent that the proposed system enables high levels of security for health monitoring in resource optimized manner. PMID:26492250

Matching network for RF plasma source

DOEpatents

Pickard, Daniel S.; Leung, Ka-Ngo

2007-11-20

A compact matching network couples an RF power supply to an RF antenna in a plasma generator. The simple and compact impedance matching network matches the plasma load to the impedance of a coaxial transmission line and the output impedance of an RF amplifier at radio frequencies. The matching network is formed of a resonantly tuned circuit formed of a variable capacitor and an inductor in a series resonance configuration, and a ferrite core transformer coupled to the resonantly tuned circuit. This matching network is compact enough to fit in existing compact focused ion beam systems.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

PubMed

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder

PubMed Central

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive. PMID:28018162

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

NASA Astrophysics Data System (ADS)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

NSI directed to continue SPAN's functions

NASA Technical Reports Server (NTRS)

Rounds, Fred

1991-01-01

During a series of network management retreats in June and July 1990, representatives from NASA Headquarters Codes O and S agreed on networking roles and responsibilities for their respective organizations. The representatives decided that NASA Science Internet (NSI) will assume management of both the Space Physics Analysis Network (SPAN) and the NASA Science Network (NSN). SPAN is now known as the NSI/DECnet, and NSN is now known as the NSI/IP. Some management functions will be distributed between Ames Research Center (ARC) and Goddard Space Flight Center (GSFC). NSI at ARC has the lead role for requirements generation and networking engineering. Advanced Applications and the Network Information Center is being developed at GSFC. GSFC will lead the NSI User Services, but NSI at Ames will continue to provide the User Services during the transition. The transition will be made as transparent as possible for the users. DECnet service will continue, but is now directly managed by NSI at Ames. NSI will continue to work closely with routing center managers at other NASA centers, and has formed a transition team to address the change in management. An NSI/DECnet working group had also been formed as a separate engineering group within NSI to plan the transition to Phase 5, DECnet's approach to Open System Integration (OSI). Transition is not expected for a year or more due to delays in produce releases. Plans to upgrade speeds in tail circuits and the backbone are underway. The proposed baseline service for new connections is up to 56 Kbps; 9.6 Kbps lines will gradually be upgraded as requirements dictate. NSI is in the process of consolidating protocol traffic, tail circuits, and the backbone. Currently NSI's backbone is fractional T1; NSI will go to full T1 service as soon as it is feasible.

Miniaturized Ultrasound Imaging Probes Enabled by CMUT Arrays with Integrated Frontend Electronic Circuits

PubMed Central

Khuri-Yakub, B. (Pierre) T.; Oralkan, Ömer; Nikoozadeh, Amin; Wygant, Ira O.; Zhuang, Steve; Gencel, Mustafa; Choe, Jung Woo; Stephens, Douglas N.; de la Rama, Alan; Chen, Peter; Lin, Feng; Dentinger, Aaron; Wildes, Douglas; Thomenius, Kai; Shivkumar, Kalyanam; Mahajan, Aman; Seo, Chi Hyung; O’Donnell, Matthew; Truong, Uyen; Sahn, David J.

2010-01-01

Capacitive micromachined ultrasonic transducer (CMUT) arrays are conveniently integrated with frontend integrated circuits either monolithically or in a hybrid multichip form. This integration helps with reducing the number of active data processing channels for 2D arrays. This approach also preserves the signal integrity for arrays with small elements. Therefore CMUT arrays integrated with electronic circuits are most suitable to implement miniaturized probes required for many intravascular, intracardiac, and endoscopic applications. This paper presents examples of miniaturized CMUT probes utilizing 1D, 2D, and ring arrays with integrated electronics. PMID:21097106

Simple photometer circuits using modular electronic components

NASA Technical Reports Server (NTRS)

Wampler, J. E.

1975-01-01

Operational and peak holding amplifiers are discussed as useful circuits for bioluminescence assays. Circuit diagrams are provided. While analog methods can give a good integration on short time scales, digital methods were found best for long term integration in bioluminescence assays. Power supplies, a general photometer circuit with ratio capability, and variations in the basic photometer design are also considered.

Highly sensitive vacuum ion pump current measurement system

DOEpatents

Hansknecht, John Christopher [Williamsburg, VA

2006-02-21

A vacuum system comprising: 1) an ion pump; 2) power supply; 3) a high voltage DC--DC converter drawing power from the power supply and powering the vacuum pump; 4) a feedback network comprising an ammeter circuit including an operational amplifier and a series of relay controlled scaling resistors of different resistance for detecting circuit feedback; 5) an optional power block section intermediate the power supply and the high voltage DC--DC converter; and 6) a microprocessor receiving feedback information from the feedback network, controlling which of the scaling resistors should be in the circuit and manipulating data from the feedback network to provide accurate vacuum measurement to an operator.

Integrated circuits and logic operations based on single-layer MoS2.

PubMed

Radisavljevic, Branimir; Whitwick, Michael Brian; Kis, Andras

2011-12-27

Logic circuits and the ability to amplify electrical signals form the functional backbone of electronics along with the possibility to integrate multiple elements on the same chip. The miniaturization of electronic circuits is expected to reach fundamental limits in the near future. Two-dimensional materials such as single-layer MoS(2) represent the ultimate limit of miniaturization in the vertical dimension, are interesting as building blocks of low-power nanoelectronic devices, and are suitable for integration due to their planar geometry. Because they are less than 1 nm thin, 2D materials in transistors could also lead to reduced short channel effects and result in fabrication of smaller and more power-efficient transistors. Here, we report on the first integrated circuit based on a two-dimensional semiconductor MoS(2). Our integrated circuits are capable of operating as inverters, converting logical "1" into logical "0", with room-temperature voltage gain higher than 1, making them suitable for incorporation into digital circuits. We also show that electrical circuits composed of single-layer MoS(2) transistors are capable of performing the NOR logic operation, the basis from which all logical operations and full digital functionality can be deduced.

LEC GaAs for integrated circuit applications

NASA Technical Reports Server (NTRS)

Kirkpatrick, C. G.; Chen, R. T.; Homes, D. E.; Asbeck, P. M.; Elliott, K. R.; Fairman, R. D.; Oliver, J. D.

1984-01-01

Recent developments in liquid encapsulated Czochralski techniques for the growth of semiinsulating GaAs for integrated circuit applications have resulted in significant improvements in the quality and quantity of GaAs material suitable for device processing. The emergence of high performance GaAs integrated circuit technologies has accelerated the demand for high quality, large diameter semiinsulating GaAs substrates. The new device technologies, including digital integrated circuits, monolithic microwave integrated circuits and charge coupled devices have largely adopted direct ion implantation for the formation of doped layers. Ion implantation lends itself to good uniformity and reproducibility, high yield and low cost; however, this technique also places stringent demands on the quality of the semiinsulating GaAs substrates. Although significant progress was made in developing a viable planar ion implantation technology, the variability and poor quality of GaAs substrates have hindered progress in process development.

Towards a whole-cell modeling approach for synthetic biology

NASA Astrophysics Data System (ADS)

Purcell, Oliver; Jain, Bonny; Karr, Jonathan R.; Covert, Markus W.; Lu, Timothy K.

2013-06-01

Despite rapid advances over the last decade, synthetic biology lacks the predictive tools needed to enable rational design. Unlike established engineering disciplines, the engineering of synthetic gene circuits still relies heavily on experimental trial-and-error, a time-consuming and inefficient process that slows down the biological design cycle. This reliance on experimental tuning is because current modeling approaches are unable to make reliable predictions about the in vivo behavior of synthetic circuits. A major reason for this lack of predictability is that current models view circuits in isolation, ignoring the vast number of complex cellular processes that impinge on the dynamics of the synthetic circuit and vice versa. To address this problem, we present a modeling approach for the design of synthetic circuits in the context of cellular networks. Using the recently published whole-cell model of Mycoplasma genitalium, we examined the effect of adding genes into the host genome. We also investigated how codon usage correlates with gene expression and find agreement with existing experimental results. Finally, we successfully implemented a synthetic Goodwin oscillator in the whole-cell model. We provide an updated software framework for the whole-cell model that lays the foundation for the integration of whole-cell models with synthetic gene circuit models. This software framework is made freely available to the community to enable future extensions. We envision that this approach will be critical to transforming the field of synthetic biology into a rational and predictive engineering discipline.

Role of perinatal long-chain omega-3 fatty acids in cortical circuit maturation: Mechanisms and implications for psychopathology

PubMed Central

McNamara, Robert K; Vannest, Jennifer J; Valentine, Christina J

2015-01-01

Accumulating translational evidence suggests that the long-chain omega-3 fatty acid docosahexaenoic acid (DHA) plays a role in the maturation and stability of cortical circuits that are impaired in different recurrent psychiatric disorders. Specifically, rodent and cell culture studies find that DHA preferentially accumulates in synaptic and growth cone membranes and promotes neurite outgrowth, dendritic spine stability, and synaptogenesis. Additional evidence suggests that DHA may play a role in microglia-mediated synaptic pruning, as well as myelin development and resilience. In non-human primates n-3 fatty acid insufficiency during perinatal development leads to widespread deficits in functional connectivity in adult frontal cortical networks compared to primates raised on DHA-fortified diet. Preterm delivery in non-human primates and humans is associated with early deficits in cortical DHA accrual. Human preterm birth is associated with long-standing deficits in myelin integrity and cortical circuit connectivity and increased risk for attention deficit/hyperactivity disorder (ADHD), mood, and psychotic disorders. In general, ADHD and mood and psychotic disorders initially emerge during rapid periods of cortical circuit maturation and are characterized by DHA deficits, myelin pathology, and impaired cortical circuit connectivity. Together these associations suggest that early and uncorrected deficits in fetal brain DHA accrual may represent a modifiable risk factor for cortical circuit maturation deficits in psychiatric disorders, and could therefore have significant implications for informing early intervention and prevention strategies. PMID:25815252

A Framework for Understanding the Emerging Role of Corticolimbic-Ventral Striatal Networks in OCD-Associated Repetitive Behaviors

PubMed Central

Wood, Jesse; Ahmari, Susanne E.

2015-01-01

Significant interest in the mechanistic underpinnings of obsessive-compulsive disorder (OCD) has fueled research on the neural origins of compulsive behaviors. Converging clinical and preclinical evidence suggests that abnormal repetitive behaviors are driven by dysfunction in cortico-striatal-thalamic-cortical (CSTC) circuits. These findings suggest that compulsive behaviors arise, in part, from aberrant communication between lateral orbitofrontal cortex (OFC) and dorsal striatum. An important body of work focused on the role of this network in OCD has been instrumental to progress in the field. Disease models focused primarily on these regions, however, fail to capture an important aspect of the disorder: affective dysregulation. High levels of anxiety are extremely prevalent in OCD, as is comorbidity with major depressive disorder. Furthermore, deficits in processing rewards and abnormalities in processing emotional stimuli are suggestive of aberrant encoding of affective information. Accordingly, OCD can be partially characterized as a disease in which behavioral selection is corrupted by exaggerated or dysregulated emotional states. This suggests that the networks producing OCD symptoms likely expand beyond traditional lateral OFC and dorsal striatum circuit models, and highlights the need to cast a wider net in our investigation of the circuits involved in generating and sustaining OCD symptoms. Here, we address the emerging role of medial OFC, amygdala, and ventral tegmental area projections to the ventral striatum (VS) in OCD pathophysiology. The VS receives strong innervation from these affect and reward processing regions, and is therefore poised to integrate information crucial to the generation of compulsive behaviors. Though it complements functions of dorsal striatum and lateral OFC, this corticolimbic-VS network is less commonly explored as a potential source of the pathology underlying OCD. In this review, we discuss this network’s potential role as a locus of OCD pathology and effective treatment. PMID:26733823

Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

NASA Astrophysics Data System (ADS)

Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

2017-08-01

Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.

Present Status of Power Circuit Breaker and its Future

NASA Astrophysics Data System (ADS)

Yoshioka, Yoshio

Gas circuit breaker and vacuum circuit breaker are the 2 main types of circuit breaker used in extra high voltage and medium voltage networks. After reviewing the history of these circuit breakers, their present status and technologies are described. As for future technology, computation of interrupting phenomena, SF6 gas less apparatus and expectation of the high voltage vacuum circuit breaker are discussed.

Testing and Qualifying Linear Integrated Circuits for Radiation Degradation in Space

NASA Technical Reports Server (NTRS)

Johnston, Allan H.; Rax, Bernard G.

2006-01-01

This paper discusses mechanisms and circuit-related factors that affect the degradation of linear integrated circuits from radiation in space. For some circuits there is sufficient degradation to affect performance at total dose levels below 4 krad(Si) because the circuit design techniques require higher gain for the pnp transistors that are the most sensitive to radiation. Qualification methods are recommended that include displacement damage as well as ionization damage.

Complex dynamics of memristive circuits: Analytical results and universal slow relaxation

NASA Astrophysics Data System (ADS)

Caravelli, F.; Traversa, F. L.; Di Ventra, M.

2017-02-01

Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph connectivity on the memory dynamics are still few, thus limiting our understanding of these important dynamical systems. In this paper, we derive an exact matrix equation of motion that takes into account all the network constraints of a purely memristive circuit, and we employ it to derive analytical results regarding its relaxation properties. We are able to describe the memory evolution in terms of orthogonal projection operators onto the subspace of fundamental loop space of the underlying circuit. This orthogonal projection explicitly reveals the coupling between the spatial and temporal sectors of the memristive circuits and compactly describes the circuit topology. For the case of disordered graphs, we are able to explain the emergence of a power-law relaxation as a superposition of exponential relaxation times with a broad range of scales using random matrices. This power law is also universal, namely independent of the topology of the underlying graph but dependent only on the density of loops. In the case of circuits subject to alternating voltage instead, we are able to obtain an approximate solution of the dynamics, which is tested against a specific network topology. These results suggest a much richer dynamics of memristive networks than previously considered.

Low-frequency sine wave hard-limiting technique

NASA Technical Reports Server (NTRS)

Anderson, T. O.

1977-01-01

Circuit includes serial-in/parallel-out shift register and weighting network that are used to eliminate effects of noise and other nonrepetitive circuit transients. Register and weighting network average decisions from section of signal where decisions are more dependable or where differences between two consecutive samples are larger.

Soliton quenching NLTL impulse circuit with a pulse forming network at the output

DOEpatents

McEwan, Thomas E.; Dallum, Gregory E.

1998-01-01

An impulse forming circuit is disclosed which produces a clean impulse from a nonlinear transmission line compressed step function without customary soliton ringing by means of a localized pulse shaping and differentiating network which shunts the nonlinear transmission line output to ground.

Millimeter-wave monolithic integrated circuit characterization by a picosecond optoelectronic technique

NASA Astrophysics Data System (ADS)

Hung, Hing-Loi A.; Smith, Thane; Huang, Ho C.; Polak-Dingels, Penny; Webb, Kevin J.

1989-08-01

The characterization of microwave and millimeter-wave monolithic integrated circits (MIMICs) using picosecond pulse-sampling techniques is developed with emphasis on improving broadband coverage and measurement accuracy. GaAs photoconductive swithces are used for signal generation and sampling operations. The measured time-domain response allows the spectral transfer function of the MIMIC to be obtained. This measurement technique is verified by characterization of the frequency response (magnitude and phase) of a reference 50-ohm microstrip line and a two-stage Ka-band MIMIC amplifier. The measured broadband results agree with those obtained from conventional frequency-domain measurements using a network analyzer. The application of this optical technique to on-wafer MIMIC characterization is described.

Numerical modelling of surface plasmonic polaritons

NASA Astrophysics Data System (ADS)

Mansoor, Riyadh; AL-Khursan, Amin Habbeb

2018-06-01

Extending optoelectronics into the nano-regime seems problematic due to the relatively long wavelengths of light. The conversion of light into plasmons is a possible way to overcome this problem. Plasmon's wavelengths are much shorter than that of light which enables the propagation of signals in small size components. In this paper, a 3D simulation of surface plasmon polariton (SPP) excitation is performed. The Finite integration technique was used to solve Maxwell's equations in the dielectric-metal interface. The results show how the surface plasmon polariton was generated at the grating assisted dielectric-metal interface. SPP is a good candidate for signal confinement in small size optoelectronics which allow high density optical integrated circuits in all optical networks.

On-Chip Optical Nonreciprocity Using an Active Microcavity

PubMed Central

Jiang, Xiaoshun; Yang, Chao; Wu, Hongya; Hua, Shiyue; Chang, Long; Ding, Yang; Hua, Qian; Xiao, Min

2016-01-01

Optically nonreciprocal devices provide critical functionalities such as light isolation and circulation in integrated photonic circuits for optical communications and information processing, but have been difficult to achieve. By exploring gain-saturation nonlinearity, we demonstrate on-chip optical nonreciprocity with excellent isolation performance within telecommunication wavelengths using only one toroid microcavity. Compatible with current complementary metal-oxide-semiconductor process, our compact and simple scheme works for a very wide range of input power levels from ~10 microwatts down to ~10 nanowatts, and exhibits remarkable properties of one-way light transport with sufficiently low insertion loss. These superior features make our device become a promising critical building block indispensable for future integrated nanophotonic networks. PMID:27958356

Performance of circuit switching in the Internet

NASA Astrophysics Data System (ADS)

Molinero-Fernández, Pablo; McKeown, Nick

2003-04-01

We study the performance of an Internet that uses circuit switching (CS) instead of, or in addition to, packet switching (PS). On the face of it, this would seem a pointless exercise; the Internet is packet switched, and it was deliberately built that way to enable the efficiencies afforded by statistical multiplexing and the robustness of fast rerouting around failures. But link utilization is low particularly at the core of the Internet, which makes statistical multiplexing less important than it once was. Moreover, circuit switches today are capable of rapid reconfiguration around failures. There is also renewed interest in CS because of the ease of building very-high-capacity optical circuit switches. Although several proposals have suggested ways in which CS may be introduced into the Internet, the research presented here is based on Transmission Control Protocol (TCP) switching, in which a new circuit is created for each application flow. Here we explore the performance of a network that uses TCP switching, with particular emphasis on the response time experienced by users. We use simple M/GI/1 and M/GI/N queues to model application flows in both packet-switched and circuit-switched networks, as well as ns-2 simulations. We conclude that because of high-bandwidth long-lived flows, it does not make sense to use CS in shared-access or local area networks. But our results suggest that in the core of the network, where high capacity is needed most, and where peak flow rate is limited by the access link, there is little or no difference in performance between CS and PS. Given that circuit switches can be built to be much faster than packet switches, this suggests that a circuit-switched core warrants further investigation.

Ka-band to L-band frequency down-conversion based on III-V-on-silicon photonic integrated circuits

NASA Astrophysics Data System (ADS)

Van Gasse, K.; Wang, Z.; Uvin, S.; De Deckere, B.; Mariën, J.; Thomassen, L.; Roelkens, G.

2017-12-01

In this work, we present the design, simulation and characterization of a frequency down-converter based on III-V-on-silicon photonic integrated circuit technology. We first demonstrate the concept using commercial discrete components, after which we demonstrate frequency conversion using an integrated mode-locked laser and integrated modulator. In our experiments, five channels in the Ka-band (27.5-30 GHz) with 500 MHz bandwidth are down-converted to the L-band (1.5 GHz). The breadboard demonstration shows a conversion efficiency of - 20 dB and a flat response over the 500 MHz bandwidth. The simulation of a fully integrated circuit indicates that a positive conversion gain can be obtained on a millimeter-sized photonic integrated circuit.

Systematic analysis of CMOS-micromachined inductors with application to mixer matching circuits

NASA Astrophysics Data System (ADS)

Wu, Jerry Chun-Li

The growing demand for consumer voice and data communication systems and military communication applications has created a need for low-power, low-cost, high-performance radio-frequency (RF) front-end. To achieve this goal, bringing passive components, especially inductors, to silicon is imperative. On-chip passive components such as inductors and capacitors generally enhance the reliability and efficiency of silicon-integrated RF cells. They can provide circuit solutions with superior performance and contribute to a higher level of integration. With passive components on chip, there is a great opportunity to have transformers, filters, and matching networks on chip. However, inductors on silicon have a low quality factor (Q) due to both substrate and metal loss. This dissertation demonstrates the systematic analysis of inductors fabricated using standard complementary metal-oxide-semiconductor (CMOS) and micro-electro-mechanical (MEMS) system technologies. We report system-on-chip inductor modeling, simulation, and measurements of effective inductance and quality factors. In this analysis methodology, a number of systematic simulations are performed on regular and micromachined inductors with different parameters such as spiral topology, number of turns, outer diameter, thickness, and percentage of substrate removed by using micromachining technologies. Three different novel support structures of the micromachined spiral inductor are proposed, analyzed, and implemented for larger size suspended inductors. The sensitivity of the structure support and different degree of substrate etching by post-processing is illustrated. The results provide guidelines for the selection of inductor parameters, post-processing methodologies, and its spiral supports to meet the RF design specifications and the stability requirements for mobile communication. The proposed CMOS-micromachined inductor is used in a low cost-effective double-balanced Gilbert mixer with on-chip matching network. The integrated mixer inductor was implemented and tested to prove the concept.

Continuous adjustment of threshold voltage in carbon nanotube field-effect transistors through gate engineering

NASA Astrophysics Data System (ADS)

Zhong, Donglai; Zhao, Chenyi; Liu, Lijun; Zhang, Zhiyong; Peng, Lian-Mao

2018-04-01

In this letter, we report a gate engineering method to adjust threshold voltage of carbon nanotube (CNT) based field-effect transistors (FETs) continuously in a wide range, which makes the application of CNT FETs especially in digital integrated circuits (ICs) easier. Top-gated FETs are fabricated using solution-processed CNT network films with stacking Pd and Sc films as gate electrodes. By decreasing the thickness of the lower layer metal (Pd) from 20 nm to zero, the effective work function of the gate decreases, thus tuning the threshold voltage (Vt) of CNT FETs from -1.0 V to 0.2 V. The continuous adjustment of threshold voltage through gate engineering lays a solid foundation for multi-threshold technology in CNT based ICs, which then can simultaneously provide high performance and low power circuit modules on one chip.

Sensor Authentication in Collaborating Sensor Networks

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

Bielefeldt, Jake Uriah

2014-11-01

In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator O i of Sensor Network S imore » to correctly determine the number of active sensors in Network Si. Such a problem is challenging in collaborating sensor networks where other sensor networks, despite showing an intent to collaborate, may not be completely trustworthy and could compromise the authentication process. We propose two authentication protocols to address this problem. Our protocols rely on Physically Unclonable Functions, which are a hardware based authentication primitive exploiting inherent randomness in circuit fabrication. Our protocols are light-weight, energy efficient, and highly secure against a number of attacks. To the best of our knowledge, ours is the first to addresses a practical security problem in collaborating sensor networks.« less

Microwave GaAs Integrated Circuits On Quartz Substrates

NASA Technical Reports Server (NTRS)

Siegel, Peter H.; Mehdi, Imran; Wilson, Barbara

1994-01-01

Integrated circuits for use in detecting electromagnetic radiation at millimeter and submillimeter wavelengths constructed by bonding GaAs-based integrated circuits onto quartz-substrate-based stripline circuits. Approach offers combined advantages of high-speed semiconductor active devices made only on epitaxially deposited GaAs substrates with low-dielectric-loss, mechanically rugged quartz substrates. Other potential applications include integration of antenna elements with active devices, using carrier substrates other than quartz to meet particular requirements using lifted-off GaAs layer in membrane configuration with quartz substrate supporting edges only, and using lift-off technique to fabricate ultrathin discrete devices diced separately and inserted into predefined larger circuits. In different device concept, quartz substrate utilized as transparent support for GaAs devices excited from back side by optical radiation.

Optical multicast system for data center networks.

PubMed

Samadi, Payman; Gupta, Varun; Xu, Junjie; Wang, Howard; Zussman, Gil; Bergman, Keren

2015-08-24

We present the design and experimental evaluation of an Optical Multicast System for Data Center Networks, a hardware-software system architecture that uniquely integrates passive optical splitters in a hybrid network architecture for faster and simpler delivery of multicast traffic flows. An application-driven control plane manages the integrated optical and electronic switched traffic routing in the data plane layer. The control plane includes a resource allocation algorithm to optimally assign optical splitters to the flows. The hardware architecture is built on a hybrid network with both Electronic Packet Switching (EPS) and Optical Circuit Switching (OCS) networks to aggregate Top-of-Rack switches. The OCS is also the connectivity substrate of splitters to the optical network. The optical multicast system implementation requires only commodity optical components. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Experimental and numerical results show simultaneous delivery of multicast flows to all receivers with steady throughput. Compared to IP multicast that is the electronic counterpart, optical multicast performs with less protocol complexity and reduced energy consumption. Compared to peer-to-peer multicast methods, it achieves at minimum an order of magnitude higher throughput for flows under 250 MB with significantly less connection overheads. Furthermore, for delivering 20 TB of data containing only 15% multicast flows, it reduces the total delivery energy consumption by 50% and improves latency by 55% compared to a data center with a sole non-blocking EPS network.

Cocaine addiction is associated with abnormal prefrontal function, increased striatal connectivity and sensitivity to monetary incentives, and decreased connectivity outside the human reward circuit.

PubMed

Vaquero, Lucía; Cámara, Estela; Sampedro, Frederic; Pérez de Los Cobos, José; Batlle, Francesca; Fabregas, Josep Maria; Sales, Joan Artur; Cervantes, Mercè; Ferrer, Xavier; Lazcano, Gerardo; Rodríguez-Fornells, Antoni; Riba, Jordi

2017-05-01

Cocaine addiction has been associated with increased sensitivity of the human reward circuit to drug-related stimuli. However, the capacity of non-drug incentives to engage this network is poorly understood. Here, we characterized the functional sensitivity to monetary incentives and the structural integrity of the human reward circuit in abstinent cocaine-dependent (CD) patients and their matched controls. We assessed the BOLD response to monetary gains and losses in 30 CD patients and 30 healthy controls performing a lottery task in a magnetic resonance imaging scanner. We measured brain gray matter volume (GMV) using voxel-based morphometry and white matter microstructure using voxel-based fractional anisotropy (FA). Functional data showed that, after monetary incentives, CD patients exhibited higher activation in the ventral striatum than controls. Furthermore, we observed an inverted BOLD response pattern in the prefrontal cortex, with activity being highest after unexpected high gains and lowest after losses. Patients showed increased GMV in the caudate and the orbitofrontal cortex, increased white matter FA in the orbito-striatal pathway but decreased FA in antero-posterior association bundles. Abnormal activation in the prefrontal cortex correlated with GMV and FA increases in the orbitofrontal cortex. While functional abnormalities in the ventral striatum were inversely correlated with abstinence duration, structural alterations were not. In conclusion, results suggest abnormal incentive processing in CD patients with high salience for rewards and punishments in subcortical structures but diminished prefrontal control after adverse outcomes. They further suggest that hypertrophy and hyper-connectivity within the reward circuit, to the expense of connectivity outside this network, characterize cocaine addiction. © 2016 Society for the Study of Addiction.

Passive and electro-optic polymer photonics and InP electronics integration

NASA Astrophysics Data System (ADS)

Zhang, Z.; Katopodis, V.; Groumas, P.; Konczykowska, A.; Dupuy, J.-.; Beretta, A.; Dede, A.; Miller, E.; Choi, J. H.; Harati, P.; Jorge, F.; Nodjiadjim, V.; Dinu, R.; Cangini, G.; Vannucci, A.; Felipe, D.; Maese-Novo, A.; Keil, N.; Bach, H.-.; Schell, Martin; Avramopoulos, H.; Kouloumentas, Ch.

2015-05-01

Hybrid photonic integration allows individual components to be developed at their best-suited material platforms without sacrificing the overall performance. In the past few years a polymer-enabled hybrid integration platform has been established, comprising 1) EO polymers for constructing low-complexity and low-cost Mach-Zehnder modulators (MZMs) with extremely high modulation bandwidth; 2) InP components for light sources, detectors, and high-speed electronics including MUX drivers and DEMUX circuits; 3) Ceramic (AIN) RF board that links the electronic signals within the package. On this platform, advanced optoelectronic modules have been demonstrated, including serial 100 Gb/s [1] and 2x100 Gb/s [2] optical transmitters, but also 400 Gb/s optoelectronic interfaces for intra-data center networks [3]. To expand the device functionalities to an unprecedented level and at the same time improve the integration compatibility with diversified active / passive photonic components, we have added a passive polymer-based photonic board (polyboard) as the 4th material system. This passive polyboard allows for low-cost fabrication of single-mode waveguide networks, enables fast and convenient integration of various thin-film elements (TFEs) to control the light polarization, and provides efficient thermo-optic elements (TOEs) for wavelength tuning, light amplitude regulation and light-path switching.

A Thermally Powered ISFET Array for On-Body pH Measurement.

PubMed

Douthwaite, Matthew; Koutsos, Ermis; Yates, David C; Mitcheson, Paul D; Georgiou, Pantelis

2017-12-01

Recent advances in electronics and electrochemical sensors have led to an emerging class of next generation wearables, detecting analytes in biofluids such as perspiration. Most of these devices utilize ion-selective electrodes (ISEs) as a detection method; however, ion-sensitive field-effect transistors (ISFETs) offer a solution with improved integration and a low power consumption. This work presents a wearable, thermoelectrically powered system composed of an application-specific integrated circuit (ASIC), two commercial power management integrated circuits and a network of commercial thermoelectric generators (TEGs). The ASIC is fabricated in 0.35 m CMOS and contains an ISFET array designed to read pH as a current, a processing module which averages the signal to reduce noise and encodes it into a frequency, and a transmitter. The output frequency has a measured sensitivity of 6 to 8 kHz/pH for a pH range of 7-5. It is shown that the sensing array and processing module has a power consumption 6 W and, therefore, can be entirely powered by body heat using a TEG. Array averaging is shown to reduce noise at these low power levels to 104 V (input referred integrated noise), reducing the minimum detectable limit of the ASIC to 0.008 pH units. The work forms the foundation and proves the feasibility of battery-less, on-body electrochemical for perspiration analysis in sports science and healthcare applications.

Metal contact engineering and registration-free fabrication of complementary metal-oxide semiconductor integrated circuits using aligned carbon nanotubes.

PubMed

Wang, Chuan; Ryu, Koungmin; Badmaev, Alexander; Zhang, Jialu; Zhou, Chongwu

2011-02-22

Complementary metal-oxide semiconductor (CMOS) operation is very desirable for logic circuit applications as it offers rail-to-rail swing, larger noise margin, and small static power consumption. However, it remains to be a challenging task for nanotube-based devices. Here in this paper, we report our progress on metal contact engineering for n-type nanotube transistors and CMOS integrated circuits using aligned carbon nanotubes. By using Pd as source/drain contacts for p-type transistors, small work function metal Gd as source/drain contacts for n-type transistors, and evaporated SiO(2) as a passivation layer, we have achieved n-type transistor, PN diode, and integrated CMOS inverter with an air-stable operation. Compared with other nanotube n-doping techniques, such as potassium doping, PEI doping, hydrazine doping, etc., using low work function metal contacts for n-type nanotube devices is not only air stable but also integrated circuit fabrication compatible. Moreover, our aligned nanotube platform for CMOS integrated circuits shows significant advantage over the previously reported individual nanotube platforms with respect to scalability and reproducibility and suggests a practical and realistic approach for nanotube-based CMOS integrated circuit applications.

Flexible and low-voltage integrated circuits constructed from high-performance nanocrystal transistors.

PubMed

Kim, David K; Lai, Yuming; Diroll, Benjamin T; Murray, Christopher B; Kagan, Cherie R

2012-01-01

Colloidal semiconductor nanocrystals are emerging as a new class of solution-processable materials for low-cost, flexible, thin-film electronics. Although these colloidal inks have been shown to form single, thin-film field-effect transistors with impressive characteristics, the use of multiple high-performance nanocrystal field-effect transistors in large-area integrated circuits has not been shown. This is needed to understand and demonstrate the applicability of these discrete nanocrystal field-effect transistors for advanced electronic technologies. Here we report solution-deposited nanocrystal integrated circuits, showing nanocrystal integrated circuit inverters, amplifiers and ring oscillators, constructed from high-performance, low-voltage, low-hysteresis CdSe nanocrystal field-effect transistors with electron mobilities of up to 22 cm(2) V(-1) s(-1), current modulation >10(6) and subthreshold swing of 0.28 V dec(-1). We fabricated the nanocrystal field-effect transistors and nanocrystal integrated circuits from colloidal inks on flexible plastic substrates and scaled the devices to operate at low voltages. We demonstrate that colloidal nanocrystal field-effect transistors can be used as building blocks to construct complex integrated circuits, promising a viable material for low-cost, flexible, large-area electronics.

Dissecting local circuits in vivo: integrated optogenetic and electrophysiology approaches for exploring inhibitory regulation of cortical activity.

PubMed

Cardin, Jessica A

2012-01-01

Local cortical circuit activity in vivo comprises a complex and flexible series of interactions between excitatory and inhibitory neurons. Our understanding of the functional interactions between these different neural populations has been limited by the difficulty of identifying and selectively manipulating the diverse and sparsely represented inhibitory interneuron classes in the intact brain. The integration of recently developed optical tools with traditional electrophysiological techniques provides a powerful window into the role of inhibition in regulating the activity of excitatory neurons. In particular, optogenetic targeting of specific cell classes reveals the distinct impacts of local inhibitory populations on other neurons in the surrounding local network. In addition to providing the ability to activate or suppress spiking in target cells, optogenetic activation identifies extracellularly recorded neurons by class, even when naturally occurring spike rates are extremely low. However, there are several important limitations on the use of these tools and the interpretation of resulting data. The purpose of this article is to outline the uses and limitations of optogenetic tools, along with current methods for achieving cell type-specific expression, and to highlight the advantages of an experimental approach combining optogenetics and electrophysiology to explore the role of inhibition in active networks. To illustrate the efficacy of these combined approaches, I present data comparing targeted manipulations of cortical fast-spiking, parvalbumin-expressing and low threshold-spiking, somatostatin-expressing interneurons in vivo. Copyright © 2011 Elsevier Ltd. All rights reserved.

Removal of Gross Air Embolization from Cardiopulmonary Bypass Circuits with Integrated Arterial Line Filters: A Comparison of Circuit Designs.

PubMed

Reagor, James A; Holt, David W

2016-03-01

Advances in technology, the desire to minimize blood product transfusions, and concerns relating to inflammatory mediators have lead many practitioners and manufacturers to minimize cardiopulmonary bypass (CBP) circuit designs. The oxygenator and arterial line filter (ALF) have been integrated into one device as a method of attaining a reduction in prime volume and surface area. The instructions for use of a currently available oxygenator with integrated ALF recommends incorporating a recirculation line distal to the oxygenator. However, according to an unscientific survey, 70% of respondents utilize CPB circuits incorporating integrated ALFs without a path of recirculation distal to the oxygenator outlet. Considering this circuit design, the ability to quickly remove a gross air bolus in the blood path distal to the oxygenator may be compromised. This in vitro study was designed to determine if the time required to remove a gross air bolus from a CPB circuit without a path of recirculation distal to the oxygenator will be significantly longer than that of a circuit with a path of recirculation distal to the oxygenator. A significant difference was found in the mean time required to remove a gross air bolus between the circuit designs (p = .0003). Additionally, There was found to be a statistically significant difference in the mean time required to remove a gross air bolus between Trial 1 and Trials 4 (p = .015) and 5 (p =.014) irrespective of the circuit design. Under the parameters of this study, a recirculation line distal to an oxygenator with an integrated ALF significantly decreases the time it takes to remove an air bolus from the CPB circuit and may be safer for clinical use than the same circuit without a recirculation line.

Dynamic Testing and Automatic Repair of Reconfigurable Wiring Harnesses

DTIC Science & Technology

2006-11-27

Switch An M ×N grid of switches configured to provide a M -input, N -output routing network. Permutation Network A permutation network performs an...wiring reduces the effective advantage of their reduced switch count, particularly when considering that regular grids (crossbar switches being a...are connected to. The outline circuit shown in Fig. 20 shows how a suitable ‘discovery probe’ might be implemented. The circuit shows a UART

Soliton quenching NLTL impulse circuit with a pulse forming network at the output

DOEpatents

McEwan, T.E.; Dallum, G.E.

1998-09-08

An impulse forming circuit is disclosed which produces a clean impulse from a nonlinear transmission line compressed step function without customary soliton ringing by means of a localized pulse shaping and differentiating network which shunts the nonlinear transmission line output to ground. 5 figs.

Technical Reliability Studies. EOS/ESD Technology Abstracts

DTIC Science & Technology

1982-01-01

RESISTANT BIPOLAR TRANSISTOR DESIGN AND ITS APPLICATIONS TO LINEAR INTEGRATED CIRCUITS 16145 MODULE ELECTROSTATIC DISCHARGE SIMULATOR 15786 SOME...T.M. 16476 STATIC DISCHARGE MODELING TECHNIQUES FOR EVALUATION OF INTEGRATED (FET) CIRCUIT DESTRUCTION 16145 MODULE ELECTAOSTATIC DISCHARGE SIMULATOR...PLASTIC LSI CIRCUITS PRklE, L.A., II 16145 MODULE ELECTROSTATIC DISCHARGE SIMULATOR PRICE, R.D. 13455 EVALUATION OF PLASTIC LSI CIRCUITS PSHAENICH, A

Silicon millimetre-wave integrated-circuit (SIMMWIC) SPST switch

NASA Astrophysics Data System (ADS)

Stabile, P. J.; Rosen, A.

1984-10-01

The first silicon millimetre-wave integrated circuit (SIMMWIC) has been successfully fabricated. This circuit is a monolithic SPST switch with a 3 dB bandwidth of 20 percent and a minimum isolation of 21.6 dB across the band (centre frequency is 36.75 GHz). This monolithic circuit is a low-cost reproducible building block for all millimetre-wave control applications.

Roles of epsilon-near-zero (ENZ) and mu-near-zero (MNZ) materials in optical metatronic circuit networks.

PubMed

Abbasi, Fereshteh; Engheta, Nader

2014-10-20

The concept of metamaterial-inspired nanocircuits, dubbed metatronics, was introduced in [Science 317, 1698 (2007); Phys. Rev. Lett. 95, 095504 (2005)]. It was suggested how optical lumped elements (nanoelements) can be made using subwavelength plasmonic or non-plasmonic particles. As a result, the optical metatronic equivalents of a number of electronic circuits, such as frequency mixers and filters, were suggested. In this work we further expand the concept of electronic lumped element networks into optical metatronic circuits and suggest a conceptual model applicable to various metatronic passive networks. In particular, we differentiate between the series and parallel networks using epsilon-near-zero (ENZ) and mu-near-zero (MNZ) materials. We employ layered structures with subwavelength thicknesses for the nanoelements as the building blocks of collections of metatronic networks. Furthermore, we explore how by choosing the non-zero constitutive parameters of the materials with specific dispersions, either Drude or Lorentzian dispersion with suitable parameters, capacitive and inductive responses can be achieved in both series and parallel networks. Next, we proceed with the one-to-one analogy between electronic circuits and optical metatronic filter layered networks and justify our analogies by comparing the frequency response of the two paradigms. Finally, we examine the material dispersion of near-zero relative permittivity as well as other physically important material considerations such as losses.

Demonstration of Inexact Computing Implemented in the JPEG Compression Algorithm using Probabilistic Boolean Logic applied to CMOS Components

DTIC Science & Technology

2015-12-24

Signal to Noise Ratio SPICE Simulation Program with Integrated Circuit Emphasis TIFF Tagged Image File Format USC University of Southern California xvii...sources can create errors in digital circuits. These effects can be simulated using Simulation Program with Integrated Circuit Emphasis ( SPICE ) or...compute summary statistics. 4.1 Circuit Simulations Noisy analog circuits can be simulated in SPICE or Cadence SpectreTM software via noisy voltage

Application of Phasor Measurement Units for Protection of Distribution Networks with High Penetration of Photovoltaic Sources

NASA Astrophysics Data System (ADS)

Meskin, Matin

The rate of the integration of distributed generation (DG) units to the distribution level to meet the growth in demand increases as a reasonable replacement for costly network expansion. This integration brings many advantages to the consumers and power grids, as well as giving rise to more challenges in relation to protection and control. Recent research has brought to light the negative effects of DG units on short circuit currents and overcurrent (OC) protection systems in distribution networks. Change in the direction of fault current flow, increment or decrement of fault current magnitude, blindness of protection, feeder sympathy trip, nuisance trip of interrupting devices, and the disruption of coordination between protective devices are some potential impacts of DG unit integration. Among other types of DG units, the integration of renewable energy resources into the electric grid has seen a vast improvement in recent years. In particular, the interconnection of photovoltaic (PV) sources to the medium voltage (MV) distribution networks has experienced a rapid increase in the last decade. In this work, the effect of PV source on conventional OC relays in MV distribution networks is shown. It is indicated that the PV output fluctuation, due to changes in solar radiation, causes the magnitude and direction of the current to change haphazardly. These variations may result in the poor operation of OC relays as the main protective devices in the MV distribution networks. In other words, due to the bi-directional power flow characteristic and the fluctuation of current magnitude occurring in the presence of PV sources, a specific setting of OC relays is difficult to realize. Therefore, OC relays may operate in normal conditions. To improve the OC relay operation, a voltage-dependent-overcurrent protection is proposed. Although, this new method prevents the OC relay from maloperation, its ability to detect earth faults and high impedance faults is poor. Thus, a comprehensive protective system is suggested at the end of the dissertation. The proposed method is based on the application of the phasor measurement unit (PMU) and the differential protection method. All of the current magnitudes and angles are collected by PMU and are sent to the phasor data concentrator (PDC), where a differential protection algorithm is applied to these data. If any fault is detected, the trip will be sent back to the corresponding circuit breakers across the network. Higher selectivity, sensitivity, and faster operation in the differential protection are superior to those of other protection schemes. Differential protection operates as unit protection, which means that it operates only when there is a fault in the protection zone. It does not function for faults occurring out of zone. Therefore, no coordination is required between differential protections across the power system. Moreover, the misoperation of this protective scheme is less likely as compared to other protection methods.

The human phosphotyrosine signaling network: Evolution and hotspots of hijacking in cancer

PubMed Central

Li, Lei; Tibiche, Chabane; Fu, Cong; Kaneko, Tomonori; Moran, Michael F.; Schiller, Martin R.; Li, Shawn Shun-Cheng; Wang, Edwin

2012-01-01

Phosphotyrosine (pTyr) signaling, which plays a central role in cell–cell and cell–environment interactions, has been considered to be an evolutionary innovation in multicellular metazoans. However, neither the emergence nor the evolution of the human pTyr signaling system is currently understood. Tyrosine kinase (TK) circuits, each of which consists of a TK writer, a kinase substrate, and a related reader, such as Src homology (SH) 2 domains and pTyr-binding (PTB) domains, comprise the core machinery of the pTyr signaling network. In this study, we analyzed the evolutionary trajectories of 583 literature-derived and 50,000 computationally predicted human TK circuits in 19 representative eukaryotic species and assigned their evolutionary origins. We found that human TK circuits for intracellular pTyr signaling originated largely from primitive organisms, whereas the inter- or extracellular signaling circuits experienced significant expansion in the bilaterian lineage through the “back-wiring” of newly evolved kinases to primitive substrates and SH2/PTB domains. Conversely, the TK circuits that are involved in tissue-specific signaling evolved mainly in vertebrates by the back-wiring of vertebrate substrates to primitive kinases and SH2/PTB domains. Importantly, we found that cancer signaling preferentially employs the pTyr sites, which are linked to more TK circuits. Our work provides insights into the evolutionary paths of the human pTyr signaling circuits and suggests the use of a network approach for cancer intervention through the targeting of key pTyr sites and their associated signaling hubs in the network. PMID:22194470

Optical printed circuit board (O-PCB) and VLSI photonic integrated circuits: visions, challenges, and progresses

NASA Astrophysics Data System (ADS)

Lee, El-Hang; Lee, S. G.; O, B. H.; Park, S. G.; Noh, H. S.; Kim, K. H.; Song, S. H.

2006-09-01

A collective overview and review is presented on the original work conducted on the theory, design, fabrication, and in-tegration of micro/nano-scale optical wires and photonic devices for applications in a newly-conceived photonic systems called "optical printed circuit board" (O-PCBs) and "VLSI photonic integrated circuits" (VLSI-PIC). These are aimed for compact, high-speed, multi-functional, intelligent, light-weight, low-energy and environmentally friendly, low-cost, and high-volume applications to complement or surpass the capabilities of electrical PCBs (E-PCBs) and/or VLSI electronic integrated circuit (VLSI-IC) systems. These consist of 2-dimensional or 3-dimensional planar arrays of micro/nano-optical wires and circuits to perform the functions of all-optical sensing, storing, transporting, processing, switching, routing and distributing optical signals on flat modular boards or substrates. The integrated optical devices include micro/nano-scale waveguides, lasers, detectors, switches, sensors, directional couplers, multi-mode interference devices, ring-resonators, photonic crystal devices, plasmonic devices, and quantum devices, made of polymer, silicon and other semiconductor materials. For VLSI photonic integration, photonic crystals and plasmonic structures have been used. Scientific and technological issues concerning the processes of miniaturization, interconnection and integration of these systems as applicable to board-to-board, chip-to-chip, and intra-chip integration, are discussed along with applications for future computers, telecommunications, and sensor-systems. Visions and challenges toward these goals are also discussed.

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

PubMed Central

Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

2016-01-01

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

Model-based analysis of pattern motion processing in mouse primary visual cortex

PubMed Central

Muir, Dylan R.; Roth, Morgane M.; Helmchen, Fritjof; Kampa, Björn M.

2015-01-01

Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features. PMID:26300738

Nanophotonic integrated circuits from nanoresonators grown on silicon.

PubMed

Chen, Roger; Ng, Kar Wei; Ko, Wai Son; Parekh, Devang; Lu, Fanglu; Tran, Thai-Truong D; Li, Kun; Chang-Hasnain, Connie

2014-07-07

Harnessing light with photonic circuits promises to catalyse powerful new technologies much like electronic circuits have in the past. Analogous to Moore's law, complexity and functionality of photonic integrated circuits depend on device size and performance scale. Semiconductor nanostructures offer an attractive approach to miniaturize photonics. However, shrinking photonics has come at great cost to performance, and assembling such devices into functional photonic circuits has remained an unfulfilled feat. Here we demonstrate an on-chip optical link constructed from InGaAs nanoresonators grown directly on a silicon substrate. Using nanoresonators, we show a complete toolkit of circuit elements including light emitters, photodetectors and a photovoltaic power supply. Devices operate with gigahertz bandwidths while consuming subpicojoule energy per bit, vastly eclipsing performance of prior nanostructure-based optoelectronics. Additionally, electrically driven stimulated emission from an as-grown nanostructure is presented for the first time. These results reveal a roadmap towards future ultradense nanophotonic integrated circuits.

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

Ryu, C.; Boshier, M. G.

An integrated coherent matter wave circuit is a single device, analogous to an integrated optical circuit, in which coherent de Broglie waves are created and then launched into waveguides where they can be switched, divided, recombined, and detected as they propagate. Applications of such circuits include guided atom interferometers, atomtronic circuits, and precisely controlled delivery of atoms. We report experiments demonstrating integrated circuits for guided coherent matter waves. The circuit elements are created with the painted potential technique, a form of time-averaged optical dipole potential in which a rapidly moving, tightly focused laser beam exerts forces on atoms through theirmore » electric polarizability. Moreover, the source of coherent matter waves is a Bose–Einstein condensate (BEC). Finally, we launch BECs into painted waveguides that guide them around bends and form switches, phase coherent beamsplitters, and closed circuits. These are the basic elements that are needed to engineer arbitrarily complex matter wave circuitry.« less

Computer model of a reverberant and parallel circuit coupling

NASA Astrophysics Data System (ADS)

Kalil, Camila de Andrade; de Castro, Maria Clícia Stelling; Cortez, Célia Martins

2017-11-01

The objective of the present study was to deepen the knowledge about the functioning of the neural circuits by implementing a signal transmission model using the Graph Theory in a small network of neurons composed of an interconnected reverberant and parallel circuit, in order to investigate the processing of the signals in each of them and the effects on the output of the network. For this, a program was developed in C language and simulations were done using neurophysiological data obtained in the literature.

Integrated testing system FiTest for diagnosis of PCBA

NASA Astrophysics Data System (ADS)

Bogdan, Arkadiusz; Lesniak, Adam

2016-12-01

This article presents the innovative integrated testing system FiTest for automatic, quick inspection of printed circuit board assemblies (PCBA) manufactured in Surface Mount Technology (SMT). Integration of Automatic Optical Inspection (AOI), In-Circuit Tests (ICT) and Functional Circuit Tests (FCT) resulted in universal hardware platform for testing variety of electronic circuits. The platform provides increased test coverage, decreased level of false calls and optimization of test duration. The platform is equipped with powerful algorithms performing tests in a stable and repetitive way and providing effective management of diagnosis.

International Conference on Integrated Optical Circuit Engineering, 1st, Cambridge, MA, October 23-25, 1984, Proceedings

NASA Astrophysics Data System (ADS)

Ostrowsky, D. B.; Sriram, S.

Aspects of waveguide technology are explored, taking into account waveguide fabrication techniques in GaAs/GaAlAs, the design and fabrication of AlGaAs/GaAs phase couplers for optical integrated circuit applications, ion implanted GaAs integrated optics fabrication technology, a direct writing electron beam lithography based process for the realization of optoelectronic integrated circuits, and advances in the development of semiconductor integrated optical circuits for telecommunications. Other subjects examined are related to optical signal processing, optical switching, and questions of optical bistability and logic. Attention is given to acousto-optic techniques in integrated optics, acousto-optic Bragg diffraction in proton exchanged waveguides, optical threshold logic architectures for hybrid binary/residue processors, integrated optical modulation and switching, all-optic logic devices for waveguide optics, optoelectronic switching, high-speed photodetector switching, and a mechanical optical switch.

Analog integrated circuits design for processing physiological signals.

PubMed

Li, Yan; Poon, Carmen C Y; Zhang, Yuan-Ting

2010-01-01

Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.

An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks

PubMed Central

Sánchez, Antonio; Blanc, Sara; Yuste, Pedro; Perles, Angel; Serrano, Juan José

2012-01-01

This paper is focused on the description of the physical layer of a new acoustic modem called ITACA. The modem architecture includes as a major novelty an ultra-low power asynchronous wake-up system implementation for underwater acoustic transmission that is based on a low-cost off-the-shelf RFID peripheral integrated circuit. This feature enables a reduced power dissipation of 10 μW in stand-by mode and registers very low power values during reception and transmission. The modem also incorporates clear channel assessment (CCA) to support CSMA-based medium access control (MAC) layer protocols. The design is part of a compact platform for a long-life short/medium range underwater wireless sensor network. PMID:22969324

Intelsat TDMA and its implementation in Australia

NASA Astrophysics Data System (ADS)

Howe, Stuart

The developmental history and characteristics of the Intelsat digital communications network are surveyed, with a focus on the current implementation status in Australia. Topics addressed include the fundamental principles and advantages of a TDMA system, the hardware required for a TDMA traffic station, and the Intelsat Indian Ocean Primary satellite network. Detailed consideration is given to TDMA test equipment (burst-mode link analyzers, PCM DSI test sets, burst-power meters, burst negators, and reference burst generators), terminal integration with terrestrial and RF links (TWT sharing and equalization), equipment compatibility, and traffic. Plans call for 950 TDMA circuits by the end of 1990, representing about 36.5 percent of the traffic between Australia and Europe, Africa, India and Pakistan, and the Middle East.

An ultra-low power and flexible acoustic modem design to develop energy-efficient underwater sensor networks.

PubMed

Sánchez, Antonio; Blanc, Sara; Yuste, Pedro; Perles, Angel; Serrano, Juan José

2012-01-01

This paper is focused on the description of the physical layer of a new acoustic modem called ITACA. The modem architecture includes as a major novelty an ultra-low power asynchronous wake-up system implementation for underwater acoustic transmission that is based on a low-cost off-the-shelf RFID peripheral integrated circuit. This feature enables a reduced power dissipation of 10 μW in stand-by mode and registers very low power values during reception and transmission. The modem also incorporates clear channel assessment (CCA) to support CSMA-based medium access control (MAC) layer protocols. The design is part of a compact platform for a long-life short/medium range underwater wireless sensor network.

Optimized Mixing in Microchannels with Integrated Microactuators

NASA Astrophysics Data System (ADS)

Folk, Christopher Richard

Microscale valves and pumps have been designed and fabricated for integration into a microfluidic circuit. Furthermore, a micromixer for this circuit has been designed and optimized. N-isopropylacrylamide (NIPA) gels have been fabricated and actuated directly with heat and indirectly by laser. A new method for photopatterning these gels based on photoinitiation has been used to fabricate hydrogel valves down to 50 mum in diameter. Hydrogel valves have been fabricated in situ in a microfluidic network. The valves open in 27 seconds and close via diffusion of water into the gel in 128 seconds, which is faster than other optically-driven polymers used for large displacements. In this research, azobis-isobutyronitrile (AIBN) is incorporated into a variety of polydimethylsiloxane (PDMS) pump chambers. The AIBN is heated via integrated resistive heaters and decomposes to release nitrogen gas. The nitrogen gas provides impulse power to a PDMS diaphragm to displace the fluid. The pump devices have been built and characterized. Lastly, in this work, we describe the use of combined fluid dynamic and diffusion modeling to simulate a micromixer based on the elements above. The micromixer is optimized via Design of Experiments to produce an optimized geometry for mixing. The optimization is validated via comparison to previous work through the Strouhal number.

Low-power analog integrated circuits for wireless ECG acquisition systems.

PubMed

Tsai, Tsung-Heng; Hong, Jia-Hua; Wang, Liang-Hung; Lee, Shuenn-Yuh

2012-09-01

This paper presents low-power analog ICs for wireless ECG acquisition systems. Considering the power-efficient communication in the body sensor network, the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration. To acquire the ECG signal, a low-power analog front-end system, including an ECG signal acquisition board, an on-chip low-pass filter, and an on-chip successive-approximation analog-to-digital converter for portable ECG detection devices is presented. A quadrature CMOS voltage-controlled oscillator and a 2.4 GHz direct-conversion transmitter with a power amplifier and upconversion mixer are also developed to transmit the ECG signal through wireless communication. In the receiver, a 2.4 GHz fully integrated CMOS RF front end with a low-noise amplifier, differential power splitter, and quadrature mixer based on current-reused folded architecture is proposed. The circuits have been implemented to meet the specifications of the IEEE 802.15.4 2.4 GHz standard. The low-power ICs of the wireless ECG acquisition systems have been fabricated using a 0.18 μm Taiwan Semiconductor Manufacturing Company (TSMC) CMOS standard process. The measured results on the human body reveal that ECG signals can be acquired effectively by the proposed low-power analog front-end ICs.

EEG acquisition system based on active electrodes with common-mode interference suppression by Driving Right Leg circuit.

PubMed

Guermandi, Marco; Bigucci, Alessandro; Franchi Scarselli, Eleonora; Guerrieri, Roberto

2015-01-01

We present a system for the acquisition of EEG signals based on active electrodes and implementing a Driving Right Leg circuit (DgRL). DgRL allows for single-ended amplification and analog-to-digital conversion, still guaranteeing a common mode rejection in excess of 110 dB. This allows the system to acquire high-quality EEG signals essentially removing network interference for both wet and dry-contact electrodes. The front-end amplification stage is integrated on the electrode, minimizing the system's sensitivity to electrode contact quality, cable movement and common mode interference. The A/D conversion stage can be either integrated in the remote back-end or placed on the head as well, allowing for an all-digital communication to the back-end. Noise integrated in the band from 0.5 to 100 Hz is comprised between 0.62 and 1.3 μV, depending on the configuration. Current consumption for the amplification and A/D conversion of one channel is 390 μA. Thanks to its low noise, the high level of interference suppression and its quick setup capabilities, the system is particularly suitable for use outside clinical environments, such as in home care, brain-computer interfaces or consumer-oriented applications.

Ecological connectivity networks in rapidly expanding cities.

PubMed

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for biodiversity conservation and urban planning.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

PubMed

He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

2014-01-01

Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

PubMed Central

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies. PMID:25350277

Testing interconnected VLSI circuits in the Big Viterbi Decoder

NASA Technical Reports Server (NTRS)

Onyszchuk, I. M.

1991-01-01

The Big Viterbi Decoder (BVD) is a powerful error-correcting hardware device for the Deep Space Network (DSN), in support of the Galileo and Comet Rendezvous Asteroid Flyby (CRAF)/Cassini Missions. Recently, a prototype was completed and run successfully at 400,000 or more decoded bits per second. This prototype is a complex digital system whose core arithmetic unit consists of 256 identical very large scale integration (VLSI) gate-array chips, 16 on each of 16 identical boards which are connected through a 28-layer, printed-circuit backplane using 4416 wires. Special techniques were developed for debugging, testing, and locating faults inside individual chips, on boards, and within the entire decoder. The methods are based upon hierarchical structure in the decoder, and require that chips or boards be wired themselves as Viterbi decoders. The basic procedure consists of sending a small set of known, very noisy channel symbols through a decoder, and matching observables against values computed by a software simulation. Also, tests were devised for finding open and short-circuited wires which connect VLSI chips on the boards and through the backplane.

Automated optical inspection of liquid crystal display anisotropic conductive film bonding

NASA Astrophysics Data System (ADS)

Ni, Guangming; Du, Xiaohui; Liu, Lin; Zhang, Jing; Liu, Juanxiu; Liu, Yong

2016-10-01

Anisotropic conductive film (ACF) bonding is widely used in the liquid crystal display (LCD) industry. It implements circuit connection between screens and flexible printed circuits or integrated circuits. Conductive microspheres in ACF are key factors that influence LCD quality, because the conductive microspheres' quantity and shape deformation rate affect the interconnection resistance. Although this issue has been studied extensively by prior work, quick and accurate methods to inspect the quality of ACF bonding are still missing in the actual production process. We propose a method to inspect ACF bonding effectively by using automated optical inspection. The method has three steps. The first step is that it acquires images of the detection zones using a differential interference contrast (DIC) imaging system. The second step is that it identifies the conductive microspheres and their shape deformation rate using quantitative analysis of the characteristics of the DIC images. The final step is that it inspects ACF bonding using a back propagation trained neural network. The result shows that the miss rate is lower than 0.1%, and the false inspection rate is lower than 0.05%.

Process development of beam-lead silicon-gate COS/MOS integrated circuits

NASA Technical Reports Server (NTRS)

Baptiste, B.; Boesenberg, W.

1974-01-01

Two processes for the fabrication of beam-leaded COS/MOS integrated circuits are described. The first process utilizes a composite gate dielectric of 800 A of silicon dioxide and 450 A of pyrolytically deposited A12O3 as an impurity barrier. The second process utilizes polysilicon gate metallization over which a sealing layer of 1000 A of pyrolytic Si3N4 is deposited. Three beam-lead integrated circuits have been implemented with the first process: (1) CD4000BL - three-input NOR gate; (2) CD4007BL - triple inverter; and (3) CD4013BL - dual D flip flop. An arithmetic and logic unit (ALU) integrated circuit was designed and implemented with the second process. The ALU chip allows addition with four bit accuracy. Processing details, device design and device characterization, circuit performance and life data are presented.

Boosting functionality of synthetic DNA circuits with tailored deactivation

PubMed Central

Montagne, Kevin; Gines, Guillaume; Fujii, Teruo; Rondelez, Yannick

2016-01-01

Molecular programming takes advantage of synthetic nucleic acid biochemistry to assemble networks of reactions, in vitro, with the double goal of better understanding cellular regulation and providing information-processing capabilities to man-made chemical systems. The function of molecular circuits is deeply related to their topological structure, but dynamical features (rate laws) also play a critical role. Here we introduce a mechanism to tune the nonlinearities associated with individual nodes of a synthetic network. This mechanism is based on programming deactivation laws using dedicated saturable pathways. We demonstrate this approach through the conversion of a single-node homoeostatic network into a bistable and reversible switch. Furthermore, we prove its generality by adding new functions to the library of reported man-made molecular devices: a system with three addressable bits of memory, and the first DNA-encoded excitable circuit. Specific saturable deactivation pathways thus greatly enrich the functional capability of a given circuit topology. PMID:27845324

Ring Attractor Dynamics Emerge from a Spiking Model of the Entire Protocerebral Bridge.

PubMed

Kakaria, Kyobi S; de Bivort, Benjamin L

2017-01-01

Animal navigation is accomplished by a combination of landmark-following and dead reckoning based on estimates of self motion. Both of these approaches require the encoding of heading information, which can be represented as an allocentric or egocentric azimuthal angle. Recently, Ca 2+ correlates of landmark position and heading direction, in egocentric coordinates, were observed in the ellipsoid body (EB), a ring-shaped processing unit in the fly central complex (CX; Seelig and Jayaraman, 2015). These correlates displayed key dynamics of so-called ring attractors, namely: (1) responsiveness to the position of external stimuli; (2) persistence in the absence of external stimuli; (3) locking onto a single external stimulus when presented with two competitors; (4) stochastically switching between competitors with low probability; and (5) sliding or jumping between positions when an external stimulus moves. We hypothesized that ring attractor-like activity in the EB arises from reciprocal neuronal connections to a related structure, the protocerebral bridge (PB). Using recent light-microscopy resolution catalogs of neuronal cell types in the PB (Lin et al., 2013; Wolff et al., 2015), we determined a connectivity matrix for the PB-EB circuit. When activity in this network was simulated using a leaky-integrate-and-fire model, we observed patterns of activity that closely resemble the reported Ca 2+ phenomena. All qualitative ring attractor behaviors were recapitulated in our model, allowing us to predict failure modes of the putative PB-EB ring attractor and the circuit dynamics phenotypes of thermogenetic or optogenetic manipulations. Ring attractor dynamics emerged under a wide variety of parameter configurations, even including non-spiking leaky-integrator implementations. This suggests that the ring-attractor computation is a robust output of this circuit, apparently arising from its high-level network properties (topological configuration, local excitation and long-range inhibition) rather than fine-scale biological detail.

The Effects of Space Radiation on Linear Integrated Circuit

NASA Technical Reports Server (NTRS)

Johnston, A.

2000-01-01

Permanent and transient effects are discussed that are induced in linear integrated circuits by space radiation. Recent developments include enhanced damage at low dose rate, increased damage from protons due to displacement effects, and transients in digital comparators that can cause circuit malfunctions.

35 GHz integrated circuit rectifying antenna with 33 percent efficiency

NASA Technical Reports Server (NTRS)

Yoo, T.-W.; Chang, K.

1991-01-01

A 35 GHz integrated circuit rectifying antenna (rectenna) has been developed using a microstrip dipole antenna and beam-lead mixer diode. Greater than 33 percent conversion efficiency has been achieved. The circuit should have applications in microwave/millimeter-wave power transmission and detection.

Optical slotted circuit switched network: a bandwidth efficient alternative to wavelength-routed network

NASA Astrophysics Data System (ADS)

Li, Yan; Collier, Martin

2007-11-01

Wavelength-routed networks have received enormous attention due to the fact that they are relatively simple to implement and implicitly offer Quality of Service (QoS) guarantees. However, they suffer from a bandwidth inefficiency problem and require complex Routing and Wavelength Assignment (RWA). Most attempts to address the above issues exploit the joint use of WDM and TDM technologies. The resultant TDM-based wavelength-routed networks partition the wavelength bandwidth into fixed-length time slots organized as a fixed-length frame. Multiple connections can thus time-share a wavelength and the grooming of their traffic leads to better bandwidth utilization. The capability of switching in both wavelength and time domains in such networks also mitigates the RWA problem. However, TMD-based wavelength-routed networks work in synchronous mode and strict synchronization among all network nodes is required. Global synchronization for all-optical networks which operate at extremely high speed is technically challenging, and deploying an optical synchronizer for each wavelength involves considerable cost. An Optical Slotted Circuit Switching (OSCS) architecture is proposed in this paper. In an OSCS network, slotted circuits are created to better utilize the wavelength bandwidth than in classic wavelength-routed networks. The operation of the protocol is such as to avoid the need for global synchronization required by TDM-based wavelength-routed networks.

A Myc-driven self-reinforcing regulatory network maintains mouse embryonic stem cell identity

PubMed Central

Fagnocchi, Luca; Cherubini, Alessandro; Hatsuda, Hiroshi; Fasciani, Alessandra; Mazzoleni, Stefania; Poli, Vittoria; Berno, Valeria; Rossi, Riccardo L.; Reinbold, Rolland; Endele, Max; Schroeder, Timm; Rocchigiani, Marina; Szkarłat, Żaneta; Oliviero, Salvatore; Dalton, Stephen; Zippo, Alessio

2016-01-01

Stem cell identity depends on the integration of extrinsic and intrinsic signals, which directly influence the maintenance of their epigenetic state. Although Myc transcription factors play a major role in stem cell self-renewal and pluripotency, their integration with signalling pathways and epigenetic regulators remains poorly defined. We addressed this point by profiling the gene expression and epigenetic pattern in ESCs whose growth depends on conditional Myc activity. Here we show that Myc potentiates the Wnt/β-catenin signalling pathway, which cooperates with the transcriptional regulatory network in sustaining ESC self-renewal. Myc activation results in the transcriptional repression of Wnt antagonists through the direct recruitment of PRC2 on these targets. The consequent potentiation of the autocrine Wnt/β-catenin signalling induces the transcriptional activation of the endogenous Myc family members, which in turn activates a Myc-driven self-reinforcing circuit. Thus, our data unravel a Myc-dependent self-propagating epigenetic memory in the maintenance of ESC self-renewal capacity. PMID:27301576

A Myc-driven self-reinforcing regulatory network maintains mouse embryonic stem cell identity.

PubMed

Fagnocchi, Luca; Cherubini, Alessandro; Hatsuda, Hiroshi; Fasciani, Alessandra; Mazzoleni, Stefania; Poli, Vittoria; Berno, Valeria; Rossi, Riccardo L; Reinbold, Rolland; Endele, Max; Schroeder, Timm; Rocchigiani, Marina; Szkarłat, Żaneta; Oliviero, Salvatore; Dalton, Stephen; Zippo, Alessio

2016-06-15

Stem cell identity depends on the integration of extrinsic and intrinsic signals, which directly influence the maintenance of their epigenetic state. Although Myc transcription factors play a major role in stem cell self-renewal and pluripotency, their integration with signalling pathways and epigenetic regulators remains poorly defined. We addressed this point by profiling the gene expression and epigenetic pattern in ESCs whose growth depends on conditional Myc activity. Here we show that Myc potentiates the Wnt/β-catenin signalling pathway, which cooperates with the transcriptional regulatory network in sustaining ESC self-renewal. Myc activation results in the transcriptional repression of Wnt antagonists through the direct recruitment of PRC2 on these targets. The consequent potentiation of the autocrine Wnt/β-catenin signalling induces the transcriptional activation of the endogenous Myc family members, which in turn activates a Myc-driven self-reinforcing circuit. Thus, our data unravel a Myc-dependent self-propagating epigenetic memory in the maintenance of ESC self-renewal capacity.

A reliable low cost integrated wireless sensor network for water quality monitoring and level control system in UAE

NASA Astrophysics Data System (ADS)

Abou-Elnour, Ali; Khaleeq, Hyder; Abou-Elnour, Ahmad

2016-04-01

In the present work, wireless sensor network and real-time controlling and monitoring system are integrated for efficient water quality monitoring for environmental and domestic applications. The proposed system has three main components (i) the sensor circuits, (ii) the wireless communication system, and (iii) the monitoring and controlling unit. LabView software has been used in the implementation of the monitoring and controlling system. On the other hand, ZigBee and myRIO wireless modules have been used to implement the wireless system. The water quality parameters are accurately measured by the present computer based monitoring system and the measurement results are instantaneously transmitted and published with minimum infrastructure costs and maximum flexibility in term of distance or location. The mobility and durability of the proposed system are further enhanced by fully powering via a photovoltaic system. The reliability and effectiveness of the system are evaluated under realistic operating conditions.

Mammalian synthetic biology: emerging medical applications

PubMed Central

Kis, Zoltán; Pereira, Hugo Sant'Ana; Homma, Takayuki; Pedrigi, Ryan M.; Krams, Rob

2015-01-01

In this review, we discuss new emerging medical applications of the rapidly evolving field of mammalian synthetic biology. We start with simple mammalian synthetic biological components and move towards more complex and therapy-oriented gene circuits. A comprehensive list of ON–OFF switches, categorized into transcriptional, post-transcriptional, translational and post-translational, is presented in the first sections. Subsequently, Boolean logic gates, synthetic mammalian oscillators and toggle switches will be described. Several synthetic gene networks are further reviewed in the medical applications section, including cancer therapy gene circuits, immuno-regulatory networks, among others. The final sections focus on the applicability of synthetic gene networks to drug discovery, drug delivery, receptor-activating gene circuits and mammalian biomanufacturing processes. PMID:25808341

The physics of bacterial decision making.

PubMed

Ben-Jacob, Eshel; Lu, Mingyang; Schultz, Daniel; Onuchic, Jose' N

2014-01-01

The choice that bacteria make between sporulation and competence when subjected to stress provides a prototypical example of collective cell fate determination that is stochastic on the individual cell level, yet predictable (deterministic) on the population level. This collective decision is performed by an elaborated gene network. Considerable effort has been devoted to simplify its complexity by taking physics approaches to untangle the basic functional modules that are integrated to form the complete network: (1) A stochastic switch whose transition probability is controlled by two order parameters-population density and internal/external stress. (2) An adaptable timer whose clock rate is normalized by the same two previous order parameters. (3) Sensing units which measure population density and external stress. (4) A communication module that exchanges information about the cells' internal stress levels. (5) An oscillating gate of the stochastic switch which is regulated by the timer. The unique circuit architecture of the gate allows special dynamics and noise management features. The gate opens a window of opportunity in time for competence transitions, during which the circuit generates oscillations that are translated into a chain of short intervals with high transition probability. In addition, the unique architecture of the gate allows filtering of external noise and robustness against variations in circuit parameters and internal noise. We illustrate that a physics approach can be very valuable in investigating the decision process and in identifying its general principles. We also show that both cell-cell variability and noise have important functional roles in the collectively controlled individual decisions.