A Study of the Robustness Against SEUs of Digital Circuits Implemented with FPGA DSPs

In this paper we present an experimental validation of the reliability increase of digital circuits implemented in XilinxTMFPGAs when they are implemented using the DSPs (Digital Signal Processors) that are available in the reconfigurable device. For this purpose, we have used a fault-injection platform developed by our research group, NESSY [1]. The presented experiments demonstrate that the probability of occurrence of a SEU effect is similar both in the circuits implemented with and without using embedded DSPs. However, the former are more efficient in terms of area usage, which leads to a decrease in the probability of a SEU occurrence.

Synchronization of Heteroclinic Circuits Through Learning in Chains of Neural Motifs

The synchronization of oscillatory activity in networks of neural networks is usually implemented through coupling the state variables describing neuronal dynamics. In this study we discuss another but complementary mechanism based on a learning process with memory. A driver network motif, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven motif, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner motif can dynamically copy the coupling pattern of the teacher and thus synchronize oscillations with the teacher. Then, we demonstrate that the replication of the WLC dynamics occurs for intermediate memory lengths only. In a unidirectional chain of N motifs coupled through teacher-learner paradigm the time interval required for pattern replication grows linearly with the chain size, hence the learning process does not blow up and at the end we observe phase synchronized oscillations along the chain. We also show that in a learning chain closed into a ring the network motifs come to a consensus, i.e. to a state with the same connectivity pattern corresponding to the mean initial pattern averaged over all network motifs.

Synthetic Circuits for Feedback and Detection in Bacteria

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.

Electrical characterization of electronic circuits produced by inkjet printing

Dissertação de Mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014

Photonic packaging: transforming silicon photonic integrated circuits into photonic devices

Dedicated multi-project wafer (MPW) runs for photonic integrated circuits (PICs) from Si foundries mean that researchers and small-to-medium enterprises (SMEs) can now afford to design and fabricate Si photonic chips. While these bare Si-PICs are adequate for testing new device and circuit designs on a probe-station, they cannot be developed into prototype devices, or tested outside of the laboratory, without first packaging them into a durable module. Photonic packaging of PICs is significantly more challenging, and currently orders of magnitude more expensive, than electronic packaging, because it calls for robust micron-level alignment of optical components, precise real-time temperature control, and often a high degree of vertical and horizontal electrical integration. Photonic packaging is perhaps the most significant bottleneck in the development of commercially relevant integrated photonic devices. This article describes how the key optical, electrical, and thermal requirements of Si-PIC packaging can be met, and what further progress is needed before industrial scale-up can be achieved.

South Carolina/Common Pleas Court Circuits Meeting Benchmark ... as of July 31, 2016

This is a list of the courts in all the circuits of South Carolina and the percentage of cases disposed of in 365 day or less. None of the courts met the 80% benchmark.

South Carolina/family court circuits meeting benchmark : 80% of pending docket 365 days or less as of July 31, 2016

This is a diagram broken down by circuits of the percentage of family courts meeting the benchmark of 80% of disposing of cases within a year. 15 out of the 16 circuits met the standard.

South Carolina/Common Pleas Court Circuits Meeting Benchmark ... as of June 30, 2016

This is a list of the courts in all the circuits of South Carolina and the percentage of cases disposed of in 365 day or less. All but four of the courts met the 80% benchmark.

South Carolina/Family Court Circuits Meeting Benchmark : 80% of Pending Docket 365 Days or Less as of June 30, 2016

This is a diagram broken down by circuits of the percentage of family courts meeting the benchmark of 80% of disposing of cases within a year. Seven out of the 16 circuits met the standard.

South Carolina/general sessions court circuits meeting benchmark : 80% of pending docket 365 days or less as of September 30, 2016

This document provides statistics on criminal and general sessions courts meeting the benchmark of 80% of pending dockets broken down by circuits and counties.

PCM-based in-memory computing: architectures, circuits and applications

Analog In-memory Computing (AIMC) has been proposed in the context of Beyond Von Neumann architectures as a valid strategy to reduce internal data transfers energy consumption and latency, and to improve compute efficiency. The aim of AIMC is to perform computations within the memory unit, typically leveraging the physical features of memory devices. Among resistive Non-volatile Memories (NVMs), Phase-change Memory (PCM) has become a promising technology due to its intrinsic capability to store multilevel data. Hence, PCM technology is currently investigated to enhance the possibilities and the applications of AIMC. This thesis aims at exploring the potential of new PCM-based architectures as in-memory computational accelerators. In a first step, a preliminar experimental characterization of PCM devices has been carried out in an AIMC perspective. PCM cells non-idealities, such as time-drift, noise, and non-linearity have been studied to develop a dedicated multilevel programming algorithm. Measurement-based simulations have been then employed to evaluate the feasibility of PCM-based operations in the fields of Deep Neural Networks (DNNs) and Structural Health Monitoring (SHM). Moreover, a first testchip has been designed and tested to evaluate the hardware implementation of Multiply-and-Accumulate (MAC) operations employing PCM cells. This prototype experimentally demonstrates the possibility to reach a 95% MAC accuracy with a circuit-level compensation of cells time drift and non-linearity. Finally, empirical circuit behavior models have been included in simulations to assess the use of this technology in specific DNN applications, and to enhance the potentiality of this innovative computation approach.

Hypothalamic Inflammation And The Central Nervous System Control Of Energy Homeostasis.

The control of energy homeostasis relies on robust neuronal circuits that regulate food intake and energy expenditure. Although the physiology of these circuits is well understood, the molecular and cellular response of this program to chronic diseases is still largely unclear. Hypothalamic inflammation has emerged as a major driver of energy homeostasis dysfunction in both obesity and anorexia. Importantly, this inflammation disrupts the action of metabolic signals promoting anabolism or supporting catabolism. In this review, we address the evidence that favors hypothalamic inflammation as a factor that resets energy homeostasis in pathological states.

Impact Of Pregabalin Treatment On Synaptic Plasticity And Glial Reactivity During The Course Of Experimental Autoimmune Encephalomyelitis.

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease that affects young adults. It is characterized by generating a chronic demyelinating autoimmune inflammation in the central nervous system. An experimental model for studying MS is the experimental autoimmune encephalomyelitis (EAE), induced by immunization with antigenic proteins from myelin. The present study investigated the evolution of EAE in pregabalin treated animals up to the remission phase. The results demonstrated a delay in the onset of the disease with statistical differences at the 10th and the 16th day after immunization. Additionally, the walking track test (CatWalk) was used to evaluate different parameters related to motor function. Although no difference between groups was obtained for the foot print pressure, the regularity index was improved post treatment, indicating a better motor coordination. The immunohistochemical analysis of putative synapse preservation and glial reactivity revealed that pregabalin treatment improved the overall morphology of the spinal cord. A preservation of circuits was depicted and the glial reaction was downregulated during the course of the disease. qRT-PCR data did not show immunomodulatory effects of pregabalin, indicating that the positive effects were restricted to the CNS environment. Overall, the present data indicate that pregabalin is efficient for reducing the seriousness of EAE, delaying its course as well as reducing synaptic loss and astroglial reaction.

Effect Of Pain Chronification And Chronic Pain On An Endogenous Pain Modulation Circuit In Rats.

We tested the hypothesis that chronic pain development (pain chronification) and ongoing chronic pain (chronic pain) reduce the activity and induce plastic changes in an endogenous analgesia circuit, the ascending nociceptive control. An important mechanism mediating this form of endogenous analgesia, referred to as capsaicin-induced analgesia, is its dependence on nucleus accumbens μ-opioid receptor mechanisms. Therefore, we also investigated whether pain chronification and chronic pain alter the requirement for nucleus accumbens μ-opioid receptor mechanisms in capsaicin-induced analgesia. We used an animal model of pain chronification in which daily subcutaneous prostaglandin E2 (PGE2) injections into the rat's hind paw for 14 days, referred to as the induction period of persistent hyperalgesia, induce a long-lasting state of nociceptor sensitization referred to as the maintenance period of persistent hyperalgesia, that lasts for at least 30 days following the cessation of the PGE2 treatment. The nociceptor hypersensitivity was measured by the shortening of the time interval for the animal to respond to a mechanical stimulation of the hind paw. We found a significant reduction in the duration of capsaicin-induced analgesia during the induction and maintenance period of persistent mechanical hyperalgesia. Intra-accumbens injection of the μ-opioid receptor selective antagonist Cys(2),Tyr(3),Orn(5),Pen(7)amide (CTOP) 10 min before the subcutaneous injection of capsaicin into the rat's fore paw blocked capsaicin-induced analgesia. Taken together, these findings indicate that pain chronification and chronic pain reduce the duration of capsaicin-induced analgesia, without affecting its dependence on nucleus accumbens μ-opioid receptor mechanisms. The attenuation of endogenous analgesia during pain chronification and chronic pain suggests that endogenous pain circuits play an important role in the development and maintenance of chronic pain.

Plasticidade neural: relações com o comportamento e abordagens experimentais

Behavioral adaptiveness to different situations as well as behavioral individuality result from the interrelations between environmental sitmuli and the responses of an organism.These kind of interrelationships also shape the neural circuits as well as characterize the plasticity and the neural individuality of the organism. Studies on neural plasticity may analyze changes in neural circuitry after environmental manipulations or changes in behavior after lesions in the nervous system. Issues on neural plasticity and recovery of function refer both to physiology and behavior as well as to the subjacent mechanisms related to morphology, biochemistry and genetics. They may be approached at the systemic, behavioral, cellular and molecular levels. This work intends to characterize these kinds of studies pointing to their relations with the analyis of behavior and learning.The analysis of how the environmental-organismic interrelationships affect the neural substrates of behavior is pointed as a very stimulating area for investigation.