On the phase-space dynamics of systems of spiking neurons. I: model and experiments

We investigate the phase-space dynamics of a general model of local systems of biological neurons in order to deduce the salient dynamical characteristics of such systems. In this article, we present a detailed exposition of an abstract dynamical system that models systems of biological neurons. The abstract system is based on a limited set of realistic assumptions and thus accommodates a wide range of neuronal models. Simulation results are presented for several instantiations of the abstract system, each modeling a typical neocortical column to a different degree of accuracy. The results demonstrate that the dynamics of the systems are generally consistent with that observed in neurophysiological experiments. They reveal that the qualitative behavior of the class of systems can be classified into three distinct categories: quiescence, intense periodic activity resembling a state of seizure, and sustained chaos over the range of intrinsic activity typically associated with normal operational conditions in the neocortex. We discuss basic ramifications of this result with regard to the computational nature of neocortical neuronal systems.     

On the phase-space dynamics of systems of spiking neurons. II: formal analysis

We begin with a brief review of the abstract dynamical system that models systems of biological neurons, introduced in the original article. We then analyze the dynamics of the system. Formal analysis of local properties of flows reveals contraction, expansion, and folding in different sections of the phase-space. The criterion for the system, set up to model a typical neocortical column, to be sensitive to initial conditions is identified. Based on physiological parameters, we then deduce that periodic orbits in the region of the phase-space corresponding to normal operational conditions in the neocortex are almost surely (with probability 1) unstable, those in the region corresponding to seizure-like conditions are almost surely stable, and trajectories in the region corresponding to normal operational conditions are almost surely sensitive to initial conditions. Next, we present a procedure that isolates all basic sets, complex sets, and attractors incrementally. Based on the two sets of results, we conclude that chaotic attractors that are potentially anisotropic play a central role in the dynamics of such systems. Finally, we examine the impact of this result on the computational nature of neocortical neuronal systems.     

Tool path generation for free form surfaces using Bézier curves/surfaces

Presented in this paper is a tool path generation method for multi-axis machining of free-form surfaces using Bézier curves and surfaces. The tool path generation includes two core steps. First is the forward-step function that determines the maximum distance, called forward step, between two cutter contact (CC) points with a given tolerance. The second component is the side step function which determines the maximum distance, called side step, between two adjacent tool paths with a given scallop height. Using the Bézier curves and surfaces, we generate cutter contact (CC) points for free-form surfaces and cutter location (CL) data files for post processing. Several parts are machined using a multi-axis milling machine. As part of the validation process, the tool paths generated from Bézier curves and surfaces are analyzed to compare the machined part and the desired part.     

Children's differentiation between beliefs about matters of fact and matters of opinion.

Two experiments investigated children's implicit and explicit differentiation between beliefs about matters of fact and matters of opinion. In Experiment 1, 8- to 9-year-olds' (n = 88) explicit understanding of the subjectivity of opinions was found to be limited, but their conformity to others' judgments on a matter of opinion was considerably lower than their conformity to others' views regarding an ambiguous fact. In Experiment 2, children aged 6, 8, or 10 years (n = 81) were asked to make judgments either about ambiguous matters of fact or about matters of opinion and then heard an opposing judgment from an expert. All age groups conformed to the opposing judgments on factual matters more than they did to the experts' views on matters of opinion. However, only the oldest children explicitly recognized that opinions are subjective and cannot be "wrong." Implications of these results for models of children's reasoning about epistemic states are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fabrication and characterization of all-oxide heterojunction p-CuAlO2 + x/n-Zn1 − xAlxO transparent diode for potential application in “invisible electronics”

Transparent p-n heterojunction diodes have been fabricated by p-type copper aluminum oxide (p-CuAlO_2 + x) and n-type aluminum doped zinc oxide (n-Zn_1 − xAl_xO) thin films on glass substrates. The n-layers are deposited by sol-gel-dip-coating process from zinc acetate dihydrate (Zn(CH₃COO)₂·2H₂O) and aluminum nitrate (Al(NO₃)₃·9H₂O). Al concentration in the nominal solution is taken as 1.62 at %. P-layers are deposited onto the ZnO:Al-coated glass substrates by direct current sputtering process from a prefabricated CuAlO₂ sintered target. The sputtering is performed in oxygen-diluted argon atmosphere with an elevated substrate temperature. Post-deposition oxygen annealing induces excess oxygen within the p-CuAlO_2 + x films, which in turn enhances p-type conductivity of the layers. The device characterization shows rectifying current-voltage characteristics, confirming the proper formation of the p-n junction. The turn-on voltage is obtained around 0.8 V, with a forward-to-reverse current ratio around 30 at ± 4 V. The diode structure has a total thickness of 1.1 μm and the optical transmission spectra of the diode show almost 60% transmittance in the visible region, indicating its potential application in ‘invisible electronics’. Also the cost-effective procedures enable the large-scale production of these transparent diodes for diverse device applications.     

Discriminant Analysis Based Prognostics of Avionic Systems

In this paper, a novel discriminant analysis based predictive model for preventing false alarms leading to unnecessary replacement of an avionic system component is presented. The model is validated by prediction of false alarms (also known as false positives, type I, or alpha errors) in the left generator shaft of a Sikorsky helicopter UH-60, using the Goodrich health and usage management system (HUMS). The paper presents one of the first approaches based on applying discriminant analysis for prognostics of avionic systems, specifically in the context of identifying false positives within the next 1 or 2 h. In practice, predictions for the next 2 h are sufficient as typical helicopter flight schedules and durations are such that up to 2 h advance notice is most useful. This is an important contribution because drive train components of helicopters are normally very robust with very rare failures; therefore, the cost of unnecessary preventive maintenance based on false alarms is very high.     

Midwavelength Infrared Avalanche Photodiode Using InAs–GaSb Strain Layer Superlattice

InAs-GaSb strain layer superlattice p⁺-n^--n avalanche photodiodes (APDs) are fabricated using a newly introduced electron-beam aided zinc sulfide deposition. Temperature-dependent measurements were performed on 300 times 300 mum² mesa etched APDs. The effect of passivation was also studied on the diode characteristics and APD performances. Temperature-dependent gain strongly correlates with avalanche mechanism.     

Ultra-Thin Si<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>Ge<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> Dislocation Blocking Layers for Ge/Strained Si CMOS Devices

We demonstrate ultra-thin (<150 nm) Si_1−x Ge _x dislocation blocking layers on Si substrates used for the fabrication of tensile-strained Si N channel metal oxide semiconductor (NMOS) and Ge P channel metal oxide semiconductor (PMOS) devices. These layers were grown using ultra high vacuum chemical vapor deposition (UHVCVD). The Ge mole fraction was varied in rapid, but distinct steps during the epitaxial layer growth. This results in several Si_1−x Ge _x interfaces in the epitaxially grown material with significant strain fields at these interfaces. The strain fields enable a dislocation blocking mechanism at the Si_1−x Ge _x interfaces on which we were able to deposit very smooth, atomically flat, tensile-strained Si and relaxed Ge layers for the fabrication of high mobility N and P channel metal oxide semiconductor (MOS) devices, respectively. Both N and P channel metal oxide semiconductor field effect transister (MOSFETs) were successfully fabricated using high-k dielectric and metal gates on these layers, demonstrating that this technique of using ultra-thin dislocation blocking layers might be ideal for incorporating high mobility channel materials in a conventional CMOS process.     

A Case‐Based Reasoning system for complex medical diagnosis

A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR‐based expert system that uses the K‐nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto‐set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu‐driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real‐world PMS cases.     

Robust manufacturing system design using multi objective genetic algorithms,Petri nets and Bayesian uncertainty representation

Decisions involving robust manufacturing system configuration design are often costly and involve long term allocation of resources. These decisions typically remain fixed for future planning horizons and failure to design a robust manufacturing system configuration can lead to high production and inventory costs, and lost sales costs. The designers need to find optimal design configurations by evaluating multiple decision variables (such as makespan and WIP) and considering different forms of manufacturing uncertainties (such as uncertainties in processing times and product demand). This paper presents a novel approach using multi objective genetic algorithms (GA), Petri nets and Bayesian model averaging (BMA) for robust design of manufacturing systems. The proposed approach is demonstrated on a manufacturing system configuration design problem to find optimal number of machines in different manufacturing cells for a manufacturing system producing multiple products. The objective function aims at minimizing makespan, mean WIP and number of machines, while considering uncertainties in processing times, equipment failure and repairs, and product demand. The integrated multi objective GA and Petri net based modeling framework coupled with Bayesian methods of uncertainty representation provides a single tool to design, analyze and simulate candidate models while considering distribution model and parameter uncertainties.