The Canadian Business Cycle: A Comparison of Models

This paper examines the ability of linear and nonlinear models to replicate features of real Canadian GDP. We evaluate the models using various business-cycle metrics. From the 9 data generating processes designed, none can completely accommodate every business-cycle metric under consideration. Richness and complexity do not guarantee a close match with Canadian data. Our findings for Canada are consistent with Piger and Morley's (2005) study of the United States data and confirms the contradiction of their results with those reported by Engel, Haugh, and Pagan (2005): nonlinear models do provide an improvement in matching business-cycle features. Lastly, the empirical results suggest that investigating the merits of forecast combination would be worthwhile.Business fluctuations and cycles; Econometric and statistical methods

Expanding Rapid Prototyping for Electronic Systems Integration of Arbitrary Form

An innovative method for rapid prototyping (RP) of electronic circuits with components characteristic of typical electronics applications was demonstrated using an enhanced version of a previously developed hybrid stereolithography (SL) and direct write (DW) system, where an existing SL machine was integrated with a three-axis DW fluid dispensing system for combined arbitrary form electronic systems manufacturing. This paper presents initial efforts at embedding functional electronic circuits using the hybrid SL/DW system. A simple temperature-sensitive circuit was selected, which oscillated an LED at a frequency proportional to the temperature sensed by the thermistor. The circuit was designed to incorporate all the required electronic components within a 2.5” x 2” x 0.5” SL part. Electrical interconnects between electronic components were deposited on the SL part with a DW system using silver conductive ink lines. Several inks were deposited, cured, and tested on a variety of SL resin substrates, and the E 1660 ink (Ercon Inc, Wareham, MA) was selected due to its measured lowest average resistivity on the SL substrates. The finished circuit was compared with Printed Circuit Board (PCB) technology for functionality. The electronic components used here include a low voltage battery, LM 555 timer chip, resistors, a thermistor, capacitors, and Light Emitting Diodes (LEDs). This circuit was selected because it (1) represented a simple circuit combining many typically used electronic components and thus provided a useful demonstration for integrated electronic systems manufacturing applicable to a wide variety of devices, and (2) provided an indication of the parasitic resistances and capacitances introduced by the fabrication process due to its sensitivity to manufacturing variation. The hybrid technology can help achieve significant size reductions, enable systems integration in atypical forms, a natural resistance to reverse engineering and possibly increase maximum operating temperatures of electronic circuits as compared to the traditional PCB process. This research demonstrates the ability of the hybrid SL/DW technology for fabricating combined electronic systems for unique electronics applications in which arbitrary form is a requirement and traditional PCB technology cannot be used.Mechanical Engineerin

HD 209458b in new light: evidence of nitrogen chemistry, patchy clouds and sub-solar water

Interpretations of exoplanetary transmission spectra have been undermined by apparent obscuration due to clouds/hazes. Debate rages on whether weak H2O features seen in exoplanet spectra are due to clouds or inherently depleted oxygen. Assertions of solar H2O abundances have relied on making a priori model assumptions, for example, chemical/radiative equilibrium. In this work, we attempt to address this problem with a new retrieval paradigm for transmission spectra. We introduce POSEIDON, a two-dimensional atmospheric retrieval algorithm including generalized inhomogeneous clouds. We demonstrate that this prescription allows one to break vital degeneracies between clouds and prominent molecular abundances. We apply POSEIDON to the best transmission spectrum presently available, for the hot Jupiter HD 209458b, uncovering new insights into its atmosphere at the day–night terminator. We extensively explore the parameter space with an unprecedented 108 models, spanning the continuum from fully cloudy to cloud-free atmospheres, in a fully Bayesian retrieval framework. We report the first detection of nitrogen chemistry (NH3 and/or HCN) in an exoplanet atmosphere at 3.7–7.7σ confidence, non-uniform cloud coverage at 4.5–5.4σ, high-altitude hazes at >3σ and sub-solar H2O at ≳3–5σ, depending on the assumed cloud distribution. We detect NH3 at 3.3σ, and 4.9σ for fully cloudy and cloud-free scenarios, respectively. For the model with the highest Bayesian evidence, we constrain H2O at 5–15 ppm (0.01–0.03) × solar and NH3 at 0.01–2.7 ppm, strongly suggesting disequilibrium chemistry and cautioning against equilibrium assumptions. Our results herald a new promise for retrieving cloudy atmospheres using high-precision Hubble Space Telescope and James Webb Space Telescope spectra

Glia Cell Morphology Analysis Using the Fiji GliaMorph Toolkit

Glial cells are the support cells of the nervous system. Glial cells typically have elaborate morphologies that facilitate close contacts with neighboring neurons, synapses, and the vasculature. In the retina, Müller glia (MG) are the principal glial cell type that supports neuronal function by providing a myriad of supportive functions via intricate cell morphologies and precise contacts. Thus, complex glial morphology is critical for glial function, but remains challenging to resolve at a sub-cellular level or reproducibly quantify in complex tissues. To address this issue, we developed GliaMorph as a Fiji-based macro toolkit that allows 3D glial cell morphology analysis in the developing and mature retina. As GliaMorph is implemented in a modular fashion, here we present guides to (a) setup of GliaMorph, (b) data understanding in 3D, including z-axis intensity decay and signal-to-noise ratio, (c) pre-processing data to enhance image quality, (d) performing and examining image segmentation, and (e) 3D quantification of MG features, including apicobasal texture analysis. To allow easier application, GliaMorph tools are supported with graphical user interfaces where appropriate, and example data are publicly available to facilitate adoption. Further, GliaMorph can be modified to meet users’ morphological analysis needs for other glial or neuronal shapes. Finally, this article provides users with an in-depth understanding of data requirements and the workflow of GliaMorph. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Download and installation of GliaMorph components including example data Basic Protocol 2: Understanding data properties and quality 3D—essential for subsequent analysis and capturing data property issues early Basic Protocol 3: Pre-processing AiryScan microscopy data for analysis Alternate Protocol: Pre-processing confocal microscopy data for analysis Basic Protocol 4: Segmentation of glial cells Basic Protocol 5: 3D quantification of glial cell morpholog

Robotic Motion Planning in Uncertain Environments via Active Sensing

Perception and control are at the foundation of automation, and in recent years, we have seen growth in feasible applications including self-driving cars and smart homes. As automation moves from regulated, well-monitored locations (e.g., factories) into society, uncertainty in hardware and the environment poses a safety concern. Within this thesis, we focus primarily on uncertainty in the environment and discuss models of the environment known a priori and learned as the robot functions. The robot is tasked with moving from one location or configuration to another while minimizing the expected cost of observation and motion actions. We focus on control that guides the robot to a position/configuration or identifies that it is impossible to reach the position/configuration. We first focus on a robot creating a plan, prior to deployment, based on a known environment model. This model encodes obstacle configurations into different environmental realizations along with a probability this realization will be encountered. The robot is also provided an observation model it may use to sense the environment during the task. We show that minimizing the expected cost from start to goal within these models is NP-Hard. Therefore, we present an efficient algorithm to create a policy which can react to obstacles in real-time while maintaining safety constraints on motion. A by-product of this algorithm is a lower bound on the expected cost of an optimal policy. We compare the policy and lower bound, generated by our algorithm, against that of an optimal policy and existing research. Our focus then shifts to remove prior information about environmental obstacles. We ask the robot to complete a finite number of start to goal tasks and show the general version of this problem is PSPACE-Hard. To reduce the complexity, we develop a method that uses an arbitrary reactionary algorithm from prior work to handle unexpected obstacles. For each new environment experienced, we incrementally update the robot's policy and show that the dependence on the reactionary algorithm is not increasing. Tests are performed on a flexible factory to demonstrate the scalability of this method