The Dynamics of Food Deprivation and Overall Health: Evidence from the Canadian National Population Health Survey

The paper explores whether the responses to food deprivation questions on the longitudinal Canadian National Population Health Survey help explain the links between socio-economic status and health. Transitions in food deprivation status are correlated with changes in health status. While health transitions are correlated with changes in food deprivation status, there is little evidence that change in food deprivation status leads changes in health status but some evidence that change in health status leads change in food deprivation status.Food insecurity; Granger causality

The Dynamics of Food Deprivation and Overall Health: Evidence from the Canadian National Population Health Survey

The paper explores whether the responses to food deprivation questions on the longitudinal Canadian National Population Health Survey help explain the links between socio-economic status and health. Transitions in food deprivation status are correlated with changes in health status. While health transitions are correlated with changes in food deprivation status, there is little evidence that change in food deprivation status leads changes in health status but some evidence that change in health status leads change in food deprivation status.Food insecurity; Granger causality; NPHS

Recommending Learning Algorithms and Their Associated Hyperparameters

The success of machine learning on a given task dependson, among other things, which learning algorithm is selected and its associated hyperparameters. Selecting an appropriate learning algorithm and setting its hyperparameters for a given data set can be a challenging task, especially for users who are not experts in machine learning. Previous work has examined using meta-features to predict which learning algorithm and hyperparameters should be used. However, choosing a set of meta-features that are predictive of algorithm performance is difficult. Here, we propose to apply collaborative filtering techniques to learning algorithm and hyperparameter selection, and find that doing so avoids determining which meta-features to use and outperforms traditional meta-learning approaches in many cases.Comment: Short paper--2 pages, 2 table

Superacid Chemistry on Mildly Acidic Water

The mechanism of proton transfer across water−hydrophobic media boundaries is investigated in experiments in which the protonation of gaseous n-hexanoic acid (PCOOH) upon collision with liquid water microjets is monitored by online electrospray mass spectrometry as a function of pH. Although PCOOH(aq) is a very weak base (pK_(BH+) < −3), PCOOH(g) is converted to PC(OH)_2^+ on pH < 4 water via a process that ostensibly retains some of the exoergicity of its gas-phase counterpart, PCOOH + H_3O^+ = PC(OH)_2^+ + H_2O, ΔG < −22 kcal mol^(−1). The large kinetic isotope effects observed on H_2O/D_2O microjets, PC(OH)_2^+/PC(OH)OD^+ = 88 and PC(OH)OD^+/PC(OD)_2^+ = 156 at pD = 2, and their inverse dependences on pH indicate that PCOOH(g) hydronation on water (1) involves tunneling, (2) is faster than H-isotope exchange, and (3) is progressively confined to the outermost layers as water becomes more acidic. Proton transfers across steep water density gradients appear to be promoted by both dynamic and thermodynamic factors

Modeling Quantum Optical Components, Pulses and Fiber Channels Using OMNeT++

Quantum Key Distribution (QKD) is an innovative technology which exploits the laws of quantum mechanics to generate and distribute unconditionally secure cryptographic keys. While QKD offers the promise of unconditionally secure key distribution, real world systems are built from non-ideal components which necessitates the need to model and understand the impact these non-idealities have on system performance and security. OMNeT++ has been used as a basis to develop a simulation framework to support this endeavor. This framework, referred to as "qkdX" extends OMNeT++'s module and message abstractions to efficiently model optical components, optical pulses, operating protocols and processes. This paper presents the design of this framework including how OMNeT++'s abstractions have been utilized to model quantum optical components, optical pulses, fiber and free space channels. Furthermore, from our toolbox of created components, we present various notional and real QKD systems, which have been studied and analyzed.Comment: Published in: A. F\"orster, C. Minkenberg, G. R. Herrera, M. Kirsche (Eds.), Proc. of the 2nd OMNeT++ Community Summit, IBM Research - Zurich, Switzerland, September 3-4, 201

Cybersecurity Architectural Analysis for Complex Cyber-Physical Systems

In the modern military’s highly interconnected and technology-reliant operational environment, cybersecurity is rapidly growing in importance. Moreover, as a number of highly publicized attacks have occurred against complex cyber-physical systems such as automobiles and airplanes, cybersecurity is no longer limited to traditional computer systems and IT networks. While architectural analysis approaches are critical to improving cybersecurity, these approaches are often poorly understood and applied in ad hoc fashion. This work addresses these gaps by answering the questions: 1. “What is cybersecurity architectural analysis?” and 2. “How can architectural analysis be used to more effectively support cybersecurity decision making for complex cyber-physical systems?” First, a readily understandable description of key architectural concepts and definitions is provided which culminates in a working definition of “cybersecurity architectural analysis,” since none is available in the literature. Next, we survey several architectural analysis approaches to provide the reader with an understanding of the various approaches being used across government and industry. Based on our proposed definition, the previously introduced key concepts, and our survey results, we establish desirable characteristics for evaluating cybersecurity architectural analysis approaches. Lastly, each of the surveyed approaches is assessed against the characteristics and areas of future work are identified

Structure of amyloid-β (20-34) with Alzheimer's-associated isomerization at Asp23 reveals a distinct protofilament interface.

Amyloid-β (Aβ) harbors numerous posttranslational modifications (PTMs) that may affect Alzheimer's disease (AD) pathogenesis. Here we present the 1.1 Å resolution MicroED structure of an Aβ 20-34 fibril with and without the disease-associated PTM, L-isoaspartate, at position 23 (L-isoAsp23). Both wild-type and L-isoAsp23 protofilaments adopt β-helix-like folds with tightly packed cores, resembling the cores of full-length fibrillar Aβ structures, and both self-associate through two distinct interfaces. One of these is a unique Aβ interface strengthened by the isoaspartyl modification. Powder diffraction patterns suggest a similar structure may be adopted by protofilaments of an analogous segment containing the heritable Iowa mutation, Asp23Asn. Consistent with its early onset phenotype in patients, Asp23Asn accelerates aggregation of Aβ 20-34, as does the L-isoAsp23 modification. These structures suggest that the enhanced amyloidogenicity of the modified Aβ segments may also reduce the concentration required to achieve nucleation and therefore help spur the pathogenesis of AD

400%/W second harmonic conversion efficiency in 14μm\mathrm{14 \mu m}-diameter gallium phosphide-on-oxide resonators

Second harmonic conversion from 1550~nm to 775~nm with an efficiency of 400% W$^{-1}$ is demonstrated in a gallium phosphide (GaP) on oxide integrated photonic platform. The platform consists of doubly-resonant, phase-matched ring resonators with quality factors $Q \sim 10^4$, low mode volumes $V \sim 30 (\lambda/n)^3$, and high nonlinear mode overlaps. Measurements and simulations indicate that conversion efficiencies can be increased by a factor of 20 by improving the waveguide-cavity coupling to achieve critical coupling in current devices.Comment: 13 pages, 6 figure