Medial opening wedge high tibial osteotomy: A retrospective review of patient outcomes over 10 years

Objectives: High tibial osteotomy (HTO) has become a well-established treatment for unicompartmental osteoarthritis of the knee. Over the last 30 years, various techniques have been introduced to advance this procedure. The purpose of this study is to review the outcomes of patients who received medial opening wedge HTO over the last ten years (2002-2012) using a modern, low profile, medially based fixation device. In addition, we sought to determine if obese patients had a less favorable outcome than their non-obese counterparts. Methods: Ninety-three patients were identified from a surgical database as having undergone a HTO for medial compartment osteoarthritis of the knee with varus mal-alignment. All procedures were performed by one of two fellowship trained orthopedic surgeons from 2002-2012 utilizing a low profile fixation device and identical surgical technique. Minimum follow-up was one year for inclusion in the study. Outcomes were measured using Lysholm and WOMAC scores. Radiographs were evaluated to determine delayed union or non-union at the osteotomy site and surveillance was undertaken to evaluate post operative complications. Results: 93 patients were identified from the database, 63 (70%) were available for follow-up and are included in this analysis. Average follow-up time was 48 months (range 17 to 137). There were 44 males and 19 females. The average age was 45 years old. The average final Lysholm and WOMAC scores were 66.4 (range: 13-100) and 18.6 (range: 0-86) respectively. There was no significant difference in reported Lysholm or WOMAC scores between obese (BMI \u3e30) and non-obese patients (p=.31;p=.69). Complications were as follows: 3 patients required a surgical lysis of adhesions, 2 patients developed an infection, and 1 patient experienced a delayed union. At final follow-up, 18 patients received additional treatment on the affected knee: 11 required removal of symptomatic hardware, 5 received viscosupplementation, 2 underwent a total knee replacement. Conclusion: Low profile, medial based devices used in the setting of HTO is an accepted treatment for unicompartmental osteoarthritis of the knee. At final follow-up, a majority of patients reported positive outcomes and few complications. 18 patients required additional treatment for osteoarthritis. In our analysis, obese patients faired equally as well as their non-obese counterparts, with no significant difference in outcomes scores or complication rate. Survivorship of high tibial osteotomy was excellent in this series, with only 2 patients having undergone total knee replacement at last follow-up. © The Author(s) 2015

Using the Regular Chains Library to build cylindrical algebraic decompositions by projecting and lifting

Cylindrical algebraic decomposition (CAD) is an important tool, both for quantifier elimination over the reals and a range of other applications. Traditionally, a CAD is built through a process of projection and lifting to move the problem within Euclidean spaces of changing dimension. Recently, an alternative approach which first decomposes complex space using triangular decomposition before refining to real space has been introduced and implemented within the RegularChains Library of Maple. We here describe a freely available package ProjectionCAD which utilises the routines within the RegularChains Library to build CADs by projection and lifting. We detail how the projection and lifting algorithms were modified to allow this, discuss the motivation and survey the functionality of the package

Structure and Dynamics of the Globular Cluster Palomar 13

We present Keck/DEIMOS spectroscopy and Canada-France-Hawaii Telescope/MegaCam photometry for the Milky Way globular cluster Palomar 13. We triple the number of spectroscopically confirmed members, including many repeat velocity measurements. Palomar 13 is the only known globular cluster with possible evidence for dark matter, based on a Keck/High Resolution Echelle Spectrometer 21 star velocity dispersion of σ = 2.2 ± 0.4 km s^(–1). We reproduce this measurement, but demonstrate that it is inflated by unresolved binary stars. For our sample of 61 stars, the velocity dispersion is σ = 0.7^(+0.6)_(–0.5) km s^(–1). Combining our DEIMOS data with literature values, our final velocity dispersion is σ = 0.4^(+0.4)_( –0.3) km s^(–1). We determine a spectroscopic metallicity of [Fe/H] = –1.6 ± 0.1 dex, placing a 1σ upper limit of σ_([Fe/H]) ~ 0.2 dex on any internal metallicity spread. We determine Palomar 13's total luminosity to be M_V = –2.8 ± 0.4, making it among the least luminous known globular clusters. The photometric isophotes are regular out to the half-light radius and mildly irregular outside this radius. The outer surface brightness profile slope is shallower than typical globular clusters (Σ α r^η, η = –2.8 ± 0.3). Thus at large radius, tidal debris is likely affecting the appearance of Palomar 13. Combining our luminosity with the intrinsic velocity dispersion, we find a dynamical mass of M_(1/2) = 1.3^(+2:7)_(–1.3) × 10^3 M_☉ and a mass-to-light ratio of M/L_V = 2.4^(+5.0)_(–2.4) M_☉/L_☉. Within our measurement errors, the mass-to-light ratio agrees with the theoretical predictions for a single stellar population. We conclude that, while there is some evidence for tidal stripping at large radius, the dynamical mass of Palomar 13 is consistent with its stellar mass and neither significant dark matter, nor extreme tidal heating, is required to explain the cluster dynamics

Using geophysical surveys to test tracer-based storage estimates in headwater catchments

Acknowledgements The authors are grateful to Stian Bradford, Chris Gabrielli, and Julie Timms for practical and logistical assistance. The provision of transport by Iain Malcolm and Ross Glover of Marine Scotland Science was greatly appreciated. We also thank the European Research Council ERC (project GA 335910 VEWA) for funding through the VeWa project and the Leverhulme Trust for funding through PLATO (RPG-2014-016).Peer reviewedPostprin

Applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition

Cylindrical algebraic decomposition(CAD) is a key tool in computational algebraic geometry, particularly for quantifier elimination over real-closed fields. When using CAD, there is often a choice for the ordering placed on the variables. This can be important, with some problems infeasible with one variable ordering but easy with another. Machine learning is the process of fitting a computer model to a complex function based on properties learned from measured data. In this paper we use machine learning (specifically a support vector machine) to select between heuristics for choosing a variable ordering, outperforming each of the separate heuristics.Comment: 16 page

Horn-Coupled, Commercially-Fabricated Aluminum Lumped-Element Kinetic Inductance Detectors for Millimeter Wavelengths

We discuss the design, fabrication, and testing of prototype horn-coupled, lumped-element kinetic inductance detectors (LEKIDs) designed for cosmic microwave background (CMB) studies. The LEKIDs are made from a thin aluminum film deposited on a silicon wafer and patterned using standard photolithographic techniques at STAR Cryoelectronics, a commercial device foundry. We fabricated twenty-element arrays, optimized for a spectral band centered on 150 GHz, to test the sensitivity and yield of the devices as well as the multiplexing scheme. We characterized the detectors in two configurations. First, the detectors were tested in a dark environment with the horn apertures covered, and second, the horn apertures were pointed towards a beam-filling cryogenic blackbody load. These tests show that the multiplexing scheme is robust and scalable, the yield across multiple LEKID arrays is 91%, and the noise-equivalent temperatures (NET) for a 4 K optical load are in the range 26\thinspace\pm6 \thinspace \mu \mbox{K} \sqrt{\mbox{s}}

Near-Infrared Molecular Hydrogen Emission from the Central Regions of Galaxies: Regulated Physical Conditions in the Interstellar Medium

The central regions of many interacting and early-type spiral galaxies are actively forming stars. This process affects the physical and chemical properties of the local interstellar medium as well as the evolution of the galaxies. We observed near-infrared H2 emission lines: v=1-0 S(1), 3-2 S(3), 1-0 S(0), and 2-1 S(1) from the central ~1 kpc regions of the archetypical starburst galaxies, M82 and NGC 253, and the less dramatic but still vigorously star-forming galaxies, NGC 6946 and IC 342. Like the far-infrared continuum luminosity, the near-infrared H2 emission luminosity can directly trace the amount of star formation activity because the H2 emission lines arise from the interaction between hot and young stars and nearby neutral clouds. The observed H2 line ratios show that both thermal and non-thermal excitation are responsible for the emission lines, but that the great majority of the near-infrared H2 line emission in these galaxies arises from energy states excited by ultraviolet fluorescence. The derived physical conditions, e.g., far-ultraviolet radiation field and gas density, from [C II] and [O I] lines and far-infrared continuum observations when used as inputs to photodissociation models, also explain the luminosity of the observed H2 v=1-0 S(1) line. The ratio of the H2 v=1-0 S(1) line to far-IR continuum luminosity is remarkably constant over a broad range of galaxy luminosities; L_H2/L_FIR = about 10^{-5}, in normal late-type galaxies (including the Galactic center), in nearby starburst galaxies, and in luminous IR galaxies (LIRGs: L_FIR > 10^{11} L_sun). Examining this constant ratio in the context of photodissociation region models, we conclude that it implies that the strength of the incident UV field on typical molecular clouds follows the gas density at the cloud surface.Comment: Accepted for ApJ, 24 pages, 17 figures, for complete PDF file, see http://kao.re.kr/~soojong/mypaper/2004_pak_egh2.pd

Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty

Dynamic real-time optimization (DRTO) is a challenging task due to the fact that optimal operating conditions must be computed in real time. The main bottleneck in the industrial application of DRTO is the presence of uncertainty. Many stochastic systems present the following obstacles: 1) plant-model mismatch, 2) process disturbances, 3) risks in violation of process constraints. To accommodate these difficulties, we present a constrained reinforcement learning (RL) based approach. RL naturally handles the process uncertainty by computing an optimal feedback policy. However, no state constraints can be introduced intuitively. To address this problem, we present a chance-constrained RL methodology. We use chance constraints to guarantee the probabilistic satisfaction of process constraints, which is accomplished by introducing backoffs, such that the optimal policy and backoffs are computed simultaneously. Backoffs are adjusted using the empirical cumulative distribution function to guarantee the satisfaction of a joint chance constraint. The advantage and performance of this strategy are illustrated through a stochastic dynamic bioprocess optimization problem, to produce sustainable high-value bioproducts